Integration of Structural Health Monitoring Systems into Unmanned Aerial Systemsâ€”Challenges and Opportunities
There is a simple reason for the dramatic growth in use of Unmanned Air Systems (UAS). Today's operations with strict rules of engagement create an insatiable appetite for intelligence, surveillance and reconnaissance (ISR) in particular in the form of live video-streams, imagery and signal intelligence. In this mission spectrum, UAS platforms offer appealingly low sustainment costs. The challenges and limits of UAS must be seen as opportunities. Defining the margin of UAS effectiveness is the first step toward identifying where manned or unmanned systems are the better solution. The big question is whether the UAS market will continue its rapid growth and whether we can develop the right technology in time and cost. It will be essential to verify and validate the more complicated level of UAS autonomy and predictable through life support costs. Open system architecture coupled with enhanced health monitoring, embedded diagnostics and prognostics leading to automated decision support are key technologies of the R&T roadmap to support the development of UASs. All these technologies will have a main contribution to meet the certification requirements. SHM is seen as a sub-system within a UAS Integrated System Health Management where information from a variety of sources is gathered in order to generate a component Health Assessment and estimate the component Remaining Useful Life for prognostic purposes.
The Journey to Incorporate Health Monitoring and Condition Based Maintenance of Sikorsky Commercial Helicopters
This paper is a discussion of the journey Sikorsky Aircraft Corporation (SAC) is on to incorporate vehicle health monitoring (VHM) and condition-based maintenance (CBM) capabilities into all our products. The paper focuses on SACâ€™s S-92Â® aircraft, which was introduced in 2004 and was the first commercial helicopter fielded with a state-of-the-art HUMS integrated into the baseline aircraft. From day one, SAC has collected aircraft generated data and established data management, analysis, and decision making processes to provide maximum benefit to the operator with reasonable man-in-the-loop support. The paper discusses the development of automated processes for collecting data daily from operators from around the world; analyzing, trending, and flagging data for follow-up by subject matter experts; and mining data to establish normal versus anomalous behavior. The paper will also discuss SACâ€™s Fleet Management Operations Center (FMOC) which was created to promote a collaborative environment between subject matter experts from various engineering and support services groups and to quickly recommend appropriate maintenance actions. Lastly, the paper discusses SACâ€™s efforts to develop processes that can be used to achieve maintenance credits (e.g., TBO and retirement time extensions) and to expand health management across all aircraft subsystems.
Embraer Perspective on the Introduction of SHM into Current and Future Commercial Aviation Programs
Knowledge about Structural Health Monitoring (SHM) evolved considerably on the last 15 years and all major aircraft manufactures are conducting their own SHM Research and Development (R&D) programs. Nevertheless, it is still not common to see SHM systems playing significant role in current commercial aviation maintenance programs. This paper presents Embraerâ€™s perspective on the introduction of SHM into current and future commercial aviation programs based mainly on the latest discussions and changes to the Air Transport Associationâ€™s Maintenance Steering Group 3 (MSG-3) methodology, used for scheduled maintenance program development. Effects on the maintenance review board process and aircraft maintenance manuals are also analyzed. Additionally, it briefly presents Embraerâ€™s general suggestions that should be taken into consideration by the SHM community in order to make it possible to start realizing some of the SHM potential.
Structural Health Monitoring for Civil Infrastructureâ€”From Instrumentation to Decision Support
In this paper, we examine the main components of structural health monitoring systems of civil infrastructure that are needed for a widespread implementation. These include instrumentation, structural system damage diagnosis and prognosis, and information delivery. The type of instrumentation is governed by the structural properties and types of damage anticipated to occur due to different loading and environmental conditions. Damage diagnosis is to a great extent dependent on the type of instrumentation used, the structural behavior, and the needs of the end-user of the information. Factors that are unique or specific to civil structures are highlighted and key impediments to implementation of the current state of monitoring are presented. It is recognized that one of the key impediments to implementation is the availability of damage diagnosis algorithms and tools. Current research on damage-diagnosis using statistical pattern recognition methods is briefly summarized drawing on the research of the author and her research team. The paper concludes with current gaps in knowledge and research needs that will advance the state of science and engineering in the field.
Does the Maturity of Structural Health Monitoring Technology Match User Readiness?
The use of in-situ sensors for real-time health monitoring of aircraft structures can be a viable option to overcome inspection impediments stemming from accessibility limitations, complex geometries, and the location and depth of hidden damage. Reliable, structural health monitoring (SHM) systems can automatically process data, assess structural condition, and signal the need for human intervention. There is a significant need for an overarching plan that will guide near-term and long-term activities and will uniformly and comprehensively support the evolution and adoption of SHM practices. Such a plan must contain input from aircraft manufacturers, regulators, operators, and research organizations so that the full spectrum of issues, ranging from design to deployment, performance and certification is appropriately considered. An important element in developing the FAA SHM R&D Roadmap is a clear understanding of the current status of SHM technology and the pending regulatory issues facing the aviation industry to safely adopt SHM solutions. Towards that end, a comprehensive survey was implemented with the aviation industry to determine the technology maturation level of SHM, identify integration issues, and prioritize research and development needs associated with implementing SHM on aircraft. Specific emphasis was placed on structural and maintenance characteristics that may impact the operational performance of an inspection process or health monitoring system. In addition, an SHM Technology Readiness Database (SHM TReaD) and an SHM Sensor Database were developed to assess the present and future prospects of SHM technology. This paper will present the results from these efforts and describe how the FAA is using this information to support the safe adoption of SHM practices.
Damage Diagnosis Algorithm for Civil Structures Using a Sequential Change Point Detection Method and Time-Series Analysis
This paper introduces a structural damage diagnosis algorithm that uses time-series analysis to extract damage sensitive features (DSFs) from structural responses and a single fault sequential change point detection method to classify those features into damage states. This algorithm provides the optimum asymptotic solution for the problem of minimizing the fault detection time delay given a false alarm rate. The advantage of this algorithm comes from its sequential nature, which allows us to make a decision from a series of observations instead of one, eliminating the need for all past observations to be stored. For validation, we applied the algorithm to a set of white noise shake table test data collected from a four-story steel momentresisting frame. The results show that the algorithm can identify damage, particularly when it uses multi-dimensional DSFs and lower false alarm rates, but further study is necessary for damage localization.
Cointegration theory from the field of econometrics has recently been suggested by the authors as a useful tool for structural health monitoring. If two or more nonstationary variables are cointegrated, then some linear combination of them will be stationary, which is to say that common trends shared by the variables can be purged. In SHM, this could be particularly useful where features contain environmental or operational trends (a temperature dependency, for example) that can often mask any changes in structural response caused by damage. In this situation, cointegration can be used to combine monitored variables and create a feature independent of environmental or operational variations but still sensitive to damage.
Piezoceramic-Based 2-D Spiral Phased Array for Damage Detection of Thin Orthotropic Composite Laminates
In this paper, a new 2-D phased array signal processing method for structural health monitoring (SHM) of thin orthotropic composite laminates is presented. The new method is developed by applying experimental wavenumber and wavefront curves to the same algorithm structure of the original 2-D phased array signal processing. The wavenumber and wavefront curves are experimentally determined for thin unidirectional and cross-ply laminates. Piezoceramic-based 2-D spiral phased array is used as a sensor array, and multiple piezoceramic elements are used as actuators in the experiments. Damage detection of the composite laminates is investigated with the spiral array and the new signal processing method, using the guided Lamb wave (GLW) technique.
Guided Wave and Probability Based Diagnostic Imaging for Detection of Multiple Welding Damages in Welded Tubular Steel Structures
Propagation of guided waves (GWs) in a welded tubular steel structure (WTSS) with rectangular cross-section is investigated using experimental analysis and finite element method (FEM) simulation with the purpose of identifying multiple welding damages on it. A sensor network made up of sixteen piezoelectric wafers is established on the WTSS, generating and collecting GWs. With the aid of a series of signal processing, a time-domain feature, termed â€˜time of maximal differenceâ€™ (ToMD) is extracted from each captured GW signal. Base on the ToMDs, a novel concept â€˜damage presence probabilityâ€™ (DPP) is consequently defined. Finally, a probability-based damage imaging approach and a two-level image fusion scheme are adopted to predict presence and location of two different damages in welding zones of the WTSS as validation. Both simulation and experimental results demonstrate the effectiveness of the developed approach for identifying multiple damages in similar structures.
Nonlinear Cointegration as a Combinatorial Optimisation Problem
Recent papers by the authors have explored the possibility of furthering SHM research by adopting techniques from time series analysis carried out in the context of econometrics. In particular, the method of cointegration shows great promise as a means of removing environmental and operational effects from SHM feature data. Essentially, cointegration allows the combination of multiple features in such a way as to purge the combination of any common trends e.g. variations due to changing environmental temperature. One major limitation of the established cointegration theory is that it is a linear one and does not accommodate the possibility that a nonlinear combination of variates may be needed in order to completely remove environmental and/or operational effects. In a previous paper, the authors made use of an evolutionary algorithm in order to create a nonlinear combination of variates. This algorithm was based on the idea that all possible multinomials in the variates might appear in a parametrised sum. In situations with many features, the previous approach is likely to run into difficulties due to the fact that the number of candidate terms grows explosively with the number of features. In the current paper, an alternative approach is taken whereby the optimisation procedure is used to select an optimal subset of the candidate terms, with the parameters for combination then determined by exploiting linear cointegration theory. The application of the method is demonstrated via system simulation of data.
Characterizing Damage in Plate Structures Based on Local Perturbance to Dynamic Equilibrium
Although vibration-based damage detection has been practiced over the years with demonstrated success, such a technique may suffer from some bottlenecks including strong dependence on benchmarks, baseline signals or pre-developed global models, needs of additional excitation sources, excessive susceptivity to boundary conditions but less sensitivity to damage until it reach a noticeable level. A novel damage identification approach was developed by examining the local perturbance to structural equilibrium characteristics described by higher-order spatial derivatives. To reduce the influence of measurement noise on identification accuracy during obtaining higher-order spatial derivatives, two de-noising options were proposed including applying a wavenumber-based signal filtering and appropriately adjusting measurement configuration, to enhance the capacity of noise-tolerance of the method. The developed approach was experimentally validated by detecting damage in a plate component of a structural system with irregular boundaries, showing satisfactory results in pinpointing the damage. In principle the method is applicable to complex systems comprising various structural components such as beams, plates and shells, provided that the local equilibrium relationship for the component under current inspection is known a prior.
Robust Diagnostics for Bayesian Compressive Sensing Technique in Structural Health Monitoring
Signal compression is often important to reduce the cost of data transfer and storage for structural health monitoring (SHM) systems of civil structures. Compressive sensing is a novel data compressing method whereby one does not measure the entire signal directly but rather a set of related (â€œprojectedâ€) measurements. The length of the required compressive-sensing measurements is typically much smaller than the original signal, therefore increasing the efficiency of data transfer and storage. Recently, a Bayesian formalism has also been employed for optimal compressive sensing, which adopts the ideas in the relevance vector machine (RVM) as a decompression tool. In this article, we study the robustness of the BCS method. We show that the usual RVM optimization algorithm lacks robustness when the number of measurements is a lot less than the length of the signals because it can produce sub-optimal signal representations; as a result, BCS is not robust when high compression efficiency is required. This induces a tradeoff between efficiently compressing data and accurately decompressing it. Based on a study of the robustness of the BCS method, diagnostic tools are proposed to investigate whether the compressed representation of the signal is optimal. The numerical results also are given to validate the proposed method.
Damage Monitoring and Evaluation for Building Structures Based on Measurement of Relative Story Displacements by Noncontact-Type Sensors
This study presents the formulation of a damage monitoring and evaluation method for building structures based on the measurement of Relative Story Displacements (RSDs) by noncontact-type optical sensors. The damage evaluation method is formulated to detect the damaged locations of structural elements and evaluate their damage degree based on the displacement loading analysis by the time histories of measured RSDs. Furthermore in the evaluation process, the analytical technique is introduced to compensate for the measurement errors associated with the properties of sensors. The monitoring accuracies are analyzed through numerical simulations on a model building subjected to a large earthquake. The results indicate the effectiveness of the proposed method in its applications to the Structural Health Monitoring (SHM) system.
Joint Condition Identification with Partially Measured Frequency Response Function
Various joints are important parts of structures and more likely to develop deteriorations than other structure parts, which are considered as substructures in the present paper. Therefore, it is necessary to examine the condition of joints from time to time. The condition of a joint can be represented by its parameters, such as stiffness and damping. In this paper, the dynamic stiffness and/or Frequency Response (FRFs) of joints are taken as condition parameters and a method for identifying these condition parameters within a structure assembled of substructures and joint structures with partially measured frequency response function is proposed. Four basic formulas are derived first and with these four formulas a method for estimating FRFs is developed as the second step of the identification procedure. Since the unmeasured FRFs of an unconstrained substructure can be easily obtained through modal calibration, this estimation method is for obtaining those of the assembled structure. Data used in the estimation contains the measured FRFs of assembled structure and those calculated from accurately calibrated substructure Finite Element (FE) model. To enhance the identification accuracy, the derived four basic formulas are integrated together to form a united form formula for utilizing all available data, i.e. all measured and estimated FRFs. With this approach, the identification accuracy can be significantly improved. An experimental example is provided to describe the identification procedure and show the effectiveness of the proposed method.
Multi-Classifier Fusion Method Based on the Reliability of the Individual Classifiers
Multi-classifier fusion is a technique used to combine individual decisions of several classifiers in order to improve the final classification performance. Fusion methodologies are necessary to realize multi-classifiers-based monitoring systems. It leads to more accurate decisions. In this paper two fusion approaches are presented. First approach is based on the reliability analysis and Dempster-Shafer theory (DST) for fault analysis. The first approach is appropriate to combine two independent classifiers. The second approach is developed to combine any number of independent classifiers. It is based on an Artificial Neural Network (ANN). The realized ANN includes two hidden layers. First layer will be tuned using the weighting factors w to make an acceptable decision about the current state of the system. The second layer includes the activation functions to define the decision boundary between different system states.
Validation of a Hybrid Automated Modal Identification Algorithm for Structural Health Monitoring Applications
In recent years a growing interest in systems and techniques for fast damage detection based on vibration analysis has raised. Modal-based damage detection algorithms are well-known techniques for structural health assessment. The development of several automated output-only modal identification procedures in the last few years has led to a renewed interest in such techniques. However, robustness of the automated modal identification algorithms towards slightly non-stationary excitation, computational efforts and reliability of modal parameter and, in particular, damping estimates still represent not definitely solved issues. In this paper, starting from the lessons learned about the performance of popular operational modal analysis techniques, an hybrid algorithm for automated output-only modal parameter estimation for structural health monitoring purposes is proposed. It has been obtained from different modal identification algorithms through a hybridization process and, as such, some issues concerning the interpretation of stabilization diagrams are overcome. The main advantages of the novel technique are represented by the possibility to control the computational time and to obtain also reliable and very accurate damping estimates. Performance of the proposed procedure are assessed through its application to simulated and real measurements. Results confirm the robustness and accuracy of the algorithm, which can be certainly employed to monitor the modal parameters of large civil structures such as bridges and tall buildings.
Power Losses in PZT Disk Actuators' Adhesive
Piezoelectric patches are used in structural health monitoring (SHM) to generate diagnostic acoustic waves traveling in a structure and to gather the electro-mechanical impedance (EMI) signatures of structures. Piezoelectric patches are generally bonded to structures by means of adhesive layers. The adhesive layers could affect both the amplitude of the generated acoustic waves and the EMI signature of the structure. This article describes an analytical model to account for the power losses incurred by the adhesive layer used to bond a circular actuator to a structure at resonance. Validation of the model was carried out by actuating various sensors mounted with epoxy adhesive thickness ranging from 20 to 640 Î¼m on aluminum plates. Experimental results confirmed that the thickness and the tangent loss modulus of the adhesive layer might play a significant role in the energy dissipated. In addition, this article explains how to interpret low-frequency EMI signature to assess the quality of a bond and estimate the thickness of the adhesive layer.
Sensitivity of the Excitelet Imaging Algorithm on Material Properties for Isotropic Structures
Imaging techniques such as EUSR or Excitelet algorithms used in guided wave damage detection rely on an accurate knowledge of group or phase velocities. The problem is that variability in material properties directly affects the guided wave dispersion curves. Traditional approaches to mechanical characterization are based on ASTM standards. However, most of these techniques require numerous specimens to test and evaluate the properties of a structure within a few percents. The main goal of this paper is to assess a new integrated characterization approach to identify the mechanical properties of an isotropic structure (Young's modulus, Poisson's ratio, density) onto which imaging is performed to detect damage. The integrated characterization approach is based on a modified version of the Excitelet algorithm, where mechanical properties, instead of geometrical features, are set as the variables to be identified. This paper thus aims at evaluating the benefit of using the same array of transducers, and similar signal processing tools, to first identify the mechanical properties of the structure using a modified version of the Excitelet algorithm and then produce an image of this structure using the standard Excitelet imaging algorithm. The experimental setup consists of an aluminum plate with a 2 mm notched hole and instrumented with a linear array of seven circular elements micro-machined from bulk piezoceramic (PZT). Excitelet imaging is performed with the linear array and the characterization uses this same array and an extra PZT transducer located in the near field of the array. In this paper, low order Lamb modes are exploited for both characterization and imaging techniques. The results obtained for the properties identified with the modified Excitelet algorithm are within 1% of properties from the material supplier. Imaging results are then presented using Excitelet with both A0 and S0 modes at dispersive frequencies for the localization the notch. This integrated characterization algorithm combined with the Excitelet imaging technique is shown to improve the accuracy of the localization of the damage for isotropic structures.
Damage Detection Index Based on Statistical Inference and PCA
This paper is focused on the development of new estimators propounding if someone statistical law could estimate or infer a system without damage knowing its reliability. This new measurement considers each experiment, and consequently, each projection to the PCA model as a random variable. An in-depth statistical analysis is performed for SHM. PCA projections are obtained from the undamaged structure (baseline projection). If these projections are considered as the set of possible results (population), then the new projections from the current structure (healthy or not) are defined as random samples. Therefore, the probability distribution of the baseline projection can be found. This new distribution can make an inference about the state of the structure and determine if there is damage in it. Consequently, the relative likelihood of each new projection is determined. If the new projection is strongly related with the population, then the structure is healthy. Otherwise, the relation indicates the damage.
Effective Damage Sensitive Feature Extraction Methods for Crack Detection Using Flaw Scattered Ultrasonic Wave Field Signal
The structural damage detection and flaw characterization are being investigated by many researchers to evaluate the integrity of a structure. The ultrasonic wave field analysis is one of the foremost nondestructive evaluation techniques in this context because of its effectiveness and applicability in a variety of materials. However, the complex and chaotic nature of raw time domain ultrasonic signals makes it very difficult for any meaningful interpretation of the unprocessed time histories. The real challenge comes in extracting the damage information after analyzing large amount of such data. The time series investigations have been conducted using STFT, WT, CWD, Stockwell Transform, HHT, Winger-Ville, MP tools etc. and are being modified to calculate the most meaningful damage sensitive index. The techniques are being developed to analyze the ultrasonic data in time-frequency (TF) domain which ensures to address these issues by focusing mainly on critical damage sensitive features present in an ultrasonic signal. In the present study, different methods are formulated, analyzed and assessed comparatively to pin-point damage sensitive attributes out of Time-Frequency representation of the ultrasonic signal. A steel channel section with several rivet holes has been considered as a physical problem to be analyzed to generate ultrasonic wave field data. The simulation has been carried out by the finite element method for two cases â€“ 1) a steel plate with cracks extending from the rivet holes and 2) an un-cracked structure. A MATLAB code has been developed for analyzing the FEM generated data.
Time-Domain Localized Structural Damage Identification with Incomplete Excitation Measurements
Though many system identification methods are currently available for system identification (SI) and damage detection, the challenge lies in the numerical difficulty in convergence when the number of unknowns is increasing. Moreover, many available methods, e.g. traditional least-squares estimation (LSE), require that the external excitation should be known for identification. However, in practice, either sensors may not be installed to measure all the external excitations or some external excitations are un-measurable. Consequently, it is highly desirable to develop SI algorithms solely utilizing response measurements and incomplete excitations. Rather than identifying the large-scale structure directly, substructural identification (SSI) method decomposes the structure into several smaller subsystems and provides an efficient way to identify the structure in sequence. In this paper, based on the idea of SSI, an approach, referred to as weighted adaptive iterative least-squares estimation with incomplete measured excitations for local damage detection (WAILSE-IME-LDD), was proposed. The substructure was firstly decomposed from the original large system, and the parameters were identified by LSE based on the response measurements of the substructure and the associated interface. The initial values of the unknown external excitations were arbitrarily assumed and the iteration process continued until the errors of the identifed forces of two adjacent iterations were within a defined tolerance. During the iteration, the estimated input vectors were updated by partially known external excitations, and the partially unknown excitations (if applied on this substructure) were identified accordingly. To improve the convergence rate and the identification accuracy, a weighted positive definite matrix and an adaptive learning coefficient were introduced during the iteration. The efficiency and accuracy of the method were validated via numerical simulation with a 10 degree-of-freedoms (DOFs) high-rise building model. Results show that the proposed approach can simultaneously identify the substructural parameters and unknown excitations with high accuracy even the responses are noise-polluted.
A Novel Damage Sensitive Feature Based on State-Space Representation
Damage detection in civil structure is a challenging task, mainly because of the strong environmental variations and the variable and unknown excitation. There is still a lack of a robust damage detection process. Taking advantage of the development of the nonlinear dynamical systems theory which represents time series in a reconstructed state-space, a novel damage sensitive feature vector is proposed. Statistical modelling using extreme value theory is conducted to classify measurement as damaged or undamaged. The whole approach is tested on two case studies. The first one is a simple 4dof mass/spring numerical model, damaged by stiffness reduction. The second one is a concrete beam subjected to temperature variations to simulate realistic conditions. Damage is introduced by loading cycles. From 30% of stiffness reduction, damage is correctly detected with a monotonic trend. In the more realistic case, only few true detections are observed before macrocracking whereas all points are well classified after. Furthermore, the method is robust against strong temperature variations.
Damage Classification in Composite Laminates: Matrix Micro-Cracking and Delamination
Fiber reinforced composites have been widely used in aerospace applications due to their functional properties, such as high strength-to-weight ratios. But many challenges remain to be overcome in order to permit more confidence in the performance of composite structures. In particular, composites have different failure types and modes that make damage prediction and propagation a very challenging subject. The main two damage types are matrix micro-cracking and delamination. Matrix micro-cracking develops first, causing delamination. The detection and quantification of matrix micro-cracks would provide the needed information to predict the development of delamination and the correct safety or maintenance decision to be made. The challenge in matrix micro-cracking identification is that it is a distributed damage, while delamination is a localized damage. The state-of-the-art diagnostic techniques are good at detecting and localizing major changes in sensor signals, which usually points to delamination, holes or other localized defects. Furthermore, there are a limited number of features that can be extracted from sensor signals, and most of them are affected by both delamination and matrix micro-cracking. The work presented in this paper aims at finding which features are more sensitive to each damage type (delamination or matrix micro-cracks), and applying machine learning techniques to learn and model a classifier that uses these features efficiently to classify the detected damage .
Identifying Scatter Targets in 2D Space Using In Situ Phased-Arrays for Guided Wave Structural Health Monitoring
Guided Wave Structural Health Monitoring, GWSHM, involves exciting high frequency mechanical waves in plate, beam, or rod-like structures and sensing the scattered response in order to detect, localize, and characterize damage. Through a process of phase-coherent delay-weight-sum similar to that used in some sonar and radar applications, time-domain scattered responses measured at several closely spaced discrete piezoelectric array elements can be transformed into a single twodimensional signal representation of amplitude (usually strain or voltage) versus distance and look direction. In this two dimensional representation, a single waveform pulse scattered from a single damage target has a predictable approximate shape which is a function of the pulse wavelength and window, and the geometric layout of the sensing array. The full response of an array, including all primary and secondary reflections (or echoes) from damage, can then be approximated by a superposition of shape functions corresponding to a finite set individual scatter targets. In this paper, following a review of the spatial domain transformation process, we describe how one can estimate the amplitude, arrival time, and bearing (arrival direction) of each discrete target through matching pursuit.
Reference-Free Damage Identification Using Statistical Modeling
This work proposes a reference-free damage identification technique based on the statistical modelling of vibration signals. This technique does not require a reference signal to identify damage, but uses the information embedded on the signal at the sensor location. The vibration signal statistical distribution is modelled using Gaussian Mixture Models (GMM) for density estimation, from which indicators such variance, skewers, kurtosis, energy and entropy are computed. Using Principal Component Analysis (PCA), the deviation from the mean value of the first and second principal components is used as indicators of damage. This approach is validated on a simulated Finite Element (FE) model of a simply supported beam, where structural damage is simulated as a reduction of local stiffness. The ability to detect damage efficiently is first investigated by modelling directly the time vibration signal. Furthermore, a frequency approach is considered, where the vibration signal is first decomposed into frequency subbands and then the estimated signal density is used in each subband to compile a space-frequency error map. Simulation results highlight the superiority of the frequency based approach over the time domain one.
Infrared Thermography and Piezoelectric Patches for Impact Damage Detection in Composite Structures
This study is motivated by the need for an efficient tool to accurately analyse an impact event on composite structures, localize the impact position and estimate its severity. The behavior of a carbon fibre reinforced polymer (CFRP) composite during low velocity impacts is analyzed and impact damage mechanisms are evaluated using both numerical prediction tools and experimental measurements. Numerical predictions are carried out using finite element models supported by progressive failure analysis tools. To perform the numerical tasks, the explicit finite element code LS-Dyna is used. Impact tests are carried out with a modified Charpy pendulum. Two experimental techniques are used to monitor the impact event: infrared thermography and bonded piezo patches. A good agreement between numerical predictions and experimental measurements, regarding the onset and the extension of the damage with increasing impact energy, is found.
An Integrated Structural Intensity Based Damage Detection Approach for Nonlinear Behaving Damage
An overview of an integrated Structural Health Monitoring approach based on Structural Intensity (SI) measurements is presented. The performances of the integrated system are evaluated by presenting numerical and experimental results concerning the different levels of detection, i.e. existence, extent and localization. Experiments are conducted on an aluminium stiffened panel, typical of many aerospace structures, where the damage is introduced in the form of loosened bolts. The characteristic nonlinear signature of this type of damage combined with SI measurements allows defining a new damage metric. This metric is able to address the different levels of detection using a single integrated approach and without requiring a quantitative baseline.
Experimentation and Detection Characters of Lamb Wave Phase Array on a Large Thin Aluminium Plate
Base on the principles of phase array of piezoelectric sensors, experimentation of lamb wave phased array in large thin aluminium plate was processed by an S0 mode Lamb wave resulted from high frequency narrow bandwidth signal. Different locations on large thin-wall structural were effectively focused through adjusting the signal transmission delay phase of elements. The concept of dead zone of phase array is further clarified and several measures to reduce the dead zone detection were given, which was favorable to improve signal-to-noise ratio of Lamb wave detection.
Damage Detection of Composite Structure Using Independent Component Analysis
This paper studies the application of independent component analysis (ICA) to structural health monitoring (SHM). The ICA technique is used to extract features from measurement sensors of a smart composite structure. To enhance information about damage, we propose a new damage detection methodology, based on the analysis of a symmetric matrix obtained from the mixing matrix. The subspaces associated to the symmetric matrix are used to define a damage index (DI). Furthermore, we propose a bound associated to this DI and decision on the state of the structure is taken. Experimentation on a composite smart structure shows the performance of the proposed approach.
Rapid Localization and Ultrasonic Imaging of Multiple Damages in Structural Panel with Piezoelectric Sensor-Actuator Network
Rapid localization of multiple damages and non-intrusive imaging of these damages can greatly help in reducing the inspection time for guided wave based NDE and in integrated SHM. A circular array of sensor-actuator network was employed for scanning a panel type structure for quantitative damage detection besides nonintrusive imaging with the help of the available reduced number of measurements and a mathematical model. This method employs Lamb waves with a narrow frequency band of excitation. What is advantageous in the proposed method is that, a circular array of sensor-actuator network with a very small physical area of coverage is sufficient to construct the virtual image of an entire panel without physically scanning using the actuators or the sensors. By employing this technique, surface breaking cracks on either inaccessible or accessible face and of size as small as 3 mm in a typical aircraft structural panel are detected with a relatively low frequency band of 100-250 kHz. The coordinates of the damages are estimated from the experimentally obtained signals using triangulation technique. Change in the wavelet coefficient with respect to a baseline signal is used to construct a quantitative relationship with damage size parameters. A damage index is then estimated by integrating the corresponding wavelet coefficient over the frequency scales of interest and over the time window of interest according to the group velocity dispersion. The magnitude of the damage index shows the severity of damage. Further correlation of these quantities with failure mechanisms and prognosis remain an open area of research.
Damage Assessment of CFRP Stiffened Panels by Electro-Mechanical Impedance Method
In this work, a portable electro-mechanical impedance, EMI, analyser is designed and developed, allowing a frequency range of 0.1-100 kHz and 10000 points per scan. Piezoelectric active patches were bonded on the surface of a stiffened CFRP plate. The optimal sensor location was determined by computer simulations using finite element analysis code ABAQUS. EMI method was used for the identification of damage on the plate, adopting a damage metrics based on the Correlation Coefficient Deviation, CCD. Damage location was varied with respect to the PZT sensor position. The damage metric is able of detecting damage on the plate. However, its localization depends upon the distance from damage point to the PZT sensor and upon the position of the PZT with respect to the Z-shape stringers. The portable and cost-effective EMI analyser is a valuable tool for damage assessment in composite components.
Optimal Sensor Fusion for Structural Health Monitoring of Aircraft Composite Components
An integrated sensor system that continuously monitors the structural integrity of an aircraftâ€™s critical composite components can have a high payoff by reducing risks, costs, inspections, and unscheduled maintenance, while increasing safety. Hybrid sensor networks combine or fuse different types of sensors. Fiber Bragg Grating (FBG) sensors can be inserted in layers of composite structures to provide local damage detection, while surface mounted Piezoelectric (PZT) sensors can provide global damage detection for the host structure under consideration. This paper describes an example of optimal sensor fusion, which combines FBG sensors and PZT sensors. Optimal sensor fusion tries to find the optimal number and location of different types of sensors such that their combined probability of detection (POD) is maximized. Optimal hybrid sensor networks can be more robust, more accurate, and/or cheaper than networks consisting only of homogenous sensors.
Impact and Damage Location Detection on Plate-Like Structures Using Timeâ€”Reversal Method
Based on time-reversal (T-R) concept, a technique for identifying both impact and damage location is developed in this paper. For the T-R method being an optimal selffocusing technique, the back-propagated wave-field which is reconstructed through the transfer functions and signals from sensors converges toward the location. Low velocity impact experiment on a flat aluminum plate with four piezoelectric sensors is performed to demonstrate the capability of T-R method for impact localization. The plate is first calibrated by transfer functions with discrete spatial spacing. A two-step search algorithm is proposed to rapidly trace the impact location. The effect of the spacing of the calibrated transfer functions on the accuracy of the detected impact location is discussed. The location of the damage is detected followed by the impact location detection technique, considering the damage as a â€œvirtual sourceâ€ when the structure is excited by the known impact source. A flat plate is employed by finite element method to generate synthetic data to verify this T-R method for locating the damage. The results show that damages with various locations and sizes can be detected successfully by exciting the force at various calibrated points. This potential of applying this technique for complex damages is also discussed. Transfer functions of the structures without damage can be used in both impact location identification and damage location detection, thus T-R method is suitable for structural health monitoring.
Fatigue Crack Detection Using Guided Waves and Probability-Based Imaging Approach
The application of ultrasonic guided waves has shown great potential for real-time monitoring of fatigue crack in metallic structures. This paper demonstrates that a probability-based imaging approach in terms of a signal feature Time of Flight (ToF) is used for estimation of presence and location of a fatigue crack in a steel plate based on guided waves generated by an active piezoelectric lead zirconate titanate (PZT) transducer network. The propagation of guided waves in a 10mm-thick steel plate is complicated due to wave dispersion and boundary reflection, which bring diverse interference to the identification of fatigue crack position. Thus, a fatigue crack model is established in virtue of finite element method (FEM) for simulating the propagation of guided waves in the presence of a fatigue crack in this structure. The characteristics of guided wave signals are extracted from the wave energy spectrum with the aid of Wavelet transform. Both the simulation and experimental results show that a fatigue crack can reflect guided waves by reason of discontinuous contact of crack surfaces under cyclic fatigue loading, and demonstrate the effectiveness of the proposed method for real-time monitoring of fatigue cracks in metallic structures.
Adaptive Fuzzy-Based Approach for Clasification of System's States
Despite the considerable development of analytical model-based methods to design fault diagnosis of systems during the last years, these methods usually need an exact model of the considered system to design appropriate fault detection systems. For diagnostic purposes additionally more information is needed for classifying and distinguishing faulty states etc. In order to avoid this problem and to develop approaches allowing distinguishing more operational states (usually those which can not be modeled easily like different operational states for condition monitoring systems etc.), qualitative model-based and also signal-based methods have been developed based on different principles. The idea of this contribution is to combine qualitative model-based methods using fuzzy logic and statistical approaches describing and using signal properties. The developed data mining technique is used to design the knowledge base as base for a new type of condition monitoring systems based on available suitable signals, related measurements, and also initial information about the classification related states/conditions of the system. The automatic extraction of a related set of distinguishable features to the states/conditions of the system is the novel keystone of this technique. The practicability as well as validation of the proposed approach is achieved by using experimental results from a test rig to study friction and wear processes of a metal surface allowing the distinction of different wear states. The developed method gives promising results to distinct related states of wear and also to determine the quality of resulting model based on a proposed quality-oriented parameter.
Image Processing Technique for Vibrothermographic Field Tests
The paper investigates the aspects of image processing in vibrothermographic measurements applied to the inspection of composite plate and carbon steel weld test specimens. A carbon epoxy prepreg plate with barely visible impact damage and carbon steel weld test specimens have been tested with use of a handheld ultrasonic excitation device. Due to varying contact pressure and misalignment between the sonotrode and the test piece the intensity of excitation is fluctuating with time. As a solution to this problem the authors propose the image processing technique based on a two dimensional Fourier transform of the infrared images. The technique allows to increase the quality and readability of the results coming from a vibrothermographic measurement with poor ultrasonic excitation
An Optimal Image-Based Method for Identification of AE Sources on Plate Structure
This study proposes an innovative method for identifying the locations of multiple simultaneous acoustic emission (AE) events in plate-like structure from the view of image processing. A synthetic aperture focusing technique (SAFT) in frequency domain for dispersive flexural wave in isotropic plate is employed to produce image displaying the locations of AE sources. Since the locations and initiation time of the AE events are unknown (namely, the length of wave signals used for SAFT is unknown), a series of images are produced by the AE wave signals with different assumed initiation times. An optimal criterion using minimum Shannon entropy is adopted to pick up the image with the locations of the AE sources and initiation time mostly approximate the actual ones. Numerical studies on an aluminum plate are performed to validate the effectiveness of the proposed optimal image-based AE source identification method.
Structural Health Monitoring System Based on Electromechanical Impedance Measurements
This paper presents a Structural Health Monitoring system utilizing measurements of the electromechanical impedance for damage assessment. The architecture and main hardware components of the system are described. The results of laboratory damage detection experiments performed for different types of mechanical structures are shown and discussed. On the basis of obtained findings remarks and guidelines for the further exploitation of the SHM system are proposed.
Damage Monitoring Based on Wave Illumination of Structures
In this communication, we present a non destructive damage (e.g. static load on the surface) detection method based on the diffraction of Lamb waves. A0 mode Lamb waves are transmitted in permanence by piezoelectric transducers into a mechanical structure such as a thin finite copper plate, to â€œilluminateâ€ the structure. We suppose that when damage is produced, the illumination propriety changes according to the position and the nature of damage. It is due to the reflection of acoustic waves occurring at the damage point. Therefore we consider damage as a diffraction source. With this consideration, we have developed a novel method for the detection of damage position. This method is based on the pattern recognition of reference diffraction signals. To test the feasibility of developed method, an experimental set-up is designed, and an absorbent object made with silicone hammer is used to provide a source of acoustic diffraction signal. Two transducers are used for transmitting the Lamb waves, and one transducer is used as wave receiver which can measure the change of illumination propriety of discussed structure. The main advantage of presented method is to generalize the different damage types by diffraction source. The experimental results show that our process can measure not only the position of the calibrated silicone hammer but also other different damage.
Design of a Self-Powered Load Monitoring System for Hot Spot Applications
A new structural health monitoring (SHM) system, which consists of a drive unit made from lead zirconatetitanate (PZT) ceramic and sensor unit made of different thicknesses PZT thin film, is proposed. For a given level of dynamic loading, the drive unit generates charges and induces voltage which will be passed to sensor unit connected to the power unit in an electrically parallel manner. Because of variable thicknesses of the sensor thin film units, each sensor unit feels different level of electric field. It is noted that any piezoelectric film subjected to cyclic electric filed induces electric fatigue phenomenon which can be seen as the relation between the remnant polarization (Pr) and number of electric cycles (N). Checking the Pr value of each daughter sensor unit, we can determine the number of mechanical loading cycles of the mechanical stress amplitude that were applied to the drive piezoelectric sensor mounted on the structure. Therefore, we can monitor the history of mechanical loading of only critical magnitudes by the proposed self-powered SHM system if we design the optimum threshold voltage values applied to daughter sensor units at and above which the electric domain switching takes place. A diagnosis tool of how to determine the numbers (N1, N2â€¦Nm) of mechanical loading with given high stress amplitudes (ï³1, ï³2, â€¦,ï³m) is also proposed.
A Robust Impact Force Determination Technique for Complex Structures
Real-time impact monitoring is widely acknowledged as important key technology within an integrated health management concept for composite airframe structures. To achieve the goal of efficient and reliable impact monitoring systems novel approaches are discussed in this contribution which allow to mitigate or to overcome stability and accuracy issues of ARX models used for real-time impact monitoring. According to theory of inverse problems and model fitting, it will be shown that these low-order ARX models are highly dependent on the signal window which has to be chosen carefully for each specific application to utilize the meaningful part of the acquired signals before the analysis. For this purpose, an optimization approach will be introduced to achieve the ARX models with the highest quality within an automated process which will be applied during the offline training step. In addition, the same approach was adopted to facilitate the selection of the most meaningful sensor for the ARX training and the best model order. As shown by the results for the analytically inverted ARX models this procedure clearly provides tremendous improvements and allows to achieve high quality ARX models by selecting the best possible inputs from acquired training data. In extension of these innovations, a novel methodology based on direct inverse identification models (DI-ARX) within a MISO framework will be presented which attacks the improvement of stability, accuracy and speed of the load identification process in a different way. The striking feature of this methodology is given by the fact that the inversion of the ARX model is already performed during the training process that no numerical inversion step, as a source of severe errors, is needed by any matrix operation etc. In such a way, further improvements were achieved even for those structures that could not be successfully handled with the traditional approach.
Analytical Formulation for the Determination of Torsional Forces and Shear Stresses in Hydraulic Steel Structures from Field Experiments
Nowadays great interest on the study of navigation steel structures has been arising. This may be the effect of catastrophic disasters that has occurred in the past due to the limited information available concerning these types of structures and the loads to which they are subjected to. This research focuses entirely in the study of miter gates structures subjected to the effects of torsional loading. A structural analysis creating a finite element model was executed to The Dalles Dam Miter Gate in Oregon after its failure. By means of this analysis a forensic study of the dam was realized for determining the causes of some major cracks and fractures in the bottom girders of the quoin block side and in the pintle. The deterioration in the extreme ends of the structure is a major issue changing its boundary conditions and causing a redistribution of forces whose components were directed to members for which that kind of loading was not considered in the design process. In order to perform an intelligent diagnosis of these types of structures an analytical formulation was developed that determines torsion forces and shear stresses in hydraulic steel structures from field experiments. Its main purpose is to provide a reliable tool for real-time monitoring of the structure and anticipate any abnormal structural behavior that may occur during its functional life. The formulation provides actual results that will avoid failure or collapse of the structure resulting in longer functional life and economical solutions for repairs and designs.
Experimental Evaluation of a Wavelet-Based FEM and its Application to Load History Identification
In the present paper, the applicability of a 2D Wavelet-based Spectral Finite Element Method (WSFEM) to Structural Health Monitoring (SHM) has been investigated from an experimental standpoint. The WSFEM resorts to the wavelet- Galerkin method to solve in-plane wave equations using finite element discretization of the space coordinates. In this research, the experimental evaluation resorts to the application of the inverse problem to load history identification. To this end, Time Reversal theory is employed, using a signal post-processing algorithm with multiresolution wavelet analysis. Results experimentally acquired at specific sensor locations are windowed, denoised, and time-reversed; the impact load is reconstructed via the numerical model as the confluence of the signals emitted from the sensors. Furthermore, the performance of the model is verified for both 1D and 2D cases, rendering a complete analysis of the 2D WSFEM. Test results show that WSFEM accurately simulates wave propagation and the reliability of results establishes its applicability to SHM.
Application of Polarization-Maintaining Fiber Bragg Grating to Optical Frequency Domain Reflectometry for Simultaneous Measurements of Strain and Temperature Distributions
We have developed a distributed strain sensing system based on optical frequency domain reflectometry (OFDR) using long-length fiber Bragg gratings (FBGs), which can measure strain distribution profiles along the FBGs with the high accuracy and the high spatial resolution. If an FBG is inscribed into a polarization-maintaining and absorption-reducing (PANDA) fiber, simultaneous strain and temperature measurement can be performed. In this paper, we applied the simultaneous measurement method to the distributed sensing system based on OFDR. We built the OFDR sensing system with the FBG inscribed in the PANDA fiber and bonded the FBG sensor part to a stainless plate. We applied bending loads as well as temperature variations in an environmental chamber. We demonstrated the capability of the simultaneous distributed strain and temperature measurement.
A System for Static and Dynamic Monitoring and Ice Sport Arena
The paper describes a monitoring system for assessing the current behavior of a major Ice Arena, covered by 78m steel trusses. The system includes two subsystems for independent assessment of static and dynamic behavior of structures. It measures the levels of strains/stresses in the cover truss elements, deflections of the cover trusses, vertical deviations of the frame columns and frequency of the public stands bearing beams. The hardware includes a main station, deformation sensors, inclinometers, accelerometers and a cable network. The deformation sensors are installed on the lower and upper belts of steel trusses, inclinometers are located on the upper portions of bearing concrete beams of public stalls. The software performs stress-strain analysis with the help of the ANSYS system and Geotek SHM monitoring system. The dynamic analysis is carried out by Artemis Extractor Pro code. Analysis of the two-year long deformations measurements has shown dependence on the environment.
Wireless, Batteryless Distributed Strain Sensing for Structural Health Monitoring
Accurate structural health monitoring and â€˜remaining useful lifeâ€™ estimation often relies upon continuous data from sensors attached to critical areas of the structure of interest. In this project, the authors demonstrated a scalable, low-cost wireless and battery-less sensing network for enabling advanced health monitoring of structures and other assets. In this phase of the effort, stand-alone strain sensors were driven and read by an autonomous WISP-based (wireless identification and sensing platform) â€œComputational RFIDâ€ node. Each WISP node is essentially an extremely low powered microprocessor coupled with on-board data acquisition powered solely by RF power harvesting. To demonstrate the sensing concept, strain data from the WISP-based strain sensors attached along a cantilever beam were transmitted through standard RFID protocols to a commercial RFID reader connected to a computer. Tests that were run included measuring the response to changes in static loads and recording temporal response to dynamic loading (an oscillating beam). The effect of distance between the sensor and the RFID antenna on the sampling rate was also explored. The technology developed here can be extended to other sensing needs for health monitoring applications. Initial efforts would include corrosion, humidity, and temperature. The authors believe that the flexibility afforded by the wireless, batteryless WISP-based sensing approach is a capability that the SHM community should consider for applications where its fundamental ease of extendibility and low/no maintenance benefits outweigh concerns related to presence of (standard) RF emissions or having only moderate (>1Hz, <100Hz) sampling rates.
Distributed Optical Fiber Sensing for Wind Blade Strain Monitoring and Defect Detection
We present results from using optical frequency domain reflectometry for high-density distributed fiber optic measurement of strain in a composite wind blade during dynamic fatigue testing. Three optical fibers were bonded to the surface of a 9-m wind blade in a grid pattern at the root, and along both the spar caps of the high- and low- pressure sides. The fiber contained distributed fiber Bragg gratings each 50-mm long spaced 50-mm apart and strain measurements were taken with 82-um spatial resolution across each grating. Within the first 10k cycles at 100% load a region of concentrated strain less than 40 mm wide was identified. This work illustrates the evolution of this region as the blade fatigued, demonstrating the potential of distributed fiber optic strain measurement for early defect detection in large-scale composite structural health monitoring.
Real-Time Micro-Explosive Damage Detection in an Unmanned Rotorcraft Vehicle Using Embedded Sensing
Demonstration of damage detection and related Health and Usage Monitoring System (HUMS) technologies for condition-based maintenance (CBM) is most convincingly done through flight testing. Demonstration of damage detection using manned aircraft may not be feasible due to airworthiness requirements which must ensure safety of the flight crew. However, demonstrations using an Unmanned Air Vehicle (UAV) provide unique opportunities to test the in-flight detection and monitoring of damage to critical aircraft components without risking a flight crew. UAV demonstrations can therefore initiate faults into primary aircraft structure while in flight to study real-time fault-sensing capability of advanced sensors. The U.S. Army Research Laboratory (ARL) is collaborating with Acellent Technologies to demonstrate the diagnostics capability of advanced sensor systems to detect embedded flaws/damage on structural components using an unmanned rotorcraft vehicle (URV). ARL developed innovative techniques to initiate controlled flaw/damage using microexplosives on a principal structural element (PSE) on the URV. The selected PSE on the URV is a side plate, shielding the engine compartment of RAPTOR 90. Two Acellent SMART Layer sensor patches were surface bonded to the damaged panel. The installed sensor systems can actuate and receive guided Lamb waves at multiple frequencies simultaneously. Data collected from the damaged PSE, compared with the baseline signals collected prior to the damage, showed change in amplitude and phase of the signals, indicating the presence of damage. Analysis of the signals by the Acellent Smart Patch software indicated a structural change within the PSE from the damage initiated by the micro-explosive. A ground-based flight test stand was developed and built to inexpensively address concerns about the safety of personnel in the area of operation of the selected URV. Preliminary tethered flight tests were then conducted as a risk reduction to planned free flight tests within the Army airspace. An autopilot was developed and control parameters were determined. The tethered flight tests showed that stable, autonomous flight could be achieved.
Comparisons of SHM Sensor Models with Empirical Test Data for Sandwich Composite Structures
This paper reports on analytical work, as well as experimental testing, that were accomplished at the Ames Research Center and at the Marshall Space Flight Center to examine acoustic wave propagating and the ability to detect intrinsic faults in sandwich type composite structures. Sandwich type composites are being studied for use in NASAs new heavy lift launch vehicle and flaw detection is crucial for safety and for failure prognostics. The work reported on in this paper involved both the theoretical modeling as well as comparison with empirical testing needed to answer the question of feasibility for reliable, and accurate, structural health monitoring (SHM) in the composite structure of interest. The analytical model of the transient wave propagation and scattering based on the Mindlin plate theory was developed. A scattered transient field properties are calculated theoretically using this model and numerically using the finite element model for acoustic waves generated by an acoustic-patch actuator. It is shown that theoretical results are in agreement with the results of numerical simulations and with experimental results.
Large Sensor Network Architectures for Monitoring Large-Scale Structures
In order to monitor large-scale structures, such as the heavy-lift launch vehicle payload shroud, propellant tanks, and aircraft fuselage, practical methods to install and connect large sensor networks are being developed. Traditional means to build such sensor networks require careful sensor placement, sensor attachment, and network wiring. Since these tasks are inherently serial and cannot easily be automated, the integration of dense sensor networks into structures is often an expensive proposition. Furthermore, large-scale structures can have numerous egress ports for umbilical attachments, power connections, fuel tank ports, and structurally complex features such as stiffeners, flanges, gaps, etc. Conventional approaches for individual sensor installation are impractical given the structureâ€™s size and geometric complexities. This paper discusses large sensor network architecture concepts and associated trade studies on the various options. All the architecture options are modular in design, i.e. they are applicable to localized areas requiring large number of sensors and scalable to large areas. Also, the architecture options consist of different components that can be considered to be on-board (permanently integrated with the vehicle structure) or off-board (detachable from the vehicle structure). Example applications and test results for composite tanks and aircraft fuselage will be presented.
Overview of CVM Technology Tests Performed by Embraer
This paper presents an overview of the Comparative Vacuum Monitoring (CVM) technology tests performed by Embraer in the scope of the companyâ€™s effort on Structural Health Monitoring. Less time-consuming and less complex maintenance procedures, facilitated damage detection in areas with restricted access, early detection of structural damages and reduction of maintenance costs are potential benefits that can be achieved by using SHM. In order to reach and make good use of those benefits, SHM technologies are being investigated at Embraer. Among them, CVM is considered one of the promising technologies for monitoring metallic material parts. Some tests with CVM technology were performed, such as having sensors installed in a Full-Scale Fatigue Test monitoring the structure periodically or installing sensors in a flight tests aircraft for on-ground periodic inspections. Those tests are focused on the investigation of the many aspects of CVM technology. Results obtained have demonstrated the viability of CVM to be applied for monitoring aircraft parts; however, aspects regarding sensors and cables durability and system qualification and readiness level still have to be addressed, depending on the application scenario.
Advanced System-Level Reliability Analysis and Prediction with Field Data Integration
As the acquisition, operating and support costs rise for mission-critical ground and air vehicles, the need for new and innovative life prediction methodologies that incorporate emerging probabilistic lifing techniques as well as advanced physics-offailure durability modeling techniques is becoming more imperative. This is because of interest in not only extending the life of current structures, but also in optimizing the design for new components and subsystems for next generation vehicles that are smaller, lighter, and more reliable with increased agility, lethality, and survivability. The component level physics-based durability models, although widely adopted and used in various applications, are often based on simplifying assumptions and their predictions may suffer from different sources of uncertainty. For instance, one source of uncertainty is the fact that the model itself is often a simplified mathematical representation of complex physical phenomena. Another source of uncertainty is that the parameters of such models should be estimated from material-level test data which itself could be unavailable, noisy or uncertain. At the system level, most modeling approaches focus on life prediction for single components and fail to account for the interdependencies that may result from interactive loading or common-cause failures among components in the system. In this paper, a hybrid approach for structural health prediction and model updating for a multi-component system is presented. This approach uses physics-offailure and reliability modeling techniques to predict the underlying degradation process and utilizes field data coming from findings of scheduled maintenance inspections (or potentially, a real-time onboard health monitoring data) as feedback to update the model and improve the predictions. The integration of field data and model updating is realized via the Bayesian updating technique. The approach is being evaluated by an OEM to a ground vehicle suspension design enhancement.
Development and Testing of an Ultrasonic Phased Array System Based on Piezo Actuators and Fiber Optic Sensors
In order to be able to monitor large areas of composite structures online, an active ultrasonic Phased Array SHM System based on Piezo-Actuators and Fiber Optic and / or Piezo Sensors was developed where approximately 8 piezo actuators and 4 fiber optic sensors are required to monitor 1 mÂ² of a composite structure. In this concept an array of piezo actuators is actuated by a series of burst signals confined in time and frequency with a defined time delay producing an ultrasonic (US) beam in a predefined direction. The beam can be swept over the area to be inspected. The beam interferes with a potential defect in the structure producing a backscattering of the US beam which will be measured by the fiber optic sensors. The captured signals will be fed in a post processing routine to visualize and quantify the damaged region. A lab based SHM system based on the mentioned technology consisting of the piezo actuators with its actuation hardware, the fiber optic sensor with its opto-electronic hardware and the control and data acquisition unit was set-up. The system was tested on several panels made of Aluminium and CFRP with different types of damages â€“ holes and impact damages - between 300 and 800 mmÂ² of overall size. All data collected were fed in a data evaluation algorithm and post processed. After first verification of the ability to detect, locate and quantify the introduced damages the system was tested on an A340 spoiler from FACC damaged by typical impact damages producing an overall delamination area of 300 to 1000 mmÂ².
Damage Detection Method for CFRP Bolted Joints Using Embedded BOCDA Optical Fiber Sensor
Mechanically fastened joints are common method of connecting structural components in aerospace structures. Bearing failure is the main failure mode at these portions of quasi-isotropic composite structures. Therefore, it is required for improving the reliability of structural health monitoring technique from the present techniques [1] to detect bearing failures including micro-damages. In this paper, micro-damages are defined as the fiber micro-buckling, matrix cracking, interlaminar delamination and out-of-plane shear cracking. The bearing damage tests were conducted to develop the damage detection method using the BOCDA optical fiber sensors. In these tests, optical fiber sensors were the hole-assisted-fiber and its diameter is 125 Î¼m. In order to understand the relationship between the BOCDA measurement results and damages, several specimens were observed by means of optical microscopy. The BOCDA can detect micro-damages by comparing the measuring results after damaged with that before damaged.
Development of Simultaneous Measurement System for Strain and Acoustic Emission Using a Fiber Bragg Grating Sensor and a Fiber Ring Laser
A simultaneous measurement system for strain and acoustic emission signals (AE signals) was developed for one fiber Bragg grating sensor (FBG sensor) using a fiber ring laser. The system consists of an erbium-doped fiber amplifier (EDFA), an optical circulator, optical couplers, photo detectors and an FBG sensor. A CFRP beam bending test was carried out to confirm the possibility of simultaneous measurement of both strain and AE signals from a single FBG sensor. In the test, signals from a conventional electric resistive strain gage and piezo-electric AE sensors were compared to those from the FBG sensor. Those were equivalent each other, and the simultaneous measurement of strain and AE signals using the newly developed system was verified.
Wireless and Batteryless Accelerometry for Aircraft Structural Health Monitoring
This paper presents the design of a self-powered impact sensor dedicated to Structural Health Monitoring for aeronautic applications. The purpose of this work is to identify and implement technological solutions that meet specific requirements for on-ground operation. A prototype featuring thermal energy harvesting, supercapacitor- based energy storage and 3D-accelerometry is demonstrated.
Flight Data from an Airworthy Structural Health Monitoring System for an Unmanned Air Vehicle Using Integrally Embedded Fiber Optic Sensors
This paper presents an airworthy, Fiber Bragg Gratings (FBG) based, Structural Health monitoring System (SHM) system for an Unmanned Aerial Vehicles (UAV). Various design issues pertaining to sensors location, embedment, integration of interrogation system instrumentation and online data recording are addressed. FBG data were processed to identify both loads and vibration modes using low pass filtering and artificial neural network algorithms. Results of an actual flight test conducted indicate that this sensor network can track the vibration and loads signature during all flight conditions, making this system a candidate for real time UAVs structural airworthy assessment.
Algorithms to Monitor Damaging Events on a Plane Blade with an Autonomous Embedded Microsystem
Monitoring of aircrafts composites structures is part of today challenge named SHM, for Structural Health Monitoring. Turboprop blade surveillance is part of it. In this context we devised a microsystem embedded on these structures in order to monitor various blade parameters such as speed, vibrations or impacts. This paper intends to show results obtained in blade monitoring data processing. These works lead to a dedicated algorithm of surveillance based on a single accelerometer.
Numerical Predictions of Elastic Wave Scattering from a Sub-Surface Defect in an F-111 Wing Skin
An effective application of stress wave based in-situ structural health monitoring methodologies requires a fundamental understanding of the interaction between a wave field and a structural defect. In the case of plate-like structural components such interactions are complicated by the dispersive nature of the stress waves and the presence of at least two wave modes at any frequency. In addition, changes in the structural geometry in the vicinity of the defect can affect the propagation of these wave modes. An ability to accurately predict the interaction of a stress wave with a structural defect therefore has significant potential benefit for the design of optimal SHM systems. The finite element method provides arguably the most versatile basis for predictive modelling of problems that involve arbitrary complexity; however simulations that cater for full piezoelectric coupling tend to be impractical for large problems. This underscores the importance of developing simplified input or forcing conditions that adequately approximate the mechanics of piezoelectric transduction. This paper examines the fidelity of two numerical approximations to piezoelectric coupling, in the context of a complex structural application involving the lower wing skin of the F-111 aircraft. Numerical predictions furnished by finite element modelling are compared to experimental observations of scattering from defects machined into a representative F-111 coupon specimen. The results show that the scheme used to approximate piezoelectric transduction has a significant influence on the predictive accuracy of the model.
Real-Time Condition Assessment of RAPTOR Telescope Systems
The RAPid Telescopes for Optical Response (RAPTOR) observatory network consists of several astronomical telescopes designed to search for astrophysical transients called gamma-ray bursts (GRBs). Although intrinsically bright, GRBs are difficult to detect due to their short durations, and as such, the RAPTOR telescopes must operate autonomously, at high duty-cycles and in peak operating condition. To facilitate more efficient planning of maintenance schedules, a recent research effort at Los Alamos National Laboratory (LANL) has focused on developing a structural health monitoring (SHM) system for these telescopes. This paper summarizes the results from this effort. The damage scenario of concern, namely damage to the telescope drive mechanism, is first presented. Next, a damage detection algorithm is developed with LANLâ€™s new publically available software package, SHMTools and the results of this process are discussed in detail. The paper then concludes with a summary of future planned refinements of the RAPTOR SHM system.
Autonomous Battery-Less Wireless Strain Gauge for Structural Health Monitoring
Strain and temperature are important measurements for structural health and integrity. High magnitude and repetitive varaitions of these two parameters may lead to fatigue or yielding in the material or even failure of the structure. Strains can be used to estimate the loads, moments, and stresses on structures, or to measure torque, pressure, and acceleration.
Mission and Scale Analysis on SHM of UAV's
Within last a few years tactical, operational and strategic UAV usages have become very common. Some UAVâ€™s mission duration may last more than 24 hours with a range of more than 1500 km. That long duration and range makes structural health monitoring (SHM) of UAVâ€™s very crucial. However, is it really necessary to monitor the structural health of every UAV? Is there any limit when considering the mission and the scale? Is damage tolerance methodology applicable to large scale UAVâ€™s? Such issues will be investigated during the study.
Monitoring the Degradation by Fire of Composite Laminates by Embedded FBG Sensors
Fire resistance is a critical requirement for some components of the aircraft structure, such as engine cowlings, meaning that the structural material must be able to contain an internal fire for at least 15 minutes, to allow the extinction system to extinguish the fire before it propagates to the structure. Composite materials degrade under fire, but the char layer is an effective low thermal conductivity protecting layer, insulating the material and delaying the degradation. Detailed mathematical models for the composite behavior are available, but to obtain accurate predictions, temperature dependent experimental parameters are requested. Only with knowledge of the internal temperature distribution a quantitative prediction can be done. Fiber optic sensors have a thickness similar to the lamina, and consequently can be embedded without disturbing the laminate. FBG sensors can withstand temperatures up to 900 Celsius for several minutes, so a detailed mapping of internal temperatures may be obtained. The paper describes the experimental setup and the obtained results on real aeronautic parts submitted to fire.
Nonlinear Ultrasonic Techniques for Nondestructive Damage Assessment in Metallic Materials
This paper presents an overview of the application of nonlinear ultrasonic (NLU) techniques to characterize materials; it has been demonstrated that NLU can provide quantitative inputs to determine the material state and measure damage in engineering components. It has recently been shown that NLU can be used to develop the framework for accurate life prediction of fatigue damaged components. These NLU measurements are done at the material level, before the formation of micro- and macro-cracks. The traditional NDE of damage of a material subject to fatigue starts from the time when a small crack initiates because there is no measurable macroscopic change in the material prior to the crack initiation. In most metallic materials, however, cracks in a measurable size appear quite late (after 80%) in the total life, while the materialâ€™s integrity in terms of toughness and strength gradually decreases due to the microplasticity (dislocations) and associated change in the materialâ€™ microstructure. Starting from mechanics fundamentals, we first develop the theoretical equations of wave motion in an elastic solid with quadratic nonlinearity. The next section considers measurement techniques for NLU, which is followed by examples of the assessment of fatigue damage in metals with NLU.
Hierarchical Sensing System Combining a Fiber-Optic Network and Distributed Built-in Capillary Sensors for Impact Damage Monitoring of CFRP Structures
In this study, the authors propose a novel hierarchical sensing concept for detecting damage in composite structures. In order to overcome the weak points of conventional fiber-optic-based monitoring, such as reparability and robustness, the proposed system stratifies the roles of â€œdamage detectionâ€ and â€œdamage signal transmissionâ€ with distributed damage sensing mechanisms and a fiber optic backbone. In order to validate the proposed concept, an impact damage detection system for large scale composite panel structures was established, utilizing comparative vacuum monitoring (CVM). It was indicated that the hierarchical system has better reparability, higher robustness, and wider monitorable area compared to existing systems. Since this system was only able to detect damage that penetrates the back surface, the authors have begun investigating a distributed device with the capability of detecting internal damage. Glass capillaries (or "hollow glass fibersâ€) embedded in the structure are considered here as a damage detection device. A concept utilizing glass capillaries is proposed, and preliminary tests were undertaken to verify the feasibility of this concept.
Waveguided and Noncontacting Thermoacoustic Sensing of Thermal Protection Systems
This paper presents the results of studies aimed at developing methods for sensing the condition of structures operating in extreme environments, such as the thermal protection system (TPS) on a space vehicle during atmospheric entry. The particularly acute challenge to sensing in these extreme conditions is that the sensor and associated electronics are not sufficiently robust to withstand the structural test conditions. Instead, it is necessary to place the sensors at a remote and more hospitable location, and then to use signal transduction methods to carry the signal from the structure to the remote sensor. An inductively coupled plasma (ICP) torch creates tests the heat shield materials of hypervelocity vehicles. Acoustic Emissions (AEs) are generated by stresses within the material, propagate as elastic waves, and can be detected with sensitive instrumentation. AE testing equipment (Physical Acoustics Corp PCI-2) and waveguides were used to monitor samples being tested in the ICP. Data were analyzed and classified using statistical pattern recognition algorithms. Results show that AE data can be used to discriminate between test conditions. The testing environment dictates the physics and chemistry of the thermal breakdown of the sample which indicates that AE testing is sensitive to those processes. This study shows the potential of AE as a powerful analysis tool for heat shield thermal degradation with the unique capability of real-time, in-situ monitoring.
Piezoelectric Wafer Active Sensor Network for Aircraft Structures Damage Localisation: Pitch-Catch Method
Mechanical flaws detection and damage severity quantification in aircraftâ€™s structures are ones among the major research axes that the aeronautic manufactures takes during theses lasts years. Our work in this field focuses on the development of a new damage diagnosis methodology based on the exploitation of specific guided wave propagation and on the capability of piezoelectric network actuators/sensors to generate/sense them. The proposed method allows a relative quick diagnosis using a smart comparison between a baseline captured before the commissioning of the plane and a damaged signal captured after N flight cycles. The major asset of this method is the capability to probe large structure within a minimum time and human interaction. This paper brings examples of feasibility on aircraft structures specimens made of composite and isotropic alloys. The feasibility of the system is therefore demonstrated using a basic sensors/actuators network.
Detecting the Point of Impact on an Anisotropic Cylindrical Surface Using Only Four Acoustic Sensors
An optimization based technique for detecting the point of impact on isotropic and anisotropic plates was developed by Kundu and his associates. Acoustic sensors attached to the plate record the arrival times of Lamb waves generated at the impact point. An objective function is then minimized to obtain the impact location [1-3]. Recently this technique has been extended to the cylindrical geometry. This optimization based technique has been tested on both flat plates and cylindrical shells made of aluminum [4]. In this paper the impact point on an anisotropic cylindrical shell geometry made of carbon fiber reinforced composite is investigated. One shortcoming of the previous method of requiring a large number of acoustic sensors to obtain the direction dependent velocity profile is also overcome here. In the new method the velocity profile in the anisotropic shell is obtained using only four sensors. Predicted points of impact on the anisotropic cylindrical shell are compared with the actual impact points. Good agreement between the two sets is observed.
Impact Damage Assessment by Sensor Signal Analysis
Aircraft that employ composites are prone to impact damage that can degrade structural performance and yet leave little visible sign. Manual inspection to detect such damage can be costly and time consuming. In this paper we investigate the use of damage detection sensors to discriminate between damaging and non-damaging impacts. In use it is likely that the impact magnitude and location will be unknown. To simulate this, a range of impact energies were performed at a varying distances from a piezoelectric acoustic sensor on composite panels. The sensor output was analysed to find distance invariant features that could be used to indicate whether an impact caused damage. In damaging impacts, a secondary signal burst, with amplitude significant when compared to the initial burst, was observed. An algorithm was produced to differentiate signals based on this feature which has the potential to contribute to a structural monitoring system and thus reduce the inspection burden ultimately leading to lower aircraft maintenance costs.
Beam Shape Sensing Using Inverse Finite Element Method: Theory and Experimental Validation
An inverse Finite Element Method (iFEM) is presented for beam and frame structures. The method is aimed at reconstructing the complete displacement field starting from in situ measurements of surface strains. A laboratory experiment is conducted on a simple cantilever beam subjected to various static loadings. Experimentally measured strains are used within a single-element iFEM model to assess the efficiency and predictive capability of the approach with respect to uncertainties and measurement errors that unavoidably affect real structures.
Integrated Optical Fibers into Aluminum Extrusions Enabling Structural Health Monitoring of Aerospace Structures
Structural Health Monitoring (SHM) enables the detection of damage via sensors that are placed within or onto the structures. SHM technologies are especially considered for the next generation aircrafts as it could reduce maintenance costs and enable significant weight savings by revolutionizing the current aircraft design approach and guaranteeing that a structure is damage-free. Constellium believes that SHM enabling aluminum parts would contribute to such improvements for metallic aerostructures and has thus produced extruded semi-products containing integrated wire-shaped sensors. Optical fibers which are particularly relevant sensors for SHM have been integrated within aluminum extrusions and tested to assess the SHM potential and the feasibility of such a solution. Fatigue crack propagation tests have then been performed, monitoring the optical signal through the optical fibers in parallel. It is demonstrated that a crack can be detected using such embedded optical fibers. Depending on the sensor type it can be used to verify the integrity of the extrusion or to provide more complex information such as the strain, or the damage position, along the extrusion's length. This could be of particular interest for aircraft areas designed in damage tolerance such as the lower wing or the upper fuselage, and enable to change the damage tolerant scenarios.
Early Results of Lamb Waves Approach to Assess Corrosion Damage Using Direct Image Path in an Aeronautical Aluminum Alloy
This paper presents an early Embraer's study of corrosion damage detection by thickness reduction effect using Lamb Waves Technology. This study is part of a set study of several SHM Technologies, like CVM (Comparative Vacuum Monitoring), EMI (Electro-Mechanical Impedance), AE (Acoustic Emission), LW (Lamb Waves). Those studies are under Embraer's R&D program. Non-destructive testing methods for rapid and reliable corrosion detection in complex metallic assemblies are an on-going challenge due to practicalities of inspection and geometric complexity. This work demonstrates the early Lamb Waves results for detecting and locating corrosion in aluminum alloys for aircraft structures. The testing were performed using Direct Image Path using Acellent Technologies Lamb Waves system. The experiments were performed using a plate with 1.6 mm thick. Artificially induced a series of thinning in the center of the test specimen. The experimental results indicate the Lamb Waves technique is high accurate and it is shown a promising application to detect corrosion damage.
Contact Pressure and Ultrasonic Damage Feature(s) in Health Monitoring of L-Shape Bolted Joints in Aerospace Structures
Though advantageous for allowing easy assembly and disassembly of a variety of structures, bolted joints often are the cause of structural failure. Checking the integrity of bolted joints after assembly is a critical but time consuming process. Recent advances in structural health monitoring (SHM) can provide techniques to automate this process. However, using SHM for the integrity check process requires relating damage feature(s) to physical quantities representing the structural integrity of bolted joints. In this paper we describe an SHM technique to monitor the integrity of bolted joints for aerospace structures. The proposed technique is based on correlating the contact pressure at the joint interface with the magnitude of ultrasonic signals passing across the bolted joint. We present a case study on L-shape bolted joint. Presented experimental observations demonstrate the ability of the proposed technique to ensure bolted joint integrity. The correlation between the contact pressure and ultrasonic signals transmitted through the bolted joint interface is demonstrated.
Application of Unscented Kalman Filters, Wavelet Packet Transforms and Feedback Control to Monitoring and Compensate Damaged Aircraft Structures
In this paper a scheme for monitoring and control of an aircraft structure is proposed based on based on nonlinear state estimation employing parametrically insensitive or sensitive unscented Kalman filters followed by the deployment of a structural controller to compensate for the damage. The measurements are obtained from accelerometers, strain measurements from fiber Bragg sensors and from a wavelet packet transform (WPT) filter of the acoustic emission. The WPT filter reveals the structure of the deterministic signal by acting a de-noising filter. By preprocessing the WPT and reconstituting the acoustic emission, all other contributions to the emission signal including the emission due to crack initiation is filtered out. The remaining signal can be considered to be purely a function of the crack propagation phase. Fiber Bragg grating sensors (FBGS) are used to locate regions of maximum strain. On detecting the damage in a region of maximum strain it is shown that it is possible to deploy a structural controller to compensate for the damage. The structural controller may be considered to be a compliance controller providing for the possibility of actively stiffening the damaged structure and also increasing the fracture toughness. However to be able implement such a controller it is required that a shape memory alloy (SMA) wires are embedded within the structure. The stiffening of the structure is facilitated by heating the wire so as to transform the wire from a martensite phase to an austenite phase.
Bond Graph Model of a Thin SHM Piezoelectric Energy Harvester
This paper presents a Bond Graph model of a SHM piezoelectric sensor used as power harvester. A FE model of the sensor bonded onto a structure subjected to low frequency mechanical vibrations has been developed. The forces applied to the sensor and measured from the FE model have been implemented in the Bond Graph model to obtain the sensor voltage response. An analytical model, providing the voltage response of the sensor subjected to an in-plane displacement field and a simplified FE model representing the sensor alone have been used to check the Bond Graph model. This Bond Graph model provides good correlation with the analytical and simplified FE models. As Bond Graph models also describe the power distribution inside a system, it has been possible with this model to estimate the power harvesting capabilities of different piezoelectric sensors under natural mechanical vibrations.
Impact Location Based on Multi-Agent Coordination and Fusion for Large Structures
In practical applications of structural health monitoring technology, a large number of distributed sensors are usually adopted to monitor the big dimension structures and different kinds of damages. The monitored structures are usually divided into different sub-structures and monitored by different sensor set. Under this situation, how to manage the different sensor set and fuse the distributed information to obtain a fast and accurate evaluation is an important problem to be addressed deeply. In the paper, multi-agent framework based impact monitoring method is presented to deal with the impact damage location problem in the large structure. The monitoring system firstly self-judges whether the impact event happens in monitored sub-region, and focuses on the impact source on the sub-region boundary to obtain the sensor network information with blackboard model. Then the service directory is used to dynamically distribute the damage location function module. Lastly a reliable assessment for the whole structure is given by fusing the sub-regionsâ€™ evaluation results. The proposed multi-agent approach is illustrated through a large aerospace aluminum plate structure experiment. The result shows that the method can automatically and effectively monitor the impact source in each sub-region, particularly near the border upon sub-region in the large-scale structure.
An Integrated Monitoring System for Damage Detection by Carbon Fibers and Optical Fibers
An integrated real-time continuous monitoring system is proposed with two types of sensors to detect damage through global and local monitoring of structures in this paper. This method combines a fast-response and easy-to-operate carbon fiber (CF) sensor and an optical fiber (OF) sensor with long-distance monitoring capacity and high spatial resolution. The distributed CF sensor monitoring system can undertake global and local monitoring, and the OF sensor monitoring system with a long sensing distance can monitor full-scale and local strain response. The measured signals of the CF and OF sensors include the strain response, the external condition response and the monitoring system noise. Towards the measuring capability in detecting low-level strain, the static measured signal of CF and OF sensor in a variable external condition is compared. Based on the relationship between sensing performance and monitoring numbers, a similar true value analysis method was developed from the measured signal, and then a wavelet transform based de-noising method was also developed. The effective high-confidence integrated monitoring system of CF and OF sensors is established and discussed along with the similar true value and the de-noised signal. Finally, this integrated system was installed on a concrete beam to determine its damage detection capability. It is found experimentally that the integrated monitoring with CF and OF sensors achieved high-confidence signals in detecting the damage location.
Advanced Approach for Multi-Site Damage Monitoring on Aircraft Fuselage Panel Using Sparse PZT Actuator/Sensor Arrays
The paper deals with an approach to automated in-situ monitoring of corrosion damage on Aluminum alloy aircraft fuselage panel. In order to monitor the panel, an array of sparsely distributed PZT actuators/sensors is used. The sensor array is designed to enclose the whole investigated area, whose health status is interrogated by means of generation and registration of ultrasonic guided waves. The status of the monitored area is visualized by a fast and robust algorithm called WEMAT. The algorithm produces an image map representing spatial distribution of a damage index using signal difference coefficients (SDC), which are calculated using correlation analysis of baseline and actual sensor response. The SDCs are further used by an advance signal processing based on Principle Component Analysis. The aim of the processing is to achieve automated and robust indication, localization and estimation of size of multiple defects, which can emerge in the monitored area. The algorithm is capable of reliable detection of very small defect located in vicinity of relatively large defect. The designed approach was tested on a fuselage panel specimen. Testing results are presented in the paper.
Anomalous Wave Propagation Imaging with Adjacent Wave Subtraction: Composite Wing Application
Application of the laser ultrasonic wave propagation imaging to field structures is challenging because the structure-wave interaction generates complex wave patterns. We developed the anomalous wave propagation imaging method with adjacent wave subtraction to alleviate this problem in our previous work. It highlights the propagation of anomalous waves related to structural discontinuities, and suppresses incident waves without the need for pre-stored reference data. Based on this method, we proposed a wing test setup for automatic NDE, and applied it to a composite wing with manufacturing defect and then to another wing underwent bending and impact tests. The results enhanced the visibility of the anomalous waves related to the damages such as stringer tip debonding, skin-spar debonding, and invisible impact damage. Based on these anomalous waves, variable time window amplitude mapping was performed to show the location, size, and shape of the damage resemble to the actual damage. The presence of structural elements such as spars, stringers, ribs, lugs, inspection windows, and integrated sensors did not adversely affect the inspection process. The proposed automatic wing NDE test setup could be expanded in a whole hanger easily for the manufacturing quality or maintenance inspection process.
Self Powered Wireless Sensor Network for Structural Bridge Health Prognosis: Achievement in the First Two Years
In this paper, recent advances achieved on the development of a new system capable of continuously monitoring the structural health of steel and concrete bridges using wireless sensors are presented. This system will be able to harvest its own power from structural vibration and wind energy and, based on the data collected and on embedded algorithms, assess and predict the health of the structure. In order to reach this objective, this five-year project includes a series of tasks that encompass a variety of developments such as developing an ultra low power AE system, energy harvester hardware and especial sensors for passive and active acoustic wave detection. Thorough studies on acoustic emission produced by corrosion on reinforced concrete and by crack propagation on steel components, and the development of models that correlate AE data with component remaining life are also part of the project activities. This project is funded by the National Institute of Standards and Technology (NIST) through its Technology Innovation Program (TIP) under grant # 70NANB9H007.
Fatigue Crack Monitoring with an Ultrasonic Sparse Array on a Real Steel Structure Component
Based on the fundamental knowledge of guided waves (GW) and structural health monitoring (SHM) a technique is presented, that monitors the structural changes at the hotspot of a running steel component fatigue test. The fatigue test is applied to a cantilever I-beam vibrating at its first natural frequency. A sparse array, consisting of four capsuled piezoelectric (PZT) sensors, is used to detect the initial flaw at a weld on the web of the beam and records the subsequent crack growth. The influence of the mechanical stress in the structure to the ultrasonic recordings is estimated. Thus the signals can be evaluated and the signal changes regarding to a flaw are useful. These changes are used to determine when and consequently where a flaw appears. The ellipse algorithm is used to image the localization and the growth of the crack.
Challenges and Strategies in Remote Sensing Implementation for Bridge Monitoring
Commercial remote sensing (CRS) technologies are ideal to help states to evaluate conditions of major bridge elements. The technology challenges regarding conventional remote sensors include the lack of high resolution and low cost techniques and the interpretation of damages identified. The educational and administrative challenges include the lack of experience of bridge engineers with remote sensing and geospatial technologies, few vendors that have invested time in â€œmarketingâ€ these technologies to the public sector, and a general lack of using remote data in bridge management software. While challenges are currently restricting the short-term commercialization of CRS for bridge monitoring, it is argued in this paper that the adoption of these technologies will be much fast-paced than other technologies. One recent informal survey taken of the AASHTO Subcommittee on Bridges and Structures members (39 states and the US Corps of Engineers responding) indicates that LiDAR technology is already being implemented and is even being used for bridge inspection. The lessons learned and applied are very important for bridge managers who may be struggling with implementation of CRS and other advanced technologies by the bridge management and preservation functions in the nations DOTs. It is envisioned that the adoption of the technology by DOTs will happen in the very near future.
An Innovative Method to Measure Bridge Deflection Using Single Telecom Fiber
The Vibrofiber sensor is a Fabry-Perot cavity formed between two broad band fiber gratings creating interference fringes. It was introduced three years ago to monitor the vibration and temperature rise of the stator end winding in a power generator. [1] This paper will discuss the use of Vibrofiber to monitor the deflection of the bridge under adverse conditions: wide temperature swings, excess load, strong winds, earth quakes, etc. The fringes in these cavity sensors have features like peaks and valleys, which are sensitive to temperature and strain. When the bridge becomes over loaded, we are interested in knowing the extent of the deflections; in addition, we might want to locate the cause of the overload. A simple Sagnac FBG interferometer has been invented to provide such diagnostics. A pair of long fiber with such cavity sensors can be installed on the underside of the target bridge segment between two supporting columns. The objective is to monitor the deflection together with any torsion in the bridge deck. Each of these 2 long fiber segments has a pair of cavity sensors, one to measure the deflection as a result of the excess strain, another to measure temperature and provide compensation for the deflection data. An array of cavity sensors with different center wavelengths will be used to support the typical multi-segment bridge structure. The interrogation unit is based on a tunable laser that can be programmed to hop to different ITU grids. A separate DFB laser will run a grating based Sagnac interferometer, measuring weight in motion, identifying the speed and the maker of vehicle in traffic, and providing deflection diagnostics. Overloaded trucks and speeding vehicles can be captured and tagged for corrective actions. The interrogation unit is equipped with wireless Ethernet communication enabling the monitoring of many bridges from a central location; similarly, warning can be initiated to alert the central traffic control ahead of any problems.
Diagnostic Performance Indication Through Field Testing of a Bridge Superstructure
Presented in this paper is the use of existing bridge load testing parameters in a new quantitative diagnostic performance indication system that is based on measured response data. Two test cases of a densely instrumented reinforced concrete deck on steel girder bridge are used to demonstrate the applicability of the approach. Each bridge field test utilized a dense deployment of a wired and/or wireless sensor system that provided real-time strain readings from full-scale load tests. Strain gauges were placed at the mid-span of the steel girders to measure neutral axis locations, transverse distribution and impact factors. Highlighted will be the results from field testing of a superstructure at the end of its service life. Controlled progressive damage of an external bearing and multiple diaphragmgirder connections were implemented to monitor the change in behavioral response. The results from the multiple tests helped to provide an inventory rating factor of the steel girder. A Performance Index (PI) was establish based solely on the measured response parameters and calibrated to load rating results. The neutral axis (NA) and distribution factor (DF) are two directly measured input parameters representing the capacity and demand of the girder similar to rating factor.
Development of Reliable and Low-Power Wireless Health Monitoring Systems for Highway Bridges
This paper provides a summary of ongoing research sponsored by the National Institute of Standards and Technology (NIST) that seeks to improve inspection practices for steel bridges by providing the technology and methodology for realtime monitoring. In order to reduce the time and cost of installing a traditional monitoring system, the research team is investigating the use of wireless communications within the sensor network. To date, the research has included the investigation of both IEEE 802.11 and IEEE 802.15.4 wireless communications, identifying the latter as more practical for bridge monitoring applications. Studies were conducted to characterize the performance of wireless communications in various bridge types. The paper also describes the development of a low-power wireless strain data acquisition device. The intended bridge monitoring requires the continuous, nonstop and reliable capture of live load data, while minimizing power consumption. An intelligent wireless sensor node that can be programmed, using LabVIEW graphical programming technology, to process and reduce the strain data in realtime has been prototyped and is being tested on a highway bridge in Austin, TX. The engineering challenges faced in trading off power consumption with performance for strain gage measurements is discussed.
Design and Application of a Wireless Sensor Network for Vibration-Based Performance Assessment of a Tied Arch Bridge
Vibration-based damage detection methodologies have rapidly matured in recent years coincident to improved sensor technologies and continued development of novel experimental approaches. While diagnostic routines leveraging baseline response measurements have been formulated and applied with success, methods without reliance on a priori knowledge of the as-built structural dynamics remain largely elusive and unproven. A steel tied arch bridge with suspected susceptibilities is to be instrumented with MEMS accelerometers at locations on the arch girder to reconstruct global and local modal response. A total of forty-eight axes of accelerometers are slated to be deployed within a single star topology wireless sensor network. To facilitate the testing of the 141m span, a custom hardware solution, tailored specifically to address the network, transmission, and power consumption requirements of the test program is designed, fabricated in-house, and documented. The hardware platform interfaces an eight channel simultaneous sampling analog-to-digital converter (ADC) with an 802.15.4 radio frequency (RF) chip transceiver, RF front end, and power management circuit at each wireless sensor node. Priority in the hardware design was assigned to data quality and noise rejection. Digital signal processing combined with a 16-bit ADC with differential inputs provides a high-resolution interface for low-noise accelerometers and offers 100dB out-of-band noise rejection. Adoption of 2nd generation low-power RF technologies, including low-noise and power amplifiers, serves to address prior range and reliability restrictions associated with wireless sensor networks. Proprietary software was developed for the design to facilitate a high-rate sampling routine, manage real-time network traffic, and employ informed power conservation strategies. The design and validation of the wireless sensor network will be documented to present the tailored approach to addressing the condition assessment needs of a site-specific application. In the structure instrumented, diaphragm openings were cut in the as-built bridge after years of service to install access hatches.
Risk Based Civil SHM and Life Cycle Management
After initial success stories structural health monitoring saw some setback due to the miss match between costumerâ€™s expectations and practical performance. These deficits are mainly attributable to the fact that monitoring and engineering expertise for structures does not go hand in hand. Monitoring shall not replace visual inspection but rather improve it. Therefore it is essential that inspectors see the benefit from monitoring and apply it. Not enough has been done to offer them services in a way they need it and where the impact is clearly visible. SHM requires international guidelines, which structure the process from the initial concept to system installation, engineering services till the periodic maintenance and update activities. The co-existence with visual inspection and traditional methods has to be demonstrated. Finally the interface to the clients and owners has to be put into the focus of our community. They are neither interested in data nor in complicated explanations. They require information on which decisions can be made. This has to be targeted and concise expertise which fits into their working process. The paper will show how a monitoring process can lead to a condition assessment which is needed to improve the life cycle assessment.
Integration of SHM into Bridge Management Systems: Case Studyâ€”Z24 Bridge
Bridge Management System (BMS) is a decision-support tool developed to assist the authorities in determining how and when to make decisions regarding maintenance, repair, and rehabilitation of structures in a systematic way. However, despite the advances in BMS modeling, the condition assessment activities still rely heavily on visual inspections, which inherently produce widely variable results. On the other hand, the goal of Structural Health Monitoring is to improve the safety and reliability of aerospace, civil, and mechanical infrastructure by detecting damage before it reaches a critical state. To achieve this goal, technology is being developed to replace qualitative visual inspection and time-based maintenance procedures with more quantifiable and automated damage assessment processes. It is the authorsâ€™ belief that for the activities related to bridge safety and maintenance should be based on visual inspections along with results from long-term monitoring. Over the last decade, the authors have realized that research in both fields has been conducted separately. Therefore, in order to develop a more reliable bridge safety and maintenance process, this paper summarizes the foundation of an approach to integrate both fields. The applicability of this approach is then demonstrated on data from the Z24 Bridge in Switzerland.
RAPID System for Hot Spot Corrosion Monitoring of Gas Pipelines
Monitoring the structural integrity of the elbow area of a gas pipeline is challenging. Utilizing SMART LayerÂ® sensing technology, a Real-time Active Pipeline Integrity Detection (RAPID) system is developed for in-situ structural integrity assessment of a pipeline. This system can evaluate and diagnose the structural integrity of a pipelineâ€™s elbow area and welding interface joints. The RAPID system is comprised of a SMART LayerÂ® sensor network permanently mounted on the structure, ScanSentry hardwareâ€”Acellentâ€™s proprietary activesensing Structural Health Monitoring (SHM) hardware, and intelligent diagnostic software operated via a portable handheld tablet computer. Acellent has performed this study with the support of ConocoPhillips. Previous research has shown that the SMART Layer sensing network technology can survive harsh environmental conditions that a pipeline undergoes throughout its operational lifetime. The RAPID system has been validated on a metallic pipeline structure in a cylindrical pipe and an elbow-shaped pipe. Damage simulation via drilling, grinding, and saw-cutting on the pipeline specimen, demonstrated the RAPID system detection functionality as effective in diagnosis of the corrosion growth in a pipeline elbow joint area.
Acoustic Emission Evaluation of Cavitation Erosion in Hydraulic Turbines
The present study represents part of a research effort having the objective to correlate cavitation with the associated hydraulic turbine erosion and associated performance degrading. The present analysis concentrates on field studies carried out in a large hydroelectric plant with the use of Acoustic Emission monitoring which is associated with turbine running parameters. Three identical Francis turbines but presenting different stages of wear have been considered in the present text. Initial analyses of the problem show that there is a clear association between acoustic emission average signals obtained during standard loading and the degree of turbine blade wear.
Structural Health Monitoring During Progressive Damage Test of S101 Bridge
For the last decades vibration based identification of damage on civil engineering structures has become an important issue for maintenance operations on transport infrastructure. Research in that field has been rapidly expanding from classic modal parameter estimation using measured excitation to modern operational monitoring. Here the difficulty is to regard to the specific environmental and operational influence to the structure under observation. In this paper, two methods accounting for statistical and/or operational uncertainties are applied to measurement data of a progressive damage test on a prestressed concrete bridge. On the base of covariance driven Stochastic Subspace Identification (SSI) an algorithm is developed to monitor and automatically compute confidence intervals of the obtained modal parameters. Furthermore, a null space based non-parametric damage detection method, utilizing a statistical c2 type test is applied to the measurement data. It can be shown that for concrete bridges the proposed methodology is able to clearly indicate the presence of structural damage, if the damage leads to a change of the structural system.
Sensing Resolution and Measurement Range of a Passive Wireless Strain Sensor
In this research, folded patch antennas are explored for the development of lowcost and wireless smart-skin sensors that monitor the strain in metallic structures. When the patch antenna is under strain/deformation, its resonance frequency varies accordingly. The variation can be easily interrogated and recorded by a wireless reader that also wirelessly delivers power for the antenna operation. The patch antenna adopts a specially selected substrate material with low dielectric constant, as well as an inexpensive off-the-shelf radiofrequency identification (RFID) chip for signal modulation. This paper reports latest tensile test results on the strain sensing limit of the prototype folded patch antenna. In particular, it is shown that the passive wireless sensor can detect small strain changes lower than 20 Î¼Îµ, and can perform well at a strain range higher than 10,000 Î¼Îµ.
Ultrasonic Wall Thickness Monitoring at High Temperatures (>500Â°C)
Corrosion and erosion shorten the life of components that are used in the petrochemical industry. In order to mitigate the safety and financial risks posed by the degradation mechanisms, plant operators monitor wall thicknesses at regular inspection intervals. In high temperature locations inspections have to be carried out at plant shut downs because conventional ultrasonic sensors cannot withstand the high operating temperatures. The authors have developed a waveguide based high temperature thickness gauge for monitoring of wall thicknesses in high temperature areas. The waveguide allows the use of conventional transduction systems (max temp. 60Â°C) at one end and guides ultrasonic waves into the high temperature region where the inspection is to be carried out. Slender stainless steel waveguides allow a temperature drop of ~500-600Â°C per 200mm length to be sustained simply by natural convection cooling. This paper describes the technical challenges that had to be overcome (dispersion and source/receiver characteristics) in order to implement this â€œacoustic cableâ€. A commercial system for wireless corrosion monitoring based on the technology is now available. Experimental results of thickness measurements on components of different thickness, furnace tests at different temperatures and accelerated corrosion tests are presented as well as data from sensors that have been installed in petrochemical plants. In addition to this it is demonstrated how trending and multiple repeat measurements allow extraction of more information from the measured data.
Early Detection of Fatigue Damage in Notched and Welded Steel Structures Using Active Thermography
This contribution presents a recently developed infrared measurement and data processing methodology that allows for early detection of localized metal fatigue damage. As an extension of the classic Thermoelastic Stress Analysis (TSA) the use of second harmonic temperature amplitudes for spatially resolved damage detection due to cyclic plasticity or clapping of crack faces in specimens made of low-alloy carbon steel is demonstrated. It is found that cyclic plastic material behavior significantly contributes to the nonlinear thermal response with respect to loading in case of mildly notched specimens. Magnitude and area size of the nonlinear temperature amplitude are correlated with the actual material damage on the micro scale. In contrast, early damaging of welded samples can be identified more easily by detection of a local drop of the elastic temperature amplitude. This is verified by making use of ultrasound excited thermography, an alternative method for crack detection. The exploitation of thermo mechanical coupling effects exhibits great potential for damage detection and quantification.
A Wavelet Based Methodology for Damage Detection and Severity Assessment on the ASCE Benchmark Structure Using Phase II Experimental Data
The American Society of Civil Engineers (ASCE) have built a scale model of a four story building and made available the acceleration data for the undamaged structure and for eight different configurations of damage which is used to assess techniques for damage detection, damage severity assessment, damage localization and identification of damage type. Data representing Ambient, Shaker and Hammer as input excitations are available. Previous publications that have used the experimental data have reported limited success in the detection and damage severity assessment. In this paper we describe a methodology that uses a combination of wavelet multi-resolution analysis, principal component analysis, the Welch spectrum estimation method and Adaptive filtering to track changes in natural frequencies. We have successfully detected, for all three input types, all of the damage configurations and completed a severity assessment. This is achieved without explicitly using the input measurements, a mathematical model of the structure or measurements from the damage cases.
Integrate On-Line RSSA and RSSI-COV Algorithms for Operational Modal Analysis of Bridge Structures
The objective of this paper is to develop on-line system parameter estimation and damage detection technique from the response measurements through using both the Stochastic Subspace identification (SSI) and Recursive Covariance-Driven Stochastic Subspace identification (RSSI-COV) approaches. To avoid time-consumption of SVD in RSSI the Extended Instrumental Variable version (EIV-PAST) is used in SSICOV. From numerical study the reliable control parameters of SSI and RSSI methods are examined. To reduce the effect of noise on the results of identification, discussion on the pre-processing of data using recursive singular spectrum analysis technique (rSSA) is also presented to remove the noise contaminant measurements, so as to enhance the stability of data analysis. Results from using both Data-drive and Covariance-driven SSI methods are discussed. Finally, through experimental study, the recursive rSSA-SSI-COV method is applied to identify the system dynamic characteristics with time-varying model parameters.
Crack Growth Monitoring System for Concrete Structures Based on Non-Contact Displacement Measurements
A convenient and reliable SHM (Structural Health Monitoring) system based on non-contact displacement measurements was proposed for applying to the real-time crack growth monitoring of concrete structures in this work. The displacement vectors of the nodes of discretized elements on digital image are measured with a CCD camera and an image processor. The maximum principal strain and the principal direction, which are calculated from the displacement vectors, are the prime parameters for crack identification. The validity of the proposed SHM system was demonstrated through the experimental results using a four-point bending specimen.
Experimental Verification of Controlled Substructure Identification Using Control Devices: A Preliminary Simulation Study
High fidelity system identification is a prerequisite for successful damage detection. In real world applications, signal noise is a major source of uncertainty and leads to poor results because many methods are unable to accommodate low signal to noise ratios. Controlled substructure identification has emerged as a technique to combat these limitations and provide accurate system identification with high levels of noise (up to 40% rms). This method works by first isolating a substructure for identification. Next, the commands to a structural control device are temporarily reconfigured with a specially designed control law that has been shown to improve identification accuracy. This process is repeated on other substructures until the entire structure is identified. Accurate identification has been demonstrated in simulation for a variety of structural control devices and building systems (Zhang & Johnson, 2011). Moreover, small scale experimental verification has taken place and simulation results were confirmed (Zhang, DeVore, & Johnson, 2010). This paper builds on the body of knowledge by documenting medium scale experimental testing undertaken at the University of Connecticut. Currently, a 12' steel structure is being fabricated and configured as a four story shear building structure. This experimental model represents a more realistic model of a civil building structure than previous work. Prior to experimental testing, numerical simulation is performed to develop performance estimates and guide testing procedure. This paper documents the numerical simulations and shows that controlled substructure identification can improve identification accuracy in substructures with poor identification accuracy.
High Frequency Axle Box Acceleration for Early Detection of Squats: Numerical Simulation, Prototype Development and Testing
Squats are a major type of rail rolling contact fatigue. The associated large dynamic force causes rapid deterioration of track structure. The cracks can lead to catastrophic rail break. It is a main cost drive for many railways worldwide. The existing automatic detection methods can only reliably find squats in the later stages. This paper discusses the detection of squat seeds by measurement and analysis of axle box acceleration (ABA). First a model is developed to numerically reproduce ABA at early squats so that their characteristic responses (signature tunes) can be determined and can be isolated from noise. Based on this a new ABA measurement system is designed and instrumented. Field testing is then performed.
A Comparison of Experimental Characterization Results for Multiple Bridge Spans of the Same Design
The efficacy of Structural Health Monitoring applications for bridges is often limited by both uncertainty related to the experimental methods used to characterize the structure and uncertainty due to the constructed nature of these systems. A global level characterization of a bridge structure serves as both a baseline for evaluating future performance and condition, and as the primary source of quantitative data used in structural identification of a structure. Bridges are usually characterized at the global level by full-scale static or dynamic testing. The uncertainty associated with full-scale static or dynamic testing methods has been discussed in numerous papers, and in most cases can be quantified or bounded through laboratory evaluation studies. The constructed nature of bridges can lead to uncertainty in their material and mechanical characteristics. Furthermore, the ultimate effect on long-term performance and condition of the various defect, deterioration and damage mechanisms that a bridge may be exposed to over its relatively long service life is difficult to quantify, particularly if the uncertainty associated with the constructed nature of a bridge has not been characterized and evaluated. The authors conducted a full-scale dynamic characterization by ambient vibration testing of two bridges that each had multiple spans of the same design. The first structure evaluated was constructed in 1987 and has ten identical, simply-supported concrete deck on steel beam spans. The second structure was constructed in 1930 and consists of three identical simply-supported Parker Pony Trusses. The bridges were selected so that the consistency of the full-scale characterization results could be compared and evaluated for both a modern and historic bridge structure. The ages of the test structures is important characteristic as construction methods and material technologies have evolved significantly over the 50+ years between the initial construction of each structure. Another important consideration in selecting these bridges was to evaluate the consistency of the characterization results for two fundamentally different structural systems. This paper describes the field testing of multiple spans of the two test structures and discusses the consistency of the characterization results.
Damage Assessment with Time Series Analysis Using Wireless Sensors
In this paper, results from an ongoing study, where acceleration data acquired with wireless sensors is used for damage assessment, are presented. A time series analysis based damage detection methodology that was previously developed by the authors and tested with wired sensors is employed. The method is based on using ARX models (Auto-Regressive models with eXogenous input) for different sensor clusters. The acceleration outputs in each sensor cluster are used as the inputs to the ARX model to predict the output of the reference channel of that sensor cluster. The difference between the fit ratios is used as damage indicating feature. Laboratory experiments using a large-scale bridge model are conducted to investigate the effectiveness of the methodology for damage detection with wireless sensors. Different global (boundary condition change by fixing different supports) and local (local stiffness loss by removing bolts) damage cases are tested. The potential and advantages of the methodology are discussed in light of the analysis results. The limitations and shortcomings of the methodology are also addressed.
An Ultrasonic Guided Wave Sensor for Gas Accumulation Detection in Nuclear Emergency Core Cooling Systems
This paper presents an ultrasonic guided wave based inspection methodology for detecting gas accumulation in the subject nuclear cooling pipe system to (1) perform in-situ measurement of the gas accumulation in order to determine if regulatory action is needed, and (2) permit verification that the subject systems are in compliance with the regulatory requirements. This approach is highlighted by a novel sensing technique using ultrasonic guided waves to perform long range long term in-situ inspection in combination with an advanced cross time-frequency analysis technique for an intelligent processing of the sensory data.
Understanding the Effects of a Breathing Crack on the Dynamic Response of Cantilever-Type Structures for Damage Detection
The presence of a crack causes local variations in the stiffness of a system and thus affects its mechanical behaviour. Considering a turbomachinery blisk as a cantilevertype structure, an investigation into the effect of the presence of a breathing crack of varying depth is carried out in this paper. This investigation provides the preliminary basis for damage detection in turbomachinery blades. A dog-bone type specimen is selected for this study. An impulsive excitation technique is used to excite the specimen model and the response is obtained at different locations. Relationships between the impulse response and crack depth/coefficient of friction are obtained. In addition, crack-face tracking is also accomplished for different modes of vibrations. The effect of crack depth and coefficient of friction on friction stresses, crack-face pressures and damping levels is investigated. The obtained results are then correlated to damage detection techniques in cantilever type structures.
Residual Life Prediction of Steel I-Beams Using Acoustic Emission and Back Propagation Neural Networks
The acoustic emission (AE) nondestructive testing method is a powerful structural health monitoring tool that has proven promising in monitoring fatigue cracking of steel structures. Back propagation neural networks (BPNNs), when trained properly, are able to predict the fatigue or residual life of the structure. This research demonstrates the use of the AE technique and BPNNs in predicting the residual lives of steel I-beams that were cyclically loaded in the laboratory. A two-channel PocketAE system was utilized to collect the acoustic data. The predictions were performed based on the AE data from the first quarter (0 - 25%), second quarter (25 - 50%) and third quarter (50 - 75%) of experimental life. The prediction results yield worst case errors of 11.4%, 10.3% and 9% respectively. The prediction based on semirandom interval of data yields worst case error of 8.9% when the network is trained on six specimens and predicts on three. This research demonstrated that BPNNs, when properly trained, are able to accurately predict the residual life of structural steel members.
Design of a Wheeled Climbing Robot for Automatic Inspection of Hydraulic Turbine Blade with Curved Surface
Hydraulic turbine blades are subject to cavitation damage on their curved surfaces induced by the passage of water through the turbine, and therefore the inspection of turbine blade surfaces becomes a key maintenance issue for the power generation industry. To automate the inspection of the blade surface, we developed a novel wheeled climbing robot with a compact visual measurement system. The robot adopts a three-wheeled mechanism and a coupled adhesion technology self-adaptive to complex curved surfaces, so that it can achieve quick motion and stable adhesion on the surface. The images of the blade surface are captured by a CCD camera and transmitted to the operation station by a wireless communication module. The wireless control of the robot, together with wireless inspection, overcomes the umbilical problem of the robot, thus avoiding additional load and expanding the working range. In order to reconstruct the 3-D profile of the cavitation, we designed a compact and low-cost sensor using multi-line structured light. Preliminary experimental results proved the feasibility of the prototype robot, and an outlook to future work concludes this article.
Experimental Investigation of the Excitation Level in System Identification of Frame Structures Using Linear Shakers
This paper presents an investigation of the relationships between excitation level and estimated dynamic properties in system identification of structures using the forced vibration technique. Investigation was experimentally performed using a frame structure and a stepper motor at the Johns Hopkins University. Random excitation technique and the Eigensystem Realization Algorithm are employed to estimate dynamic properties of the structure. Excitation level is referenced to the signal-tonoise ratio of structural response. The confidence level of the estimated properties is evaluated at each natural frequency based on the coherence function. The experimental results showed that the accuracy and confidence level of the estimated properties vary in vibration mode. In the case study of a frame structure, the confidence level of the first mode is always lower than those in the higher modes. The results also showed that the accuracy and confidence level can be improved by the increase in excitation level. In particular, significant increase in the confidence level can be achieved for the higher vibration modes even by a small increase in excitation level.
Identifying Foundation Impedance Properties from Seismic Records
According to a 1995 article published in Civil Engineering Magazine [1], more than 100,000 bridges over water in the United States have what is known as "unknown foundations." The fact that the details of the foundations and surrounding soil are not known implies that an accurate structural condition assessment of the bridges cannot be performed. Several approaches have been proposed in order to determine the needed physical parameters to complete the assessment process, although traditional methods tend to be work intensive, time consuming and costly. In this paper an approach under investigation is presented which uses existing seismic records in conjunction with system identification and model updating techniques. The goal is to determine the information needed to create a simplified but calibrated model of the structure. The proposed methodology focuses on the foundations and surrounding soil and employs the lumped-parameter model approach to account for them. A numerical example of a simplified soil-structure system which uses the proposed methodology to identify the modelâ€™s free parameters is presented. Also, a brief theoretical background of the methodology is included.
Application of Fuzzy Set Theory in Structural Health Monitoring to Pattern Different States of an RC Bridge at Interstate 40
Identifying unknown states of a structure based on the defined known states is one of the main objectives of a structural health monitoring (SHM) system to inform authorities about the current state of the structure. In this paper, we use principles of fuzzy set theory to pattern unknown states of a reinforced concrete (RC) bridge at Interstate 40. Our approach aims at establishing fuzzy sets to describe damage states in the bridge. Since different damage states in the bridge have significant overlap and vague boundaries, fuzzy sets are suitable to describe these damage states. An inductive reasoning method based on minimizing information entropy, is used to implement the above approach. Vibration signals were obtained from an SHM system installed on the bridge. A wavelet multi resolution analysis is used to extract features from signals sent wirelessly from the installed SHM system. The extracted damage features from the bridge are used to establish the healthy fuzzy set. To establish damaged fuzzy sets, a 3D finite element (FE) model of the bridge is developed. The model is calibrated based on field vibration data. The efficiency of the fuzzy pattern recognition in identifying unknown states of the bridge is validated based on the analyzed field data at different time instances and the data describing different damage severities in the finite element model. The model is tested and proved to work efficiently.
Verification of Unified Framework for Plate Structures Using Kirchhoff's Plate Theory
In this paper the Unified Framework which models structures with damages to obtain their vibration characteristics, is applied to plates. There are two inputs to the Unified Framework, the damage model and the modes and natural frequencies of the undamaged structure. The damage model is presented for a damage of arbitrary shape and size. Examples of damages for four different types of damages are presented, a point damage, a line damage, a curve shaped damage and a 2 dimensional rectangu- lar shaped damage. Although, Unified Framework is applicable to any arbitrary set of boundary conditions of an overall self adjoint system, for plates, only boundary conditions which have at least two opposite ends simply supported has been solved in literature.
Finite Element Simulation of Compensation for Temperature Influence on Lamb Wave Propagation
Structural health monitoring (SHM) is an emerging research area with multiple applications. Among SHM techniques, Lamb waves are ultrasonic elastic waves that travel inside and along thin plates and is frequently used as diagnostic tools to detect damage in plate-like structures. It has been observed that the use of a single baseline measurement suffers in the medium to long-term due to the variation of environmental conditions. A key parameter in the instability is the change in the temperature of the test structure. In this paper, a transient dynamic finite element simulation of Lamb wave for damage detection in a stiffened plate under different temperature condition is carried out on the commercial finite element code ANSYS platform Simulations are conducted over a temperature range of 25-75Â°C using 275 kHz as excitation frequencies. The changes in temperature-dependent material properties are used to measure the differences in the response signalâ€™s waveform. The baseline selection method and baseline signal stretch method are used to compensate the temperature influence on Lamb wave propagation for three different damages. The results of the numerical simulation demonstrate the effectiveness of the temperature compensation approach and the simulated damage on the stiffened plate can be defected effectively under elevated temperatures environment.
Experimental Validation of Algorithms for Wave Propagation Modeling in 2D and 3D Structures Based on the Spectral Element Method
The aim of this paper is an experimental validation of developed 2D and 3D spectral elements applied for Lamb wave modeling in thinâ€“walled isotropic and orthotropic structures. Lamb waves are generated in a plate specimen by using a piezoelectric actuator. Experimental measurements are carried out using 3D laser vibrometry. Very good agreement between numerical results and experimental measurements are observed both in terms of signals as well as in the wave field pattern. Due to the fact that both numerical calculations and laser vibrometry measurements provide information about the entire wave field. New damage index is proposed based on energy of propagating waves.
Damage Assessment Using Hyperchaotic Excitation and Nonlinear Prediction Error
The idea of damage assessment based on using a steady-state chaotic excitation and state space embedding, proposed during the recent few years, has led to the development of a computationally feasible SHM technique based on comparisons between the geometry of a baseline attractor and a test attractor at some unknown state of health. This study explores an extension to this concept, namely a hyperchaotic excitation. The feature that is used to analyze the responses of the structures to the chaotic/hyperchaotic excitations is called â€˜Nonlinear Auto- Prediction Errorâ€™ (NAPE), which is based on attractor geometry. A comparison between the results from the chaotic excitation with the results from each of the hyperchaotic excitations, obtained both numerically and experimentally, highlights the higher sensitivity of hyperchaotic excitations relative to a chaotic excitation.
Wave Propagation in Anisotropic Layered 2D Structures Using Spectral Finite Elements
The method of spectral finite elements applied to the numerical calculation of high-frequency Lamb wave propagation in thin-walled structures is presented. For this purpose, Gauss-Lobatto-Legendre points are used as interpolation points of the element shape functions formulated by Lagrangian polynomials as well as integration points for the numerical evaluation of the integrals for, e.g. stiffness and mass, matrices. The position of these points leads to a diagonalised mass matrix, which is advantageous for the time integration if an explicit time integration scheme is used. Numerical results of an undamaged and damaged anisotropic plate using a plane strain plate model are shown.
1-D and 2-D Modeling of Power and Energy Transduction of Piezoelectric Wafer Active Sensors for Structural Health Monitoring
This paper presents an investigation of power and energy transduction in piezoelectric wafer active sensors (PWAS) on isotropic structure for structural health monitoring (SHM). After a literature review of the state of the art, we developed a power and energy model for PWAS on an isotropic beam. We performed 1-D and 2-D model of the power and energy transduction for PWAS transducers attached to structure. This 1-D and 2-D model allows examination of power and energy flow for linear and circular crested wave pattern. The power and energy transduction flow chart for a complete pitch-catch setup is examined. At each stage, the electro-acoustic power and energy transduction of the PWAS transmitter and receiver are examined. The power flow converts from electrical source into piezoelectric power at the transmitter, the piezoelectric transduction converts the electrical power into the mechanical interface power at the transmitter PWAS and then into acoustic wave power travelling in the structure. The wave power arrives at the receiver PWAS and is captured at the mechanical interface between the receiver PWAS at the structure. The mechanical power captured is converted back into electrical power in the receiver PWAS and captured at the receivers electric instrument. The parametric study of PWAS size, impedance match gives the PWAS design guideline for PWAS sensing and power harvesting applications.
A Time Domain Spectral Element for Coupled Piezoelectric Actuator/Sensor with Complex Thin-Walled Assembly Structures
Characterised by geometrical flexibility, and robustness with respect to realistic conditions modelling such as non-uniform damping, the finite element method (FEM) has dominated the field of numerical simulation of wave propagation phenomena. The main challenge in wide adoption of FEM in numerical simulation of SHM systems based on GW propagation is the prohibitive computational requirements. This paper presents a structured mesh approach with nonequal number of nodes along the element edges, in order to optimize the use of an efficient variant of FEM, spectral element method (SEM) to model relatively complex thin-walled assembly structures. As low as three nodes per thickness can be used, while using a larger number of nodes in the length direction of a two dimensional structure. The presented approach does not require a modification in the element integration, thus preserving the spectral convergence rate of the method. For the modelling of the coupling between the piezoceramic element and the structure, the proposed approach implements mixed implicit/explicit time integration. The propagation of GW has been simulated using ANSYS as a representative of the FEM, compared with experimental measurements and with the results of an in-house developed code implementing the proposed optimized spectral element. The results presented as a comparison of the computational requirements and accuracy for both FEM and SEM, show a higher efficiency for the SEM for the same accuracy.
Simulation Platform for UWB Impulse Radio Wireless Sensor Networks Dedicated to Aeronautic Applications
Impulse Radio Ultra Wide Band (IR-UWB) is a promising technology to address Wireless Sensor Network (WSN) constraints such as low power consumption. Existing network simulation tools do not provide a complete WSN simulation architecture, with the IR-UWB specificities at the PHYsical (PHY) and the Medium Access Control (MAC) layers. In this paper, we propose a WSN simulator based on the IR-UWB technique and taking into account the application specificities depending on the channel propagation characteristics. The main application addressed in this paper is the Structure Health Monitoring for aircrafts. Electromagnetic simulations of the real channel propagation inside the aircraft are done and the obtained channel propagation model is introduced in the WSN simulator for a very good accuracy. This WSN simulator allows to establish the best network topology, under the constraints of an application, even for very high number of wireless sensor nodes.
Finite Element Driven Damage Detection of a Skewed Highway Bridge with Pin and Hanger Assemblies
Pin and hanger assemblies are among the traditional structural components that have been widely used in many conventional suspended plate girder bridge systems around the U.S. The failure of pin and hanger assemblies has been reported as the main reason for collapse of all or part of several bridges. This paper investigates the vulnerability of a skewed highway bridge using the pin and hanger assemblies, and evaluates the application of five different modally-based damage detection techniques in identifying the failure of a pin and hanger assembly in this specific type of bridge. A detailed high-fidelity nonlinear finite element (FE) model of a typical suspended bridge using pin and hanger system is developed to investigate the possible failure of pin and hanger assemblies. Different types of loadings were applied to identify a critical stress state in the hangers. The results show that the hangers could reach to a critical bending-torsion stress state when a combination of unsymmetrical truck loadings is added to the temperature-induced stresses. In the second part of the paper, five different vibration-based damage detection techniques were used to identify failure of pin and hanger assemblies on one of the exterior steel girders. The results of the investigation showed that the local failure of pin and hanger assemblies can partially change the global modal response of the bridge. Finally, the change in flexibility method and the change in uniform load surface method yield better damage identification results compared to the other methods.
Analysis of Bearing Damage Using a Multibody Model and a Test Rig for Validation Purposes
Intensive research, performed over the last five decades, focuses on fault diagnosis of bearings. To investigate the generation of these fault symptoms, this paper discusses the development of a multibody model of a bearing. Localized faults are introduced in the model, aiming to analyse vibration signals of damaged bearings. The paper compares different possibilities to implement these defects. Simultaneously, a test rig is built to validate the model. The rig allows applying a fully controlled multiaxial static and dynamic load on different types of bearings. Therefore, it is a powerful tool to load a bearing as built into a real machine, and measure its response.
Real-Time Characterization of Aerospace Structures Using Onboard Strain Measurement Technologies and Inverse Finite Element Method
The inverse problem of real-time reconstruction of full-field structural displacements, strains, and stresses is addressed using an inverse finite element method based on shear deformable shell finite element technology. Utilizing surface strain measurements from strain sensors mounted on load-carrying structural components, the methodology enables accurate computations of the three-dimensional displacement field for a general built-up shell structure undergoing multi-axial deformations. The strain and stress computations are then carried out at the element level using strain-displacement and constitutive relations. This high fidelity computational technology is essential for providing feedback to the actuation and control systems of the next generation of aerospace vehicles, and for assessing realtime internal loads and structural integrity.
Impact Echo Signal Interpretation Using Ensemble Empirical Mode Decomposition
One of the biggest obstacles for impact-echo application is data interpretation. Fourier transform is limited by its cumulative feature; Short Time Fourier Transform (STFT) and wavelet transform give a time-frequency analysis but at a sacrifice of resolution. Empirical mode decomposition (EMD) is an adaptive time-frequency analysis method that has been applied to interpret impact-echo data recently, but it has the mode mixing problem when surface wave intermits the signal. In this paper, an improved empirical mode decomposition (EMD) method, ensemble empirical mode decomposition (EEMD), which can effectively solve the previous problem by simply adding white noise, is applied to analyze the impact-echo data. EMD, EEMD as well as wavelet transform are applied to the numerical data of concrete deck defected by a delamination and results have shown EEMD is more promising at certain points.
Mode Conversion Estimation of Filleted T-Joint Using FEM and 3D Laser Vibrometry
T-joint configurations, commonly found in aerospace applications, provide a challenge for structural health monitoring (SHM) strategies that employ wave propagation based interrogation techniques. The challenge arises from the complexity of wave propagation through the T-joint interface, and the consequent mode conversion and reflections. This work presents a numerical characterization of undamaged T-joint using simplified two-dimensional (2D) plane strain finite element (FE) models, where excitation from a piezoelectric actuator is simulated on one side of the T-joint. The incident and consequent reflected waveforms are separated in the frequency-wavenumber domain, and spatially-integrated multiple component mode coefficients are formulated in the frequency-spatial domain with the intent to characterize wave reflections and mode conversions. Mode coefficients from the undamaged configuration are compared to T-joints with blind side notch damage located in the fillet radius. Trends from the 2D FE numerical studies are verified by a three dimensional (3D) Scanning Laser Vibrometer test setup for the undamaged case, which consists of an aluminum T-joint for selected fillet radius (0.6 cm) and stiffener thickness (0.3 cm). The setup enables 3D full wavefield surface measurements of the front and back sides of the plate, plate-stiffener radius, and stiffener. Recommendations of how to use the mode coefficient formulation as a damage quantification tool for the T-joint are given.
Detection of Impact Strain Waves in Composites by High-Speed FBG Sensor System with AWG Filter
In our previous study, an active ultrasonic propagation system has been developed using fiber Bragg grating (FBG) sensors as ultrasonic receivers for delamination detection in composite structures. This system uses an arrayed waveguide gratings (AWG) filter as a Bragg wavelength filter to detect really small strain change of ultrasonic waves. In this research, the authors extended the function of this system to detection of large strain waves caused by impact loads. The main issue in the largestrain case is that the relation between the Bragg wavelength and outputs of AWG filter is nonlinear. First, therefore, tensile tests were conducted to obtain the relations between the strain and the outputs from multiple ports of the AWG that the reflection spectra of FBG sensors passed through. From the results, the relational equations between Bragg wavelength and output ratios of the AWG were obtained. Then, an impact test was carried out to a carbon fiber reinforced plastic (CFRP) quasi-isotropic laminate on which an FBG was bonded. After that, inverse analysis was applied to the measured output ratios of multiple ports of the AWG using the relational equations obtained from the tensile tests. As a result, the impact strain wave was able to be detected with a high degree of accuracy. Furthermore, in order to confirm the applicability of this method to simultaneous multipoint measurement, three multiplexed FBGs were bonded on an acrylic plate. Since the stiffness of this plate was smaller than that of the CFRP plate, much larger strains occurred under an impact load. Hence Bragg wavelengths shifted over multiple ports of the AWG filter. However, the strain waves received in the three FBG sensors could be reconstructed precisely through the same automatic inverse analysis. The merits of this method to detect impact strain waves are as follows. First, since the ratio of multiple port outputs are used, the Bragg wavelength can be estimated independent of the variation of optical power caused by some disturbances. Secondly, this method can detect impact behaviour at really high sampling rate, because the measurement speed depends on the performance of the data recorder. Thirdly, this system can detect not only really small strain of ultrasonic waves but also large strain waves caused by impact loads.
The Application of Compressed Sensing to Detecting Damage in Structures
One of the principal challenges facing the structural health monitoring (SHM) community is taking large, heterogeneous sets of data collected from sensors, and extracting information that allows the estimation of the remaining service life of a structure. Another important challenge is to collect relevant data from a structure in a manner that is cost effective, and respects the size, weight, cost, energy consumption, and bandwidth limitations placed on the system. In this work we explore the suitability of compressed sensing to address both challenges. In this work a digital version of a compressed sensor is implemented on-board a microcontroller similar to those used in embedded SHM sensor nodes. The sensor node is tested in a surrogate SHM application requiring acceleration measurements. Currently the prototype compressed sensor is capable of collecting compressed coefficients from measurements and sending them to an off-board processor for reconstruction using L1 norm minimization. A compressed version of the matched filter known as the smashed filter, has also been implemented on-board the sensor node, and its suitability for detecting structural damage will be discussed.
Measuring the Average Thickness of a Plate Using a Bayesian Method and Free Vibration Data
In this paper a model-based approach is taken to identify certain geometric and/or material parameters for a structure. Specifically, the focus is on determining the average thickness of a thin, fully-clamped plate undergoing free vibration. The methodology is described and then implemented in an experimental setting using the measured free response of a plate. The practical SHM scenario driving this investigation is corrosion, since the extent of corrosion damage is often described in terms of the effective thickness of the plate, i.e. how much of the plateâ€™s thickness is still structurally intact. Data are gathered from three resistive strain gages, placed at arbitrary locations and orientations. Using the experimental response and a finite element model, a Bayesian approach is taken to estimate the plate thickness, h. This thickness could then be used to infer the extent of the damage, had corrosion been present. The results show that even with limited, noisy vibration data valuable information regarding the geometry and material characteristics of a plate can be successfully estimated.
This article reports on our success in applying a mathematical morphology approach, normally used in image processing, to SHM data collected from the Red River North Perimeter Bridge in Winnipeg, Canada. This data is modeled as the sum of the true structural response, together with an undesirable temperature dependent strain and a strain offset. A single reference gauge was installed on the structure with the intent of tracking and removing the latter two effects. In practice, however, that approach failed to yield satisfactorily corrected datasets. Further attempts were made to use basic envelope detection or simply high pass filtering to remove the slowly varying components of the data. Both of these methods show some promise but did not perform sufficiently well to be of practical use. In place of the previous approaches, a modified form of envelope detection was implemented that applies morphological operators to the recorded strain signal. In this study the operators opening and closing were used, which are based on the more fundamental operations of erosion and dilation. When processing SHM data, the opening and closing operations were applied in pairs: opening-closing, and closing-opening. Doing so removes the important strain event activity from the original signal leaving only the background response. It is then possible to subtract this background response from the original signal to produce a cleaned signal. This approach can be applied equally well to signals with significant background trends and to signals with no discernible trend, without the risk of corrupting the key features of the data in either case. This means that the technique can be applied indiscriminately as a general pre-processing step to clean SHM measurements before further analysis is carried out. Having such a generally applicable method is important as it simplifies the data processing by avoiding the need to perform separate, case-based, procedures on the data streams.
Examination of Wear Phenomena by Using Filtering Techniques for FDI Purposes
Fault detection and isolation (FDI) methods applied to technical systems and especially to highly complex safety-relevant or invest intensive components, machines, and plants are becoming of increasing importance. Especially wearrelated phenomena are difficulty to describe. Additionally it is also very difficult to measure related phenomena directly during the operation of components and systems. The idea detailed in this contribution deals with the development of a new methodology for online examination of wear phenomena using acoustic emission (AE) filtered and evaluated using field programmable gate array (FPGA)-based hardware.
Automated Data Interpretation for Modal Identification of a Truss Bridge
Various kinds of uncertainty involved in bridge field test data leads to a number of extraneous modes which are difficult to be separated from real structural modes, thus making automatic data interpretation be a challenge in structural identification (St-Id) area. A practical St-Id procedure consisting of multi-level data pre-processing techniques and a vector backward auto-regressive (VBAR) method is proposed in this article for automatic data interpretation. In contrast to the difficulty to manually separate structure modes from extraneous modes in most traditional modal identification methods, the VBAR method provides a determinative way to automatically distinguish them. The proposed data pre-processing strategies play a key role to mitigate uncertainty and improve data quality. Without them, the subsequent data post-processing may meet problems. Ambient test data of a cantilever beam is studied to show how the proposed St-Id procedure automatically interprets test data. St-Id of a long-span truss bridge using field test data is performed to illustrate that the proposed method is effective for real bridge identification.
Structural Health Monitoring of an Advanced Composite Aircraft Structure Using a Modal Approach
The experimental feasibility of a vibration based approach to identify damage in an advanced composite aircraft structure is presented. Analysis showed that the Modal Strain Energy Damage Index (MSE-DI) algorithm can be used to detect and localize single and multiple damage scenarios by using modal data. However, this method is less suitable to quantify the severity in terms of mechanical properties. Based on the concept of dimensional reduction it is suggested to move to a higher dimensional subset of parameters. A combination of damage sensitive features is required to enclose all levels of damage identification.
On the Application of Bayesian Analysis and Advanced Signal Processing Techniques for the Impact Monitoring of Smart Structures
Impact is a common source of in-service damage that compromises the safety and performance of engineering structures. Impact monitoring has been extensively studied by several researchers and it has been shown that damage extent can be correlated with the impact magnitude. For this reason, online impact detection systems are essential and require automatic and intelligent techniques providing a probabilistic interpretation of their diagnostics. On that account, the present study proposes an automatic approach based on Bayesian regression with Gaussian processes for impact magnitude estimation and localization. Firstly, structural dynamic responses captured by PZT transducers due to impact events are recorded from simple impact experiments. In a second step, the discrete wavelet transform and nonlinear principal component analysis are evaluated for signal filtration, feature extraction and data compression of the time histories respectively. In order to improve the impact localization, a chirplet atomic decomposition is developed and used in conjunction with a time-frequency energy distribution in order to accurately separate wave packets and extract frequency information. Additionally, the signals power spectral density and time difference of arrivals are estimated and used in conjunction with the extracted features to provide the training inputs to the Gaussian Processes. At the end, the effectiveness of proposed methodology is demonstrated experimentally.
Comparison of Damage Localization Based on Modal Filters Using Strain Measurements and Acceleration Measurements
This paper deals with the comparison of two techniques recently developed for non-model based automated damage localization using vibration measurements. The two techniques are based on modal filtering methods but differ in the sensing technologies used, i.e., acceleration or strain sensors. The advantages and drawbacks of the two techniques are illustrated with simulated data of a simply supported beam.
Multi-Source Acoustic Emission Signals Analysis Based on Blind Source Separation Using Macro Fiber Composite
In case of multiple damage sources, i.e. acoustic emission sources, signals from different damage sources are overlap each other during propagation as elastic stress wave. This article proposes a methodology to identify and separate multi-source acoustic emission signals using both Blind Source Separation (BSS) technique and Macro Fiber Composites (MFC) sensors. This methodology will be applied on plate structure, in which the acoustic emission signal propagates as Lamb wave. The strain responses under arbitrary excitations are simulated numerically. Voltage response of piezoelectric sensors is calculated analytically for the different angles of incidence of signal. Considering the simplified case, i.e. a couple of sensors and acoustic sources, the transform matrix for BSS from acoustic emission source to response of sensors is obtained with respect to different angles of incidence of signal. For identifiability of multi-source acoustic emission signals based BSS analysis, full rank of transform matrix is essential, while the transform matrix is not reversible for only few special cases. Numerical simulation for separation of multi-source acoustic emission signals is presented in this article.
Finite Element Model Based State Estimation in Mechanical and Structural Systems
This paper presents a finite element model based state estimation algorithm to reconstruct the complete dynamic response of an instrumented structure subject to unmeasured disturbances in the form of realizations of random excitations. The proposed algorithm operates on noise contaminated measurements of dynamic response, a finite element model of the system and a spectral density description of the random excitations and measurement noise. Although this problem typically falls within the category of Kalman filtering; the main contribution of the paper is that it develops an estimator with similar state error characteristics as the Kalman filter, but with the advantage that it can be directly implemented as a modified version of the finite element model of the system. The proposed observer results in a modified version of the model of the system with added dampers and applied forces which are linear combinations of the measurements applied at the sensor locations. The proposed method is successfully illustrated in a 10 degree of freedom spring-mass-dashpot structure with two noise contaminated measurements and subject to realizations of random excitations at all degrees of freedom.
Hybrid Immune Algorithm for Structural Health Monitoring Using Acceleration Data
In order to detect and identify damage of civil engineering structures precisely and efficiently, an approach for damage detection by employing hybrid immune algorithm combined with Negative Selection (NS) and Clonal Selection Algorithm (CSA) is proposed. NS and CSA play different roles in this process. The first step is to create a detector set by using normal acceleration data as input. The second step is to use negative selection algorithm to detect and localize the damage of the structure. At last, CSA will quantify the damage severity of the structure. The experimental results of an 8-story shear frame structure indicated that this hybrid immune algorithm can efficiently and precisely detect, localize and quantify damage of civil engineering structures with different damage location, extent and measurement noise.
Simulation Method of Selection of Diagnostic Parameters in the Process of Monitoring the Rail Vehicle's Conditions
The development of actions aiming towards the improvement of the travel comfort and safety, parallel to an increase of velocity in the passenger rail transport has become one of the reasons for intensification of research in the field of rail diagnostic systems. The mentioned systems are to be used in the process of monitoring the condition of individual elements of the rail infrastructure. One of these elements is the rail fleet. It was assumed that the research will focus on the state of the I and II degree of springing flexible systems in objects such as carriages or electric traction sets; additionally, the process of monitoring should allow for current quantitative evaluation of these systems. Furthermore, it was also assumed that the monitoring system should be simple and inexpensive and, for this reason, based on a small number of sensors built into selected parts of the vehicle. The subsequent assumption was to adopt acceleration as a signal registered in the process of monitoring and, consequently, used in the phase of the flexible systemsâ€™ condition assessment. The adoption of such assessment resulted from the existing requirements, concerning the tests through multi-mass discrete system, where masses are joined by non-mass flexible connectors. In general, the model of this system in non-linear. As the next step, the simulation plan was elaborated, assuming the ride on tracks with different states of maintenance and with different constant speeds. The simulation rides were carried out for an intact vehicle and for cases with damaged elements of the flexible system. The acceleration signals were registered in selected parts of the vehicle for every simulation ride. By which a rail vehicle is admitted to traffic, where acceleration is the fundamental signal measured and analyzed. In order to determine the number and placement of the sensors, and to indicate the diagnostic parameters (statistical measures) necessary in the process of evaluating the state of flexible systems, the method of computer simulation on a model of the rail vehicle â€“ track system was used. The model of this system considers the following components: track, its properties and geometry, area of contact with real profiles of the wheels and track, as well as the vehicle seen as a doing so, a set of signals was obtained, which characterized an intact vehicle, later adopted
Experimental Broadband Estimation of Guided Waves Group Velocity with High Signal to Noise Ratio
Most of the damage detection and localization approaches are currently based on the measurement of a Time-of-Flight (ToF) and the knowledge of the group velocity for a mode propagating at a given frequency. In order to extract mode-related information from a time-domain signal affected by a dispersive propagation, numerous approaches have been proposed but the group velocity must be known with precision. In order to evaluate the group velocity for dispersive frequency ranges, broadband excitation patterns must be used. This works presents a cost-effective approach to estimate the group velocity from simple measurements in a given frequency range. The principle is to generate a set of properly patterned impulse signals using a piezoceramic (PZT) and to sense the response after propagation using either a Laser Doppler Vibrometer (LDV) or another PZT. While broadband excitation using a single impulse excitation might lead to limited wave amplitude, the originality of the present approach is to use N input signals with different central angular frequencies in order to reconstruct an impulse response. The parameters of the N input signals are optimized such that the addition of all signals has a broadband frequency content in order to increase the Signal to Noise Ratio (SNR). The experimental setup consists of an thin aluminum plate instrumented with one PZT actuator and a LDV to measure the out-of-plane displacement. The influence of the number of signals N used for the reconstruction of the impulse response and the actuator / sensor distance are investigated experimentally for frequencies below 1.5 MHz. It is shown that an increase of SNR in the impulse response measurement can be obtained for the LDV sensor and thus a better agreement between theoretical and experimental predictions of group velocity can be observed even for dispersive or multimodal propagation.
Self Focusing of 2D Arrays for SHM of Plate-Like Structures Using Time Reversal Operator
Lamb waves have shown a great potential in structural health monitoring (SHM) of thin plates that are frequently used in engineering structures. Dense transducer networks or active ultrasonic arrays can be employed to generate and receive Lamb waves. Active arrays, however, enable beam steering and can work as spatial filters enabling assessment of large plate areas from a single fixed position. In this paper a novel method for selective focusing of Lamb waves is presented. The algorithm is an extension of the DORT method (French acronym for decomposition of time-reversal operator) where the continuous wavelet transform (CWT) is used for the time-frequency representation (TFR) of nonstationary signals instead of the discrete Fourier transform. An application of the proposed method to self focusing of Lamb waves in an aluminum plate is demonstrated both for a linear and a 2D star-shaped array. The 2D star-like array was designed to eliminate the effect of ambiguous mirrored images encountered for linear arrays. The results obtained with both arrays are presented and compared in the paper. It is shown that the decomposition of the time reversal operator obtained with the proposed method enabled separating point like scatters in the aluminum plate and allowed to focus Lamb waves at a desired point.
A View into Baseline Free Guided Wave Approaches for Structural Health Monitoring
Much work has been done in the field of structural health monitoring based on guided (Lamb) waves especially for aerospace applications but also others. This work can be basically split into two different concepts. The first is a concept, where a measured signal is compared to a historical baseline measured for the same or at least similar signal path and signal processing method to obtain a damage indication. The other concept makes use of instantaneous and hence time coincident data from comparable signal paths or time reversed methods instead of historical baselines. Compared to the first this latter concept is considered to be baseline free. Both concepts can be applied either experimentally or numerically, yielding damage parameters or images for the assessment of the structural health. An essential condition for the baseline free analysis is the availability of several transducers communicating among each other and allowing a statistical pattern differentiation between damaged and undamaged conditions. The paper will provide an overview and a comparison of different published approaches considered baseline free and will try to outline a concept on how baseline free monitoring might be tackled in the longer term.
Physics Based Temperature Compensation Strategy for Structural Health Monitoring
One of the widely accepted challenges in the field of structural health monitoring (SHM) using ultrasonic guided waves is to carry an accurate damage diagnosis even in the presence of changing environmental conditions. The present paper investigates the role of ambient temperature in causing changes to the structural wave propagation in a newer perspective and presents a novel methodology to compensate its effect. The changes in the sensor signal parameters, caused by the variation in ambient temperature, are related to the changes in the physical properties of the system through a linear system identification model. A very limited data set is used to train the inputoutput model which has the capability to generate a large baseline space of sensor signals underlying its practical efficacy and usefulness.
Load-Enhanced Imaging of Fatigue Cracks Via Sparse Guided Wave Arrays
Detection and localization of fatigue cracks originating from fastener holes is an important application of proposed systems for structural health monitoring (SHM). However, detection of even large fatigue cracks using ultrasonic guided waves can be challenging when cracks are tightly closed, which is common in the absence of applied tensile loads. It can also be problematic to detect fatigue cracks using baseline comparison methods if the baseline data are not recorded under the same environmental and operational conditions as the current signals of interest. Work presented here considers guided wave signals recorded from a spatially distributed array of PZT discs bonded to an aluminum plate. A hole was drilled in the center of the plate to simulate a fastener hole, and cracks were grown via low cycle tensiontension fatigue. At intervals during the fatigue test, signals were recorded as a function of static tensile load from all transmit-receive transducer pairs. Data were first analyzed by comparing current signals to baselines recorded from the undamaged specimen at different loads. Results indicate that load mismatch can significantly degrade images, and cracks may be invisible if loads are not applied. Data were next analyzed by comparing signals at one load to those at another load at the same damage state, and results show that cracks can be effectively detected and localized without using baseline data from the undamaged state. This load-dependent but baseline-free approach could thus enable robust monitoring of fatigue cracks in the presence of varying loads.
Effect of Water Temperature on the Laser-Based Ultrasonic Testing of Immersed Structures
Laser-generated ultrasonic guided and bulk waves are increasingly considered for the nondestructive testing (NDT) and structural health monitoring of engineering systems. Methods based on the use of pulsed laser or continuum laser are ideal when a noncontact approach for the generation of stress waves is desired. This paper presents the initial progresses of an ongoing study where a pulsed laser is used to generate stress waves in underwater structures. In particular, in this paper we show the results of one experiment that investigates the effect of water temperature on the ultrasonic energy propagating through one immersed test specimen. We first studied the effect of water temperature on the amplitude of the laser-generated waves. Then, we conducted a cross-correlation analysis on the waveforms to assess their similarity. Finally, we performed a frequency analysis to investigate the frequency content of the laser-generated bulk waves.
Mystery Revealed on Natural Frequency Change of a Structure During Rainstorms
Recent observations as well as previous research show a 2-3% increase in the natural frequencies of Caltechâ€™s Millikan Library, a nine-story reinforced concrete frame and shear wall building, during rainstorms. It has been a mystery about whether changes in the building structure or the soil underneath cause the phenomenon. The Southern California Seismic Network (SCSN) installed a 24-bit 3-axis rotational sensor in the basement of the Millikan Library in 2008. It acts as an excellent data source to examine the mode shape changes that accompany frequency changes of the building. During the rainstorm period in late 2010, the authors ran several shaking tests of the building at its natural frequencies, and the ratio of the roof translational response to the basement rotational response was used to reveal the mystery. Experimental results suggest that the building concrete swells in response to moisture and cracks on the building surface are forced to close. The corresponding increase in the Youngâ€™s modulus of the building structure causes an increase in the measured natural frequencies. Furthermore, when the authors watered the ground adjacent to the Millikan Library, no changes in the buildingâ€™s natural frequencies were observed. The irrelevance of â€œsoil saturationâ€ supports the suggested hypothesis. Finally, a 1- dimensional Timoshenko Beam model with soil-structure interaction is used to verify the proposed explanation for the mystery.
Influence of Environment Condition on the Group Velocity of the Lamb Wave for SHM System
We have been developing a Structural Health Monitoring (SHM) system. One of the monitoring targets of the system is the debonding in the bond-line of Carbon Fiber Reinforced Plastic (CFRP) adhesive structures. In the SHM system, Fiber Bragg Grating (FBG) optical fiber sensors are used to detect Lamb waves and piezoelectric (PZT) transducers are used as actuators to generate Lamb waves. When debonding occurs in the bond-line of CFRP adhesive structures, the transmission route length of the Lamb waves increases, and the time taken for the Lamb wave to reach the FBG sensors increases. The SHM system measures the Lamb waves and calculates the debonding length from the increase of the transmission time. Therefore, in the case of debonding monitoring, the precise group velocity of a specific Lamb wave mode is required to achieve an accurate evaluation ofthe debonding length.However, it is well known that the group velocities of the Lamb waves are affected by environmental conditions such as temperature and strain. Thus, it is necessary to investigate the influence of strain and temperature on the velocity of the A0 mode in the Lamb waves and to develop a technique to compensate the influences of environmental conditions. In this study, we investigated the influences of temperature and strain on Lamb waves. Moreover, we developed prototype integrated tape-type FBG sensors to measure ambient temperature, and we evaluated the temperature detection performance of the sensor.
Measurement of Distributed Strain and Deformation and Load Identification Using Optical Fiber Strain Sensors
We have implemented strain measurements along three sensing lines of long-length fiber Bragg grating (FBG) sensors in a wing model. The sensing system based on optical frequency domain reflectometry (OFDR) can measure strain at an arbitrary position along long-length FBG sensors with the high spatial resolution. We estimated displacement from the measured strain data by applying the beam theory. In addition, in order to investigate the applicability of the load identification method based on the inverse analysis, we applied it to a simply supported beam. In this experiment, the strain distribution along the beam was measured by the long-length FBG and the displacement distribution was also estimated from the measured strain data. Then the applied load distribution was identified by the inverse analysis using the strain or the displacement data.
Extension of the Generalized Unknown Input Kalman Filter for Online-Reconstruction of External Structural Loads
External load information is of great interest in structural health monitoring (SHM), since it can help to evaluate possible damage of a structure due to fatigue loading or after extreme events. However, some loads might not be measured directly and have to be reconstructed from structural response measurements. This is a type of ill-posed inverse problem where small perturbation of the measurements may cause unstable solutions. Therefore, a robust load reconstruction strategy is needed. In this paper, an extension of the generalized Kalman filter with unknown inputs method, G-KF-UKI (Generalized Kalman Filter with Unknown and Known Inputs), is proposed. This method can realize online input force estimation and is robust to modeling errors and measurement noise. Besides this, the presented G-KF-UKI strategy also includes known inputs (e.g. control inputs or known force inputs), which makes it applicable to a larger class of systems. An experiment on a laboratory twostorey structure and a simulation study on wind load reconstruction are given as examples to show the effectiveness of this method.
Characterization of the Temperature, Load and Damage Effects Using Piezoelectric Transducer Patches Based on Fuzzy Clustering
Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in a structure. One of the critical challenges for practical implementation of SHM system is the ability to detect damage under changing environmental conditions. This paper aims to characterize the temperature, load and damage effects in the sensor measurements obtained with piezoelectric transducer (PZT) patches. Data sets are collected on thin aluminum specimens under different environmental conditions and artificially induced damage states. The fuzzy clustering algorithm is used to organize the sensor measurements into a set of clusters, which can attribute the variation in sensor data due to temperature, load or any induced damage.
An Efficient Temperature Compensation Technique for Guided Wave Ultrasonic Inspection
One challenge in the development of structural health monitoring technology is the necessity to distinguish benign effects from those caused by damage. For ultrasonic guided waves systems, this is a problem of particular importance. Guided waves create complex, multi-modal, and dispersive wave fields which reflect off specimen boundaries as well as damage. Direct timedomain comparisons with a known baseline can be used to overcome these complexities, but fail to discriminate damage from benign environmental effects. Although many environmental changes affect guided waves, variations in temperature are often the most dominant. This paper proposes a computationally efficient temperature compensation technique based on the scale-invariant correlation coefficient. Using experimental measurements, we compare the performance of the scale-invariant correlation coefficient with two other compensation strategies: the local peak coherence and optimal signal stretch methods. We demonstrate the scale-invariant correlation coefficient to be robust, effective, and computational efficient.
Machine Learning for Pipeline Monitoring under Environmental and Operational Variations
We study structural health monitoring ultrasonics experimentally, using piezoelectric transducers affixed to a steel pipe. In this paper, we apply machine learning algorithms to detect and localize changes produced by damage while differentiating from changes produced by ambient environmental and operational variations. Damage was simulated physically by a mass scatterer grease-coupled to the surface of the pipe, and benign variations were simulated by varying the internal pressure of the pipe and the ambient temperature over time. We create a library of 335 features extracted from ultrasonic signals by utilizing a variety of signal processing and machine learning techniques. Adaptive boosting algorithm is employed to select the most significant features out of the feature library. The selected features are then fed to support vector machines to determine the presence and the location of the damage. The results show that the machine learning scheme is effective at identifying principal features like shift-invariant correlation coefficients, wavelet coefficients and curve length, and provides an average accuracy of 95% for damage detection and 93% for damage localization.
Prognostic Modeling and Experimental Techniques for Electrolytic Capacitor Health Monitoring
Electrolytic capacitors are used in several applications ranging from power supplies on safety critical avionics equipment to power drivers for electromechanical actuators, and this makes them good candidates for prognostics and health management research. Prognostics provides a way to assess remaining useful life of components or systems based on their current state of health and their anticipated future use and operational conditions. Past experiences show that capacitors tend to degrade and fail faster under high electrical and thermal stress conditions that they are often subjected to during operations. In this paper, we study the effects of accelerated ageing due to thermal stress on a set of capacitors. Our focus is on deriving first principles degradation models for thermal stress conditions. Data collected from simultaneous experiments are used to validate the desired models. Our overall goal is to derive accurate models of capacitor degradation, and use them to predict performance changes in DC-DC converters.
Improving the Accuracy of Structural Fatigue Life Tracking Through Dynamic Strain Sensor Calibration
The ability to accurately determine the amount of structural life that has been consumed in military aircraft can be compromised by the inability to be consistent in the manufacture and installation of strain sensors and general aircraft-to-aircraft variations in the structures themselves. The variations must be accounted for in order to be able to make correct decisions - regarding the ability to safely operate the aircraft as well as reducing the need to purchase new aircraft (resulting from retiring of aircraft with remaining useful life) - which are based on fatigue life calculations. Accurate strain gauge calibration is thus necessary to ensure accurate aircraft fatigue usage estimates. However, the methods that are currently used for strain gauge calibration are costly, time consuming, or inaccurate. To address these issues, the authors are developing an innovative strain sensor calibration system that uses a portable device to 1) apply a low level and localized dynamic load near the strain gauge, 2) record the input load and structural response measured by the strain gauge, 3) evaluate the measurements relative to a reference structure, and 4) provide a calibration factor for each individual strain sensor/structure. This paper presents an overview of the approach and describes experimental results for both baseline (static) and dynamic excitation tests. The accuracy goal of 1% has been set for the calculated calibration factors on simpler structures and 2% on trial parts of increasing complexity. Tests were thus conducted to verify test repeatability and evaluate calibration accuracy in these scenarios.
A 9-Step Process for Developing a Structural Health Monitoring System
"The portion of the structural health-monitoring process that has received the least attention in the technical literature is the development of statistical models to enhance the SHM (structural health monitoring) process", according to a book-length literature review (Sohn et al. 2004, p. 157). This article will help fill this gap by extensions to general SHM applications of the statistical advances made for the SHMs for emissions controls, mandated on all new cars and trucks sold in the developed world and in many developing countries. In the 1990s tightening legal mandates for "on-board diagnostics (OBDs)" pushed the Low Emissions Partnership of Chrysler, Ford and General Motors to fund research to (a) improve the statistical sophistication of their OBD work, and (b) help them negotiate with regulators. A summary of this research was embedded in the "8-step process for OBDs" described by Box et al. (2000). This paper will compare a 9-step extension of this Box et al. (2000) process with the 4-part SHM process of Ferrar et al. (2001), used by Sohn et al. (2004) to structure their literature review; see Table 1. There are similarities between the monitoring processes of Table 1 and the 6-step Structural Identification process of Catbas, Moon, and Aktan (2010), but the purposes can be different. Structural identification is often but not always conducted as part of monitor design, and monitors (i.e., monitoring systems) can be designed without a formal structural identification effort. Further comparison of structural identification and monitor design will not be attempted here.
Combined and I Indices Based on Principal Component Analysis for Damage Detection and Localization
In this paper, two indices (combined or phi index and I index), different to the presented in [1][2][3] are used to detect damages; these indices are calculated from the information obtained from the projection of the experiments into the PCA models (baseline). They give us a measurement about the difference between the tested and the healthy structure. The experiments are taken from an active piezoelectric system which is excited with lamb waves in different phases and the fact that any defect in the structure changes its vibrational response is exploited. For localization, five different methods of contribution analysis are used (complete decomposition contribution, partial decomposition contribution, angle based contribution, reconstruction based contribution and diagonal contribution). With these methods, the contribution of each sensor to each index is analyzed, in this way, sensor with largest contribution suggests the path where the damage could be located (from the actuator to this sensor). The combination of all indices and all contributions (a total of 2 x 5) are analyzed and compared. To validate the approaches, they are applied to an aircraft turbine blade instrumented with seven PZTâ€™s. Different damages are simulated.
An Experimental and Numerical Investigation of Damage Detection in a Mistuned Bladed Disc
Mistuning in repeating structures like bladed discs is caused by small variations in the individual blade properties that, results in the splitting of degenerate vibration modes and affects the dynamic behaviour of the system. As a result, it is complicated to highlight a small damage in the mistuned environment. This paper is focussed on the effect of mistuning on the dynamic characteristics of the bladed disc. An experimental rig is setup and a bladed disc having eight blades, rigidly attached to the base to represent a blisk, is selected for this study. The splitting of resonance frequency peaks in an FRF obtained for the mistuned structure is analysed experimentally and numerically. A very basic level of mistuning in any repeating structure usually comes from the manufacturing tolerance, so the effect of manufacturing tolerance-induced mistuning is also investigated in the paper. The possibility of utilising the Modal Assurance Criterion (MAC) for developing a damage detection strategy in mistuned bladed discs is also examined. Experimental and numerical results for the splitting of FRF peaks are then compared. Outlier detection analysis is utilised for detecting damage in the frequency domain.
Fatigue Evaluation and Prognosis for Steel Bridges with Remote Acoustic Emission Monitoring
Remote acoustic emission (AE) monitoring is desirable for fatigue damage evaluation and life prediction for in-service steel bridges. Understanding the mechanism of AE signals corresponding to the fracture events in the material of interest is the basis of AE monitoring applications. Conventional fatigue tests along with AE monitoring were performed for correlating AE signals with crack growth behavior. Signal identification approaches based on load pattern and waveform features were employed in data filtering and reduction procedures. AE parameters from the filtered dataset were associated with corresponding crack growth parameters for damage evaluation. It has been indicated that AE parameters can robustly identify fatigue damage level. The parameters in terms of signal energy are suitable for fatigue life prediction.
Impact Damage Characterisation Using a Statistical Approach
Many of the materials utilised in current technologies, especially those used in the aerospace industry, require an unusual combination of properties that cannot be met by conventional metallic, ceramic or polymeric materials alone. Therefore, aerospace structural engineers are constantly searching for alternative materials, such as composites. Composite materials consist of two or more constituents with varying properties, that when used together, form a new material. These can be tailored to have low densities, high strength and stiffness, and have good corrosion resistance. These materials improve structural efficiency, and can reduce the structural mass without compromising structural stiffness and strength. The ultimate objective of the research work, described in this paper, was to conduct an experimental investigation to detect and quantify impact damage in structures made from composite plates. Two different approaches were used to record acceleration response signals resulting from impact excitation. The first used a standard impulse hammer in order to acquire time data and produce spectra for a number of non-damaging impacts. The second approach used a drop-test to perform a number of potentially damaging impacts. The impact energies for the drop tests ranged from 0.37 J to 41.72 J. Following a systematic series of experiments on the induction of impact damage in composite specimens, two different techniques were used to examine the impacted samples. X-ray radiography was used to evaluate the damage area whilst Scanning Electron Microscopy (SEM) was used to inspect the topographies of the specimens at high magnifications. The motivation behind this research work was based on the idea of using statistical or machine-learning methods to identify and categorise impacts (damaging or non-damaging and also types of failure modes) using only structural response data. The discussion here will be focused on outlier analysis on higher-dimensional multivariate data, the features are from binned spectra which leads to an 8-dimensional feature.
Accelerated Aging Experiments for Prognostics of Damage Growth in Composite Materials
Composite structures are gaining importance for use in the aerospace industry. Compared to metallic structures their behavior is less well understood. This lack of understanding may pose constraints on their use. One possible way to deal with some of the risks associated with potential failure is to perform in-situ monitoring to detect precursors of failures. Prognostic algorithms can be used to predict impending failures. They require large amounts of training data to build and tune damage model for making useful predictions. One of the key aspects is to get confirmatory feedback from data as damage progresses. These kinds of data are rarely available from actual systems. The next possible resource to collect such data is an accelerated aging platform. To that end this paper describes a fatigue cycling experiment with the goal to stress carbon-carbon composite coupons with various layups. Piezoelectric disc sensors were used to periodically interrogate the system. Analysis showed distinct differences in the signatures of growing failures between data collected at conditions. Periodic X-radiographs were taken to assess the damage ground truth. Results after signal processing showed clear trends of damage growth that were correlated to damage assessed from the X-ray images.
Prognostics and Diagnostics of Rotorcraft Bearings
This paper presents a diagnostic and prognostic approach for rotorcraft bearing health monitoring using the Hilbert-Huang Transform (HHT). The HHT transforms a raw vibration data into in a two-dimensional time-frequency domain by extracting instantaneous frequency components within the signal through an empirical mode decomposition EMD process. EMD transforms the complex vibration signal into simple oscillatory modes called intrinsic mode functions (IMFs). Since the IMFs are obtained based on the local characteristic time scale of the data, they can be used to analyze the nonlinear and nonstationary bearing degradation processes. In performing diagnostic decisions, the work presented here uses the energy ratios of the highest two intrinsic modes and the respective marginal frequencies as condition indicative features. The approach has been tested using experimental data obtained from seeded spall and corrosion tests on AH-64 Apache hanger bearings.
Bayesian Sensitivity Analysis of Numerical Models for Structural Health Monitoring
The scarcity of damaged-state data is an abiding problem in practical applications of structural health monitoring. Given this scarcity, it is perhaps unsurprising that many of the techniques proposed for the SHM make use of physics-based modelling in order to â€˜fill in the blanks'. The aim of developing the model is often, but not exclusively, to act as the basis for a model-update type SHM strategy. However, it is possible to get more out of a developed numerical model. By probing the physical interactions encapsulated in the model a comprehensive picture of the relationships between inputs and outputs can be constructed. In this paper, a global sensitivity analysis approach is demonstrated for this purpose. The techniques applied reflect progress in the field of analysis of complex computational models, and make use of both code emulation and Bayesian statistical methods.
Adaptive Classification Based on Multisensor Decision
This paper investigates the use of multisensor data fusion principle to design an object detection system based on Support Vector Machine (SVM) for monitoring and supervision of complex production processes. The goal is to state the existence of undesired objects in the production process. The monitoring system includes acceleration sensors used as sensor-cluster. A Short Time Fourier Transform (STFT) is used as prefilter in order to extract relevant features of the acceleration signals. The extracted features of the individual sensors undergone multistage filtration process including a preliminary SVM filter, fuzzy filters, a rule-based filter, and double stage local SVM filters. This process aims to avoid misclassification of system states as well as to realize a reliable decision about the presence of undesired objects. The decisions of the individual stages are interpreted and fused in the final decision module which is responsible for the practical realization of the decision whether undesired objects are present.
Artificial Neural Network Based Damage Detection from Lamb Wave Response
Lamb waves in plate-like structures have been known for their excellent propagation capability and sensitivity to structural damage. ANNs are well-known to be a versatile technique of pattern recognition. Use of ANNs to detect patterns in timedomain Lamb-wave response waveforms in metal sheets has been explored as a damage identification method which could be highly suitable for Structural Health Monitoring of aircraft. Experiments were conducted on Aluminium sheets having either none, or one of three different types of damage (dent, notch, erosion), using piezoelectric actuators and sensors to excite lamb-waves and detect responses. A comprehensive set of data was accumulated, and, after de-noising and re-sampling, used to train and test ANNs for the ability to detect the existence and type of damage. Out-of-sample data were used for validation of trained and tested networks. Multiple network-architectures and data-processing techniques were considered. Trained networks were found to be remarkably successful in detection of damage (90-95% detection rate), but only moderately so in identification (accurately classifying about 70-75% cases). The robustness of the ANN method is evident considering the high variability that was observed in the experimental data used for training. Changes in network configuration were not found to produce appreciable change in results.
Integration of Data Mining Operations for Structural Health Monitoring
Data Integration is a well elaborated scienti c area and one of the most important use cases of the Semantic Web. Techniques developed in this eld aim at providing interoperability between heterogeneous data sources. Com- pared to typical Semantic Web use cases, data integration issues are manifold and also a ect applications through their underlying schemas. Civil engi- neers specialized in risk and measurement analysis need a reliable Decision Support System (DSS) that integrates various required techniques. Hence, Structural Health Monitoring (SHM) applications tend to adopt typical inte- gration concepts, but not by regarding data and their semantics independent from the application domain. Instead, such a DSS should be accessible in an integrated manner to support the usage of methods and techniques from di erent systems according to their intended operational purpose. This paper presents some practical examples of using Data Mining operations which en- able a better understanding of the analysed data and which can be successfully integrated into a uni ed DSS for SHM.
Cognitive Architectures for Real-Time ISHM
In the real-time battlefield arena, situational awareness becomes critical to making the right decisions and achieving the overall goals for the system. The key to Situational Awareness is not simply collecting and disseminating data, but it is actually getting the right information to the right users at the right time. In ground processing systems, various sensors, spacecraft, and other data sources gather and generate data different relevant contexts. What is required is an Integrated System Health Management (ISHM) processing architecture that allows users to turn the data into meaningful information, and to reason about that information in a context relative to the user at that time, and to update the information real-time as the situation changes. In short, it is imperative that the information processing environment be efficient, timely, and accurate. Described will be an Intelligent Information Agent processing environment which allows data to be processed into relevant, actionable knowledge. Based on the technologies described above, situational management is one of the most innovative components of this processing system. Utilizing the Artificial Cognitive Neural Framework (ACNF) (Crowder, 2005), it can provide real-time processing and display of dynamic, situational awareness information.
Integration of Structural Health Monitoring and Fatigue Damage Prognosis
This paper presents a probabilistic methodology for model-based fatigue damage prognosis, which also incorporates information from structural health monitoring. This method adopts fracture mechanics-based fatigue crack growth modeling in the predictive prognosis, along with quantification of various sources of uncertainty, such as natural variability, data uncertainty, and model errors. Realtime monitoring data of external variable amplitude loading history is used to construct an adaptive autoregressive integrated moving average (ARIMA) model to predict future loading. A continuous Bayesian updating approach is used to adjust the ARIMA model in accordance with the real-time data. The on-ground crack inspection data on single component or fleet of components is used to quantify the uncertainty in the initial and current size of an existing crack. Bayesâ€™ theorem is applied to infer the probability distribution of initial crack size using the inspection results on fleet of components. The cycle-by-cycle simulation of fatigue crack growth is expedited via the use of a surrogate modeling technique (Gaussian process model) to replace computationally expensive finite element analysis. A numerical example, surface cracking in cylindrical components under service loading, is carried out to illustrate the proposed method.
Wavelet-Based SVM System for Evaluation of Wear States and Remaining Life Time
An approach for developing a fault diagnosis and prognosis system to support condition-based maintenance of wear parts is presented. The system is used as a prewarning module to detect the necessity for replacing wear parts of production machines and to evaluate the remaining life time of the supervised part. The system is based on a support vector machine as a signal-based classification technique and as a feature fusion tool. Relevant features are extracted using wavelet transform techniques with the aid of wavelet energy and entropy measures. A new approach for feature-based resampling is presented based on a multi-level wavelet decomposition. Measurements were processed to select the most reliable combination of characteristics to depend on. A related change index is proposed based on the decision value of the SVM to evaluate the remaining life time.
Sensor Location Analysis for Fatigue Crack Detection Using Nonlinear Acoustics
Structural Health Monitoring and Non-destructive Testing systems require reliable methods techniques that detect very small defects or indicate changes in structural performance at very early stages of deterioration. Guided ultrasonic waves and ultrasonic methods based on various nonlinear phenomena are often used for earlystage damage detection. The later has attracted many investigations for the last fifteen years. The paper investigates the effect of sensor location for crack detection in metallic structures based on nonlinear vibro-acoustic wave modulations. Surfacebounded, low-profile piezoceramic transducers are used for low- and high-frequency excitations. Ultrasonic responses are monitored using non-contact laser vibrometry. The study reveals plate areas more sensitive to nonlinear wave modulations.
Uncertainty Quantification and Validation of Finite Element Models of Bridge Structures
Finite element models are a key tool for the management and analysis of civil structures but little attention is generally paid to the Verification and Validation (V&V) of these models. The purpose of this paper is to apply a complete step-by-step V&V procedure to two bridge structures, a scale-model and an actual full-scale structure, in order to compare the methodological choices and results. Three dimensional finite element models were developed in order to predict the dynamic behavior of the target bridges. Experimental modal testing is performed in each bridge. Design-of-experiments (DoE) are established to analyze the effects of uncertainty in model parameters on the model simulation results in order to select the most uncertain and sensitive modeling parameters. These parameters are investigated through a Bayesian inference analysis aiming at obtaining the probability distributions of the parameters that reproduce the experimental variability. By analyzing the uncertainties in the model, interesting features of the real structure as well as the model can be achieved and the model gains in credibility.
Identification of the Stiffness Distribution Using BOTDR
BOTDR is one of the strain measurement technologies that is suitable for smart monitoring of civil engineering infrastructures. While the technology has the advantage of supplying spatially distributed data, it is currently limited to a spatial resolution of about 1 m. In a previous work, it was found that curvature increase along the beam can be related to the crack configuration. This, however, only appropriate to statically determinate beams, where no redistribution of internal forces is induced by the damage. Consequently, the use of the previously suggested relation to statically indeterminate beams may result in inaccurate estimation of the damage. In order to overcome this problem the current paper suggests an iterative identification algorithm which deals with statically indeterminate beams.
Co-Bonding of Piezoelectric Sensors on CFRP Structures
In order to replace conventional Non Destructive Testing (NDT), SHM needs to be at least as reliable and cost effective as the competing NDTTechnology. With respect to high recurring costs for sensor installation assuming state-of-the-art application procedures, wide area utilization with SHM sensors in aircraft seems to be not feasible. This results from the currently used secondary bonding process, at which the sensors are bonded to the cured structure by a multistage process. In order to reduce complexity, costs and required time of the bonding process, cobonding of the sensors is envisaged. Co-bonding is leading to several benefits regarding the process, as the sensors are applied outside the critical manufacturing path, but is leading at the same time to challenges regarding the sensor requirements. These requirements are outlined in the present work. In this context, different possibilities of sensor protection systems are presented. Additional the main basic requirement - â€œdo the sensors survive the autoclave-process?â€ - of sensor co-bonding is successfully tested using commercial available PZT-sensors. For this reason, several sensors were placed in different configurations on the wet material of a generic CFRP specimen and put into the standard autoclave process. To determine the degree of degradation, several self diagnosis tests are conducted. As a second step, sensors will be applied on a more realistic specimen. As result, the authors present the capability for co-bonding of PZT-sensors in principle, but challenging with respect to different aspects.
Development of Probability of Detection Data for Structural Health Monitoring Damage Detection Techniques Based on Acoustic Emission
Structural Health Monitoring (SHM) techniques have been developed as a cost effective alternative to currently adopted Non-Destructive Testing (NDT) methods which have well understood levels of performance. Quantitative performance assessment, as used in NDT, needs to be applied to SHM techniques to establish their performance levels as a basis for technique comparison and also as a requirement for practical aerospace application according to set regulations. One such measurand is Probability of Detection (POD). This paper reports experiments conducted to investigate the location accuracy of the Acoustic Emission (AE) system in monitoring events from Hsu- Nielson and fatigue crack AE sources as a route to establish the POD of AE in SHM. It was found that fatigue crack tips could be located at 90% POD within 10 mm accuracy.
Uncertainty Assessment in Structural Health Monitoring
This paper develops methods for the quantification of uncertainty in each of the three steps of damage diagnosis (detection, localization and quantification), in the context of continuous online monitoring. Sources of uncertainty include physical variability, measurement uncertainty and model errors. Damage detection is based on hypothesis testing of residuals, i.e the difference between nominal and damaged system-level responses. Localization is based on the comparison of damage signatures derived from the system model. Both classical statistics-based methods and Bayesian statistics-based methods are investigated to quantify the uncertainty in all the three steps of diagnosis, i.e. detection, localization, and quantification. While classical statistics-based methods use of least squares-based optimization, Bayesian methods make use of likelihood function and Bayes theorem. The uncertainties in damage detection, isolation and quantification are combined to quantify the overall uncertainty in diagnosis. The proposed methods are illustrated using two types of example problems, a structural frame and a hydraulic actuation system.
Very Dense Arrays of Sensors for SHM Based on Large Area Electronics
In spite of its potential, structural health monitoring is rarely utilized on real civil structures. The main reason for this is the cost and limited reliability achievable by current monitoring technologies. The sensors currently available must be sparsely spaced and either provide severely insufficient spatial-resolution for early damage detection or rely on complex algorithms that degrade specificity against practical environmental and variable-load conditions. The objectives of this research are twofold: (1) to investigate a sensing-system principle that provides low-cost monitoring through a dense and expansive array of sensors enabled by a technology called largearea electronics; and (2) to experimentally study how the high-resolution sensing offered by such a system can overcome the robustness and reliability limitations affecting current SHM technologies. A novel sensing approach based on dense arrays of sensors possible through large-area electronics is being developed and tested. The primary concepts related to structural sensing are presented in this paper along with preliminary test results. These demonstrate that the proposed technology and direct sensing approach are beneficial for both reliable and low-cost damage detection, as well as the localization of damage over large areas of a structure.
On-Board Structural Health Monitoring (OBSHM) Smart Tag
This paper presents a complete electronic smart monitoring system dedicated to Structural Health Monitoring (SHM) applications for aeronautics.
Highly Nonlinear Granular Crystal Sensor and Actuator for Delamination Detection in Composite Structures
We propose a new â€œgranular crystal sensor and actuatorâ€ based on highly nonlinear solitary waves (HNSWs) to detect delaminations in composite structures. HNSWs are compactly-supported energy packets, which are generated by a balance of nonlinear and dispersive effects in nonlinear media. Their unique physical properties allow the usage of HNSWs as novel information carrier for nondestructive evaluation (NDE) and structural health monitoring (SHM) applications. Particularly, HNSWâ€™s tunability and high power intensity can enhance sensitivity and energy-efficiency, offering advantages beyond the conventional linear-wave based diagnostic schemes. To efficiently generate and propagate diagnostic HNSWs, we assemble a granular crystal composed of closely packed elastic particles. This granular crystal can function both as actuator and sensor, by exciting a composite structure via injected HNSWs to an area of interest and measuring reflected pulses that carry diagnostic information about defects. In this study, we demonstrate experimentally the ability to detect delaminations in a carbon fiber-reinforced polymer (CFRP) composite panel using a prototype of granular crystal sensor/actuator. Preliminary results show that a compact granular crystal sensor/actuator can successfully detect artificially created delaminations in a composite panel. Due to the compactness and energy-efficiency of the granular crystal sensor/actuator, the proposed diagnostic method has the potential to become a portable and reliable sensing instrument for inspecting structural damages in critical areas of composite structures.
The Implementation of Piezoelectric Wafer Sensors for Acoustic Emission Sensing in Aluminum
Piezoelectric wafer sensors have been used extensively for the guided wave ultrasonic method in order to detect discontinuities at the aircraft aluminum components. This study shows the implementation of the piezoelectric wafer sensors for detecting propagating elastic waves in thin aluminum due to crack growth under fatigue loading using acoustic emission (AE). The responses of piezoelectric bulk and wafer type sensors to detect damage in a thin aluminum under fatigue loading are compared. The first comparison is conducted on a 1-mm thick plate made of 7075-T6 aluminum alloy using a piezoelectric actuator in order to control the frequencies of the propagating elastic waves. The actuator inputs are 3-cycle sine waves with sine envelope with 50 kHz frequency increments starting at 100 kHz to 400 kHz. In overall frequency range, piezoelectric wafer sensor is 9 dB less sensitive than conventional AE sensor. In the fatigue testing, the threshold levels of two sensors (conventional AE sensor as 50 dB, piezoelectric wafer sensor as 41 dB) are set up such a way that their dynamic sensitivity levels are similar. The AE hit rate histories of two sensors show a similar pattern, which indicates that both sensors detect the same events. Two piezoelectric wafer sensors placed at two ends of the sample can locate the damage source using the linear location algorithm. The sensors detect and locate the AE events earlier than visual observation. The cumulative AE event decreases when the sample is close to the fracture, which agrees with the theory that the volume of relaxing of material decreases due to the formation of dislocation arrays. The reduction in the AE hit rate and event accumulation after the cluster of events is detected can be considered as the proximity of the fracture. In the paper, in addition to the time based comparison of the sensors (e.g. hit envelope, amplitude, source location), waveform signatures and frequency contents of crack growth emissions detected by two sensor types are evaluated. The responses of the sensors are compared with the dynamic strain measurement at the vicinity of the hole. In summary, the piezoelectric wafer sensors show good promise to be used as the AE sensors in thin aluminum plates.
Diagnosis of Internal Defect of a Pipe by Mechanoluminescent Sensor
A novel technique has been developed to get the stress distribution by the mechanoluminescent (ML) sensor which can emits light in response to dynamic deformation [1, 2]. Using the ML sensor, we have realized a safety monitoring system for the bridges, buildings, tunnels, etc. successfully. A defect in a pressurized pipe was detected by mechanoluminescent (ML) sensor. In this paper, the hoop strain distribution on the outer surface of a defective pipe was obtained by ML intensity measurement and strain gage measurement. Additionally, a FEM calculation was also performed and compared with the experimental results. The hoop strain distribution obtained from the ML intensity agreed well with that obtained from the strain gage measurement and the FEM calculation. These results indicate that the location and depth of the defect in a pipe can be estimated by the ML sensor.
Development of an Integrated Fibre Bragg Grating Contact Pressure and Temperature Sensor for Composite Smart Manufacturing
Polymer matrix composites are widely used as structural materials due to their low weight and high strength vs. metallic ones. However, some issues concern their durability, the possibility of damage detection and prediction, the characterization of residual stresses, and the identification of their global mechanical properties. A better knowledge would help to understand the materialâ€™s structural integrity and the inevitable variability of properties induced by manufacturing processes. In this way, the monitoring of composite material manufacturing is a key feature for better process understanding and quality improvement. Today, measurements are often limited to global or indirect sensing, but very few are routinely performed locally or in the vicinity of the composite parts during the process. Therefore, controlling curing parameters in such areas where resin flows are complex appears relevant for process optimization [1-3]. In such a context, the research project ELICo-CP devoted to the development of a small and weakly intrusive optical Fibre Bragg Gratings (FBG)-based sensor for both contact pressure and temperature variation measurements has been initiated. Such a sensor will allow the measurement of contact pressures up to 10 bar with surrounding temperatures greater than 200Â°C in small curvature areas (down to 4 mm radius) inside manufacturing tools (autoclave and moulding processes based on a liquid resin injection). This sensor could be multiplexed and interrogated thanks to a high resolution and fast speed analyser similar to the BraggFITÂ® FBG measurement system already developed by the CEA LIST [4-5]. Experimental results of the sensor prototype, tested in a dedicated Resin Transfer Moulding (RTM) tool equipped with commercial reference sensors, demonstrate that the contact pressure variation information inside the mould can be measured with 0.1 bar resolution over the 10 bar range with such small sensors. However, for these first contact-pressure sensorprototypes, both hysteresis (10% full scale) and temperature cross-sensitivity shouldbe improved.
Development and Qualification of FBG-Based Strain Patches and Rosettes
A fibre Bragg grating (FBG) strain patch specially adapted for long-term and high-strain applications was developed and characterised. Additionally, in the case of unknown main stress axis, two fibre optic strain rosettes were developed. The design concept for the patch and the rosettes is based on a glass fibre reinforced plastic (gfrp) carrier material. The patches were characterised due to their strain gauge factor and fatigue behaviour. As a result, FBG strain patches with linear strain behaviour and excellent fatigue resistance were developed and can be used as part of a monitoring system for aerospace structures or wind turbine power plants. The rosettes were designed to be small in geometrical size and their strain transfer behaviour was characterised.
Characterization of Ultrasound Detection Using a Strain-Insensitive FBG Sensing System Incorporating Fiber Ring Laser
A fiber Bragg grating (FBG) ultrasonic sensing system incorporating a fiber ring laser was constructed. An FBG was used not only as a sensor but also as a ring cavity mirror in the system. The fiber ring laser emitted a laser at the Bragg wavelength of the FBG sensor. When ultrasound impinged on the FBG sensor, the intensity of the laser varied in accordance with the ultrasonic vibration. Ultrasound detection of this system is attributed to the wavelength dependence of optical gain in an optical amplifier used the fiber ring laser. Despite a considerable shift in the Bragg wavelength of an FBG sensor, this system could sensitively detect vibrations over a broad band ranging from a few Hz to hundreds of kHz.
Improved Sensor Concepts for Durability Monitoring of Reinforced Concrete Structures
Corrosion of the steel reinforcement is as a major problem affecting the durability and structural integrity of reinforced concrete structures. This leads to the need and increasing importance for an integrated non-destructive on site-assessment and longterm monitoring of durability related properties and condition parameters of concrete. In combination with non-destructive visual inspection and appropriate monitoring tools structural defects, degradation processes and damages can be identified at an early stage so that appropriate measures can be taken promptly. In this contribution a package of several newly developed and improved sensorbased measurement techniques for durability and corrosion monitoring of concrete structures will be presented. The thematic focus lays here on the current state of research, essential findings and acquired experiences as well as improvements and further developments of the different embeddable sensor types.
Photoacoustic Ultrasound Generation on an Optical Fiber Tip Using Gold Nanoparticles as the Target Material
Ultrasonic generators have been used in various applications such as medical imaging and nondestructive testing. The authors have proposed an integration of an ultrasonic generator and a receiver on one piece of optical fiber. The ultrasound wave is steered by the phased array technique, which is inspired by the way bats detecting objects in the dark environment. This application requires an ultrasonic generator featuring a higher frequency, a wider bandwidth and a smaller size. Conventional ultrasonic generators, which are made from piezoelectric materials, have difficulty in achieving the frequency higher than 10 MHz. However, real-time ultrasonic imaging applications need generators featuring frequencies higher than 30 MHz. Recent studies are developing novel ultrasonic generators via the photoacoustic mechanism. An energy absorption layer is applied to absorb light energy and convert it into heat. A mechanical wave is generated by the layer expanding itself due to the thermal expansion phenomenon. The ultrasonic generator based on the photoacoustic principle can exhibit high frequency and wide bandwidth. An ideal energy absorption layer must feature high energy absorption coefficient and high coefficient of thermal expansion (CTE). In this paper, a photoacoustic ultrasound generator on an optical fiber tip was designed, fabricated and tested. Gold nanoparticles (Au NPs) were coated on the end surface of a piece of commercial single mode fiber to be the energy absorption layer. Au NPs were synthesized by the traditional sodium citrate reduction method and the diameter of the Au NP was controlled at 20 nm. Layer by layer (L-b- L) technique was used to coat the Au NPs on the end surface of the fiber. By introducing excitation laser pulses on to the Au NPs, the laser energy was converted into the heat through photothermal effect and finally was turned into a mechanical wave by the thermo-elastic mechanism. The ultrasound generator exhibits very compact size due to the fiberâ€™s miniature size (125 Î¼m in diameter). The results from the experiment showed that an acoustic level of 2.44 kPa at 1.16 mm away from the fiber tip was observed. The laser energy density was 4.244 J/cm2 and the pulse width of the laser was 120 ns.
Properties of Interdigital Transducers for Lamb-Wave Based SHM Systems
Recently, an intensive research activity has been observed concerning the application of guided waves to long range ultrasound (LRUT) and structural health monitoring. Guided waves propagating in plates, known as Lamb waves, have appeared to be suitable for monitoring and condition evaluation of planar structures. Lamb waves can be generated using different types of actuators including piezoelectric or electromagnetic acoustic transducers. In this paper a novel type of piezoelectric transducers is presented based on macro-fiber piezocomposite (MFC). Contrary to the previously presented MFC transducers the transducers presented here are provided with interdigital electrodes matched to certain wavelength. Two different designs of interdigital transducers (IDT) made of MFC substrate are presented in the paper together with the results of numerical simulations and experimental tests.
Piezoelectric Paint as Spatially Distributed Modal Sensors
Piezoelectric materials have gained broad popularity in many fields since their first discovery by the brothers Curie in 1880. Recently, a new piezoelectric composite, the piezoelectric paint has been introduced into the field of structural health monitoring. Piezoelectric paint is a composite piezoelectric material which comprises of tiny piezoceramic particles, polymer resin and other additives. After polarization, it attains piezoelectricity and can be applied as a piezoelectric sensors/actuators. This work explores the application of piezoelectric paint as spatially distributed modal sensors. A spatially shaped modal sensor is a sensor that measures a single mode of a structure and filters the other modes out. Compared with the conventional discrete sensors, the distributed sensors are continuously distributed on the host structure. They are very useful in active control since it reduces the problems of spillover, where high frequency unmodeled modes affect the stability of the closed loop system. In this work, a piezoelectric paint is fabricated. It is flexible, can be applied to almost any structural surface and tailored to any shape. In addition, compared to traditional piezoelectric composites, e.g., PVDF, the polarization profile of the piezoelectric paint is easier to control according to the applications, which are very important for the design of a modal sensor. These advantages make the piezoelectric paint a very promising candidate for a spatially distributed modal sensor.
Towards Smart Sonar Transducersâ€”Polarimetric Sensing for Sonar Array Compensation
An optical fibre polarimetric sensor is discussed for monitoring the acoustic output of an immersion sonar transducer in the frequency range around 250 kHz. It is shown that the sensor was suitable for both narrowband and broadband applications, and experimental results are presented to compare the measured sensor output with numerical models. Applications for the sensor include periodic sonar array calibration, and real time compensation to modify output acoustic field characteristics.
This paper presents the implementation and characterization of a wireless strain measurement system that features ultra-low power consumption, wireless strain transmission, and wireless powering. The wireless strain sensor consumes about 6 mW. To achieve such an ultra-low power operation, a voltage-controlled oscillator (VCO) was used to convert the direct-current (DC) strain signal to a high frequency oscillatory signal, which is then wirelessly transmitted using an unpowered wireless transponder. A wireless RF powering module provides the power for the sensor node. The application of such sensor in structure health monitoring could bring the benefits of reduction of the wiring cost, and high sensor density with great sensor portability.
Flexible Integration Techniques for Wireless Sensors Network Deployment: Application to Aircraft Structure Health Monitoring
This paper describes the realization of a 60GHz wireless communicating node integrated on a flexible substrate for wireless sensors networks. These wireless communicating objects are composed of sensors and a transceiver which includes digital baseband, RF front-end at 60GHz and an antenna. The MAC layer which establishes the network is also integrated in ASIC together with the digital baseband and reported by flip chip on flexible substrate. The 60GHz band was chosen because of its short range propagation and its directionally which is a major advantage for wireless sensor networks deployed in a small, closed area, like an aircraft. The main advantage of the flexible substrate integration is the realization of wireless sensor networks which can be placed in all locations, even those difficult to access. The main application addressed in this paper is Structure Health Monitoring for aircrafts.
Detecting the Debonding of Adhesively Mounted Sensors in an Optimally Designed Structural Health Monitoring System
The ability to distinguish a debonding sensor from structural damage is a challenging issue in structural health monitoring. This study presents a method for detecting a debonding sensor when considering a group of sensors comprising an optimally designed structural health monitoring system. Experimental data is obtained by bonding accelerometers to an aluminum fitting that is repeatedly cycled though temperatures ranging from -60 to 150 Â°F to cause adhesion failure. The effects of damage are examined in a separate experiment. The data is used to develop several metrics for identifying a debonding sensor on a damaged structure.
Power Management in a Wireless Sensor for Structural Monitoring Application
This paper describes the power management approaches in a wireless sensing unit for structural monitoring techniques targeted to civil engineering applications. The wireless sensing unit is designed for some types of sensors with different power requirement and it is mainly based on the advanced System on Chip low power transceiver. The power management module of the unit mainly consists of low quiescent current Low Dropout (LDO) linear regulator and switching regulators which feature a low quiescent current, a highly efficient power conversion, an adjustable output voltage and a medium output power. As a result, the designed and prototyped unit is suitable for both low-power and non low-power sensors.
Integrating Diamond Sensors in Silicon Technology Integrated Circuits
This paper presents the results of a research program aimed at developing passive and active circuit components to be used in missiles and other air vehicle applications. The team of Advanced Engineering Technology (AET, Inc.) and Vanderbilt University is developing diamond sensors that will be integrated with a silicon-based integrated circuit for incorporation into aircraft and missiles. Specifically, the team is developing the technology necessary to integrate chemical vapor deposited (CVD) diamond films with the silicon integrated circuit.
Development of a Bi-axial Accelerometer Based on Intensity Modulated Plastic Optical Fiber for Wind Turbine Monitoring
The paper proposed an intensity modulated bi-axial accelerometer made from plastic optical fiber. The comparing to traditional piezo-electric accelerometer, the proposed design is light-weight, low-cost and immune to electromagnetic interference. The bi-axial acceleration was measured by light intensity coupling between a cantilever fiber and two receiving fibers. With pre-calibration, the two light intensity output are used to compute x and y components of a 2D acceleration. The frequency response test showed stable performance of the accelerometer up to 80 Hz, which is sufficient for the purpose of wind turbine monitoring.
Intelligent Structural Health Monitoring Using Carbon Nanomaterial Networks
Below is a set of instructions for preparing your paper in a format suitable for camera-ready or the intended media for this proceedings. Remember, if camera-ready, your manuscript will be photographically reproduced as received. It is most important that you follow these guidelines as closely as possible and adhere to the margins (discussed below) for overall consistency and format relationship to all other papers in the intended proceedings. Whether camera-ready or not, please follow the guidelines.
Characterization of an Elastomer Based Autonomous Sensing-Actuating System
Elastomers are materials which exhibit variable stiffness with respect to temperature. This property can be utilized in designing a system to sense the temperature and act according to a pre-design, autonomously. The stiffness change is remarkable near to the glass transition temperature. Hence to get the best effect of design, the device can be designed by the proper selection of the type of elastomer so that the glass transition temperature can be shifted to the desired value. The present paper describes an elastomer based sensing-actuating system in the form of a bender which is designed using a spring steel strip with cured elastomer layer bonded to it and pre-loaded. The paper gives the details of characterization of the device with reference to temperature and with various degrees of pre loading. The experiments are also carried out with different elastomer materials. The results are recorded for all the configurations and analysed. The studies are also carried out at different humidity conditions. The pre loading is carried out by winding the spring steel strip around a cylinder and bonding the elastomer layer around that. The bonding agent has been selected based on the temperature range required to be sensed and the materials to be bonded. An environmental chamber is used to obtain the different temperature conditions. This unit has a programmable controller where temperature and humidity can be set. The chamber has a cut out to access the device at different temperatures. The bender type system is positioned in the environmental chamber with one end fixed to the base. The other end is connected to a link which is taken through the access point. The temperature at the device is recorded using a thermocouple fixed to it. The measurements are carried out using a strain-gauged link, which is calibrated prior to the experiment. A precision Linear Variable Differential transformer (LVDT) is also connected to the free end in order to measure the displacement. The measurements are made through out the temperature range. The calibrated sensing-actuating system can be used for sensing the temperature and to trigger a desired action in various applications. Some of the typical applications are sensing and actuating in hostile conditions, space applications, operation of self sensing thermal valves.
Overview of the European FP 7 Project â€œAircraft Integrated Structural Health Assessment IIâ€ with Focus on the Detection of Corrosive and Hydraulic Liquids by Gauges Based on the Collapse of Percolation Conductivity
The European project â€œAircraft Integrated Structural Health Assessment IIâ€ AISHA II focuses on the development of structural health monitoring systems for aircraft with a relatively high technology readiness level (TRL). As full-scale parts aluminium alloy-based floor beams, stringer-stiffeners structures, slat-tracks made of maraging steel and helicopter tailbooms consisting of monolithic and sandwich CFRP were selected. The applied NDT technologies are based on ultrasonics as well as on electrical and electrochemical impedance measurements. Due to the dominance of platestructures, guided ultrasonic waves are used, such as Lamb waves and Rayleigh waves. In this context, mode conversion effects are exploited and detected with appropriated sensors arrays. Another promising candidate is high-end time-of-flight detection of Lamb waves using chirp technology. Such ultrasonic systems were used for helicopter tailbooms, slat tracks and aluminium sheet structures. For more local damage detection, the interruption of electrical signals by fatigue crack formation (slat tracks and aluminium sheet structures) or by leaking corrosive liquids (floor beams) appears to be successful. Finally, electrochemical and electric impedance spectroscopy is used for detecting corrosion in floor beams and cracks in doubler repairs. For all systems proposed, durability and robustness is a major concern. Since April 2011 a first sensor system for detecting aqueous liquids in floor beams was implemented in an operational airliner Boeing 737-500 (Lufthansa).
Fiber-Optic Extensometer Array in a Small Alcove at 1.25-km Depth in the Sanford Laboratory at Homestake, Lead, South Dakota
We are establishing a dense array of fiber-optic sensors in a small alcove at 4100-ft (1250-m) depth in the Sanford Laboratory at Homestake in Lead, South Dakota. The monitoring array will measure deformation in intact rock and serves also as an experimental site for research in structural health monitoring of deep underground spaces. Our GEOX^TM (Geological Optical eXtensometers and Tiltmeter) collaboration has installed approximately 10 Fiber Bragg Grating (FBG) strain and temperature sensors, which each house between 2 and 12 FBG gages, as well as distributed temperature sensing cable (DTS) in an alcove measuring 2 x 3 m and 2 m high and in the associated drift.
Inter-Digitized Transducers (IDTs) for Structural Health Monitoring (SHM) Applications
Single element piezoelectric plates having inter-digitized electrode patterns, specifically tuned to operate at several hundred kHz to several MHz of frequencies, have been designed and fabricated by a laser micro-machining process. These narrow band low profile sensors are extremely effective to induce Rayleigh surface waves directly on the surfaces of various materials including metals, plastics and composites. Ultrasonic signatures of flaws, defects and damages on the surfaces of materials are easy to interpret due to the non-dispersive wave property of Rayleigh waves. Laboratory tests prove that detection of a deterministic fatigue crack on a metallic structure is straightforward in terms of changes in amplitudes. As a first step toward SHM application of IDT sensors to composite materials, the ultrasonic properties of the test panels made from polyester and glass fiber have been measured with respect to the fiber directions. Unlike isotropic metallic structures, anisotropy caused by glass fiber directions affects the ultrasonic properties as well as detection of defects and flaws in composite panels. Artificially induced surface cracks and impact damage on test panels are used to quantify the size, location and severity of damage in terms of changes in amplitudes. It is estimated to cover a distance close to one meter with a set of IDT sensors, one transmitter and two receivers for the composite panels, while the distance coverage can reach several meters for metallic structures at a several hundred kHz of frequency.
Monitoring of 3D Composite Structures Using Fiber Optic Bragg Grating Sensors
This paper presents an experimental investigation of the fatigue properties of a novel type of composite structure. Specimens were made from a so-called 3D carbon composite, with integrated Fiber Bragg Grating sensors. Fatigue tests were carried out to evaluate the suitability of this kind of sensor for monitoring the structural health of 3D structures.
Inherently Conductive Polymer Based Structure Health Monitoring Sensor for Composite
A soluble polyaniline was synthesized through emulsion polymerization and characterized using differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), gel permeation chromatography (GPC), and viscosity analysis. The electrical conductivity is found to reach 1000 S/cm with specific post doping treatments. Multiple printing processes, such as inkjet printing, screen printing and aerosol jet printing etc, make it feasible to print a variety of sensor patterns. The electromechanical response of these sensors was used to measure strain/stress or damage of composite structures under various load conditions expected to be experienced by aircraft. These unique conductive polymer sensors provide a feasible, near real time monitoring system for composites without adding significant additional weight to the structure.
Versatile and Easy-to-Assemble Measurement System for Impedance-Based Structural Health Monitoring
In this paper we present a versatile and easy-to-assemble measurement system for structural health monitoring (SHM) based on the electromechanical impedance (EMI) technique. The hardware of the proposed system consists only of a common data acquisition (DAQ) device with external resistors and allows real-time data acquisition from multiple sensors. Besides the low-cost compared to conventional impedance analyzers, the hardware and the software are simple and easier to implement than other measurement systems that have been recently proposed.
High Sampling Rate Fiber-Optic Extensometry for Ultrasonic Wave Detection
A high-speed Fiber Bragg Grating interrogator system has been designed and tested in the ultrasonic frequency region, focusing on its potential application to for Structural Health Monitoring. The overall performance of the setup is discussed, and the response of the system under sine and square signals of various frequencies is studied.
Inertial Energy Harvester for Monitoring Wind Turbine Blades
In order to operate a structural health monitoring (SHM) device for a wind turbine blade, one needs to use a slip ring to siphon power from the turbineâ€™s generator or use a power source inside the blade. An energy harvester mounted inside the turbine blade capturing energy from the blades rotation would be a great solution for powering a SHM device for a long period of time. The low rotation speeds (between 5 and 20 RPM for the many large scale turbines) make it challenging to harvest sufficient power. Previous research into energy harvesters in rotating environments (e.g. automotive wheels and propellers on large ships) has examined much higher rotation speeds (in the range of 100 to 1000 RPM). At the rotation speeds of large wind turbines, these harvesters have either not been tested or they produced only a few hundred microwatts. This paper discusses the modeling and experimental validation of an inertial energy harvester for use in low speed wind turbines to power a SHM device. The harvester consists of a magnet placed inside a slider tube and a coil mounted on the outside of the tube. The harvester assembly is then mounted radially inside the turbine blade. As the turbine rotates, the magnet slides along the tube and through the coil. The moving magnet induces a voltage across the terminals of the coil. This voltage can be stored in a capacitor or rechargeable battery which would in turn supply power to a health monitoring system. This paper will outline the modeling of the harvester, validation of an electromechanical coupling model, and testing a prototype harvester on a rotating apparatus.
Load Shaping for Maximizing Energy Capture and Structural Health in a HAWT Using Rotor-Mounted Inertial Sensors
It has been shown that even a small decrease in the accuracy of a turbineâ€™s yaw control due to hysteresis of the yaw drive and other factors results in considerable loss in energy capture by the rotor. As a cost-effective means of characterizing the turbineâ€™s dynamic response when such losses are experienced, it is proposed that rotor-mounted inertial sensors can be used to measure static and dynamic variables that are correlated with swept wind loads on the blades. Based on these measurements, it is shown that the yaw set point can be tuned to shape the loads on the rotor to maximize energy capture. Improved maintenance schedules for individual turbines can also be realized using these measurements to reduce turbine down time and increase turbine component life. For example, cyclic loading that is observed in the lead-lag direction is known to cause torsional oscillations that result in accelerated gear and bearing wear. Free and forced dynamic response measurements on a 2.1 meter horizontal axis wind turbine are used to characterize the rotor-dynamics of a turbine operating in yawed wind flow to demonstrate that rotor-mounted inertial sensors provide an effective means for characterizing the wind loads on the rotor disk.
Passive Damage Monitoring of Wind Turbine Rotor Blades Using Cyclic Signal Processing
As of Q1 2011, 41,400 MW of wind energy had been installed in the US and those installations are on pace to achieve the US DOE goal of 20% wind energy by 2030. With this increased level of penetration from wind generation, the stability of the electrical grid will become dependent on the reliability of offshore and terrestrial wind turbines. Structural health monitoring (SHM) integrated into the Operations & Maintenance (O&M) strategy of wind plants has the ability to both increase reliability and reduce O&M costs. Sandia National Laboratories Wind Energy Technologies Department (SNL) has been actively researching SHM technologies at the subcomponent, component, and full system levels in both computational and experimental efforts for both terrestrial and offshore wind plants. SNL commissioned the fabrication of a Sensored rotor blade during Spring 2008 as a test bed for promising wind rotor monitoring technologies, including strain gages, fiber Bragg gratings, RTD temperature sensors and accelerometers. Following operational testing, the rotor blade was shipped to the National Renewable Energy Laboratory National Wind Technology Center to test structural health monitoring techniques during a fatigue to failure rotor blade test. To understand the structural state of the rotor blade, a method was devised to estimate Frequency Response Functions from the fatigue excitation and response. The results showed that the method for estimating FRFs could be used to monitor the fatigue test magnitude, phase and structural characteristics throughout the 2M cycle test.
Vibration Based Damage Detection for Structures of Offshore Wind Energy Plants
The offshore wind industry has been growing significantly in the last years. Consequently, a need of structural health monitoring (SHM) methodologies arises to monitor the expensive structures of offshore wind plants (OWEP) which are often difficult to access. Using the vibration of the plants to extract damage sensitive features is often accompanied by problems due to variations of the dynamical properties with the changing environmental and operational conditions (EOC). So it could happen that the EOCs have the same effect on the features variation as a damage. In order to design adequate SHM algorithms for OWEP monitoring, the paper starts with a discussion of the basic characteristics of excitation sources, vibration and environmental conditions of OWEPs. Subsequently, the theoretical backgrounds of the null space-based damage detection algorithm (NSFD) and one approach for compensation of EOC effects by means of fuzzy-classification techniques are presented. Finally the theory and the algorithms are successfully tested with time series from the OWEP M5000 and with data from a OWEP laboratory model.
Investigation of Various Condition Monitoring Techniques Based on a Damaged Wind Turbine Gearbox
The National Renewable Energy Laboratory presented an investigation of various wind turbine drivetrain condition monitoring (CM) techniques at the 7th International Workshop on Structural Health Monitoring held in 2009. The study contained in this report is a continuation of the 2009 paper and focuses on results obtained by various CM techniques from a damaged Gearbox Reliability Collaborative test gearbox. The purpose of the study is to demonstrate the capabilities and limitations of each technique. In order to provide the audience a relatively complete picture, a brief discussion of CM system implementation is provided first. The dynamometer test setup, along with some failure information on the damaged gearbox obtained during its disassembly, is presented next, followed by the CM results obtained during the retest of the damaged gearbox. For comparison and discussion purposes, earlier results obtained from a test gearbox under healthy condition will also be included. Finally, the paper will conclude with some observations obtained during the tests.
Compressive Sensing Approach for Structural Health Monitoring of Ship Hulls
The research presented in this paper aims to use compressed sensing algorithms to reduce the size and complexity of data sets relevant to structural health monitoring applications. Compressed sensing (CS), a powerful new data processing paradigm just beginning to emerge, proposes to accurately reconstruct unknown signals which are assumed to be compressible in some basis. Samples are taken as projections of the sparse signal onto an incoherent domain. Compressed signals are generally reconstructed via convex optimization or greedy algorithms that solve for transform coefficients most consistent with the samples taken. The advantage of CS based data acquisition lies in the amount of work saved at the sensor in data acquisition, storage, and transmission payload. In the context of wireless sensors engaged in structural health monitoring, the reduction in the number of samples possible with CS directly translates to power and communication bandwidth savings, two immensely important constraints in a wireless sensor network. CS exploits the sparsity that is so often present in natural signals such as strain response of structures subject to wave loading. As a case-study, this paper explores the use of CS in the structural health monitoring of the FSF-1 Sea Fighter, a small waterplane area twin hull (SWATH) littoral combat ship.
Structural Damage Identification in Stiffened Plate Fatigue Specimens Using Piezoelectric Active Sensing
This paper presents a guided wave structural health monitoring (SHM) technique, based on the use of piezoelectric active-sensors, used to determine the structural integrity of stiffened aluminum plates. For damage detection, the transmitted power between piezoelectric transducers used for Lamb wave propagation is utilized to analyze the extent of damage in the structure. Damage initiation and propagation were successfully monitored with the guided wave technique. Overall, these methods yielded sufficient damage detection capability to warrant further investigation into field deployment. This paper summarizes considerations needed to design such SHM systems, experimental procedures and results, and recommendations that can be used as guidelines for future investigations.
Health Monitoring of Aluminum Weldings with the Surface Response to Excitation (SuRE) Approach
Recently, the impedance and Lamb wave methods were used to evaluate the integrity of welded structures. Both approaches were proven to detect defects at the other side of the welded butt joints. In this paper, the Surface Response to Excitation (SuRE) approach was used and compared with the other two methods for evaluating the integrity of the welded structures. The SuRE approach was found to be an effective structural health monitoring (SHM) tool for inspection of welded structures while yielding results similar to the other two methods. Overall, the SuRE approach is very similar to the impedance method, with the main difference being the necessity of using two transducers instead of one self-sensing actuator.
Distributed Sensor Network for Structural Health Monitoring of Ships
The Strain Acquisition and Monitoring System (SAMS), currently under development for the Navy, is a scalable network of distributed, low cost, miniature strain sensor nodes that acquire and relay strain data to a strain data monitor user interface. The SAMS architecture significantly reduces the amount of cabling required to instrument structures of interest, is tolerant of EMI, and is capable of running indefinitely without batteries. In this paper, we present the results of the research and development of a preliminary prototype SAMS that was successfully demonstrated to the Navy as a proof of concept.
Cochlea-Based Spectral Decomposition of Sensor Signals for Resource-Constrained Sensor Networks
The biological nervous system represents a highly efficient method of sensing and transmitting information from the external world through a condensed format. Additionally, the system is capable of aggregating information from various sources and actuating based on the perceived external stimulus. This entire process is performed instantaneously, allowing for real time sensing and actuation. Of particular interest in this study is the succinct sensing methods exhibited by the human ear, which can comprehend a wide variety of sound frequencies, as well as a large range of decibels. To perceive sound, the ear uses a novel method of place theory and frequency decomposition. This study will focus on mimicking the techniques used in the ear for applications of signal decomposition in sensor networks. The benefit of this method can be a highly compressive form of data that requires less bandwidth and energy in resource constrained sensor networks. The accuracy of the proposed signal decomposition technique was validated using simulated sensor signals. Additionally, a prototype signal decomposition device was developed to experimentally validate the decomposition technique.
Bio-Inspired Smart Skin Based on Expandable Network
Methods for creating an electronic skin with integrated temperature sensors based on highly expandable polyimide substrate have been developed. Stresses and strains due to electronic skin expansion are minimized through unique designs developed using finite element analysis. Through the use of a uniquely patterned polyimide substrate an expansion ratio of 1,000% is achieved and the electrical resistance of wire components is maintained from pre-expansion to full expansion. Platinum resistance temperature detectors and electrodes are integrated directly in the polyimide-based electronic skin through a non-standard micro fabrication process. Real-time distributed temperature measurement has been achieved through this highly expandable electronic skin.1
Integrated Piezo-Element Drive Electronics for Structural Health Monitoring
This paper presents the theory and design of an integrated piezo-element drive chip for use in active Structural Health Monitoring (SHM). The integrated circuit (IC) can drive a miniature piezoelectric transducer with a tone-burst signal of Â±36 V up to 850 kHz. This combination of high voltage, high frequency and the type of waveform, as dictated by the application, is beyond the capability of existing ICs. We propose a solution using pulse width modulation (PWM), in which the tone-burst signal is rendered by a series of precisely timed pulses. The switching times of the PWM pulses are engineered by formulating and solving a least square optimization problem. The accuracy of the switching times is the most crucial design requirement for an IC implementation of this scheme. A circuit technique is introduced to compensate the uncertainty of the switching times to achieve sub-nanosecond timing accuracy.
Micropillar Sensing Element for Bio-Inspired Flow Sensors
This paper describes the efforts toward the development of bio-inspired flow sensor. Anatomy study has indicated a basic transduction element is the hairy structure. This study describes the fabrication of sensing element that emulates the mechano-electrical transduction mechanism. Different transduction element designs were investigated. Especially, the hairy structure made of the SDW method not only produces transduction component for mechano-electrical coupling, it is also rugged, sensitive and fracture resistant. The hairy structure also features directional sensitivity which could be used for acoustic field direction determination. The hairy structure is being further refined and will ultimately be integrated into develop bio-inspired flow sensors.
A Bio-Inspired Nanocomposite for Photocurrent-Based Strain Sensing
In this study, a photosynthesis-inspired nanocomposite strain sensor is proposed, and its sensing performance is characterized. Contrary to conventional strain sensors, the proposed sensor can measure applied strains using photocurrent generated by ambient light illumination and thus do not require an external power source for longterm operations. First, fabrication of the poly(3-hexylthiophene) (P3HT)-based multilayer thin film using spin coating is presented. Holes and electrons can separate at p-n heterojunctions within the P3HT-based photoactive layer to generate photocurrent. In addition, films with and without double-walled carbon nanotubes (DWNT) will be investigated. Second, photocurrent generation validation tests of the two types of films will be conducted. It has been found that the films generate time-variant photocurrents but can be fitted using an exponential decay model. Finally, both types of films will be subjected to tensile cyclic loading while their generated photocurrent is recorded. The results show that films enhanced by DWNTs will increase their photocurrent generation in tandem with increasingly applied strains and exhibit good linearity, repeatability, and high strain sensitivity of 6.03.
Improving the Reliability of Sensor Skins for Structural Health Monitoring
Fatigue cracking is one of the most common failure modes in load carrying structures. Detecting small fatigue cracks requires densely distributed sensors over a large area. By implementing multiple sensors on a flexible substrate, an engineered sensor skin that can detect small crack over a large area may be realized. Recently, we presented the implementation of such a sensor skin based on microstrip patch antenna and demonstrated that it can detect sub-millimeter crack growth. However, due to the fatigue loading, the sensor skin showed signs of either tearing or debonding from the host structure. This can cause significant reliability issues and might also cause misrepresentation of the crack in practical applications. In this paper, we investigate the inclusion of an additional flexible layer between the host structure and the sensor skin to relieve the strain transfer from the specimen to the sensors and thus improved the reliability of the sensor. Finite element simulation indicated that a 70 Î¼m thick PDMS layer can reduce the strain transfer by up to 40%. The improvement in the reliability of the sensor was validated experimentally. The fabrication of the PDMS layer and its effect on the resonant parameters of the antenna sensor are discussed.
Bio-Inspired Computing Algorithms for Adaptive Structural Health Monitoring
This paper studies a bio-inspired pattern recognition algorithm for the structural damage detection and classification in changing environments. Biological system such as natural immune system is a remarkable distributed information processing system. It uses feature extraction, signaling, learning, and memory mechanisms to solve pattern recognition and classification problems. Artificial-immune-systembased damage pattern recognition algorithms detect damage patterns by examining the deviations of real-time sensor data from a normal pattern model (a set of representative feature vectors for the normal pattern). To enhance the adaptability of the presented algorithm, the normal pattern model is updated when the temperature changes. The performance of the updating of the normal pattern model is evaluated using environmental monitoring data collected by the SIMCES (System Identification to Monitor Civil Engineering Structures) project. The validation result shows that the updating of the normal pattern model increases the success rates of the damage detection.
Field Validation of Flexure-Based Mobile Sensing Nodes on a Space Frame Bridge
This research investigates the field validation of flexure-based mobile sensing nodes developed for structural health monitoring (SHM). Each mobile sensing node is a miniature robot that can carry sensors and automatically navigate on a steel structure. The flexible body design of the mobile sensing node allows it to negotiate with sharp corners on the structure. Multiple mobile nodes then form an organic mobile sensor network that can search for potential structural damage. Our previous research has investigated the performance of the mobile sensing nodes through laboratory experiments. The mobile sensor network was able to identify minor structural damage, illustrating a high sensitivity in damage detection that is enabled by the flexible deployment of the mobile sensing nodes. This paper extends the investigation into field study with a space frame bridge. Under wireless control command, multiple mobile and tetherless sensing nodes navigate autonomously to different sections of the steel bridge, for measuring structural vibrations at high spatial resolution. Using a small number of mobile sensing nodes, detailed modal characteristics of the bridge are identified.
Development of a Bio-Inspired Bridge Health Monitoring System
A bio-inspired bridge structural health monitoring (SHM) system to evaluate the scouring depth of bridges by measuring the dynamic response of superstructure only is developed. The main objective of this research is develop an effective bridge SHM system to meet the urgent necessity of monitoring the large amount of old and aging bridges in the world. To solve the unique and complicated problem, the dynamic scouring effect is carefully considered in the bio-inspired bridge SHM system. The array expression data format is proposed for the development of the SHM algorithm to transplant the Deoxyribonucleic acid (DNA) array concept from molecular biology to the field of SHM. A two-tier auto-regression with exogenous (AR-ARX) process is used to extract the expression array from the recorded ambient vibration response. The scouring depth of the bridge is then determined by the proposed SHM algorithm based on NaÃ¯ve Bayes (NB). To verify the performance and reliability of the SHM algorithm, a series of experiment on a scaled down single-column bridge model with dynamic scour impact under flooding was conducted with various settings of initial scour depth to clarify the complicated fluid-solid-coupling effect. Test results from the dynamic flooding test showed that the scouring depth of the bridge can be reliably identified by the proposed SHM system. The performance of the bio-inspired bridge SHM system has been successfully demonstrated.
Towards Autonomous Wireless Sensors Systems in Civil Engineering: Paving the Way to an â€œEnergy Oriented Design Methodâ€
Last years, SHM and similar non-destructive techniques communities have developed and published solutions and efforts regarding wireless and smart sensors solutions. Those numerous works clearly demonstrate the immediate gain that wireless solutions imply especially when applied to civil engineering structures: cost-effectiveness, simplicity, more mobile and reusable devices, etc. As an evidence, the main input constraint when designing a wireless instrumentation (sensor or other) refers to energy saving. In that prolific domain, numerous solutions are designed with more or less positive results. Most known or commercialized solutions refers to improved and optimized electronic design that save energy. But, in most of the case, the consequence resides in sensors that offer lower sampling rate (up to some Hz), lower computing abilities, and limited wireless communications: distances, rates, durations.... Moreover some other functionalities are forgotten when sensor is too focused on energy: synchronization, intelligence. The aim of this paper is to pave the ground of methods and approaches that refers to energy harvesting to make wireless sensors able of high level functionalities. More than some general considerations, this paper also includes real and technical feedback that French Public Works Laboratory (IFSTTAR) obtained through the application of its generic and wireless sensor platform (PEGASE) in collaboration with SATIE Laboratory (from ENS-Cachan). This article first makes the distinction between the sensor's sub-entities from the energy point of view: sources, charge, storage. Then, in view of optimal dimensioning (solar cells, battery capacity), concept of degree of freedom is introduced as well as a concept of quality index from energy point of view. The article proposes a method that details
Radar Sensor Based Accurate Tumor Tracking for Respiratory-Gated Lung Cancer Radiotherapy
As a promising motion-adaptive tumor treatment, respiratory-gated radiotherapy carries its merits of minimizing incidence and severity of normal tissue complication by precisely adapting the radiation beam to the targeted lung tumor. Accurate measurement of respiration motion is of vital importance in respiratory-gated radiotherapy. However, conventional gating techniques, relying on implanted internal markers or external markers placed on patientsâ€™ body, are either invasive to the patientâ€™s body or bring insufficient accuracy and discomfort to the patients. In this paper, we present an accurate noncontact means of deriving respiratory gating signals for the use in gated lung cancer radiotherapy. Two 5.8 GHz radar sensors are used to monitor the chest wall and abdominal movements simultaneously to get high resolution and enhanced parameter identification. The radar sensors can also be used in structural health monitoring (SHM). It is shown that our multiple radar system can supply reliable gating signals for accurate mobile tumor tracking in radiotherapy.
Computation of Lifetime Value of Information for Monitoring Systems
Structural Health Monitoring (SHM) systems are useful instruments for limiting the risk related to seismic events. Aside from the cost of the devices and the convenience of their operation, the selection of these systems should be guided by the quality of the information gained and by their effect on reduction of overall losses. This selection can be guided quantitatively by the Value of Information (VoI) principle of decision theory. VoI is essentially the difference between the expected loss of managing a structure without and with the SHM system. Indeed, while a monitoring system can provide improved information as to damage suffered by the structure, it is only by considering the savings resulting from subsequent decisions (e.g., inspection, repair, continued operation or closure of the structure) that the value of such a system can be determined. An accurate estimation of the VoI generally requires running a large number of simulations, making use of complex numerical models, and its computational cost is high. Therefore, a procedure for obtaining an approximate estimate by a relatively small number of simulations is needed. In this paper we investigate a numerical approach based on Monte Carlo simulation and non-parametric regression to estimate the VoI. Application of the proposed technique is presented on a bridge model subject to seismic excitation and instrumented with accelerometers.
Carbon Nanotube (CNT) Enhancements for Aerosurface State Awareness1807
The goal of the present effort was to develop an integrated system capable of reliable ice-detection, de-icing and anti-icing in addition to structural diagnostics to enable aerosurface state awareness. The basis for the system is nanoengineered structured carbon nanotube (CNT) enhancements that can either be embedded within the composite laminates during manufacturing, or applied as a separate surface layer in a secondary process. The aligned CNTs are sufficiently long (20- 30 um) to span interply matrix regions, acting as mechanical reinforcement in addition to improving electrical conductivity by a factor of more than a million. Optimized electrode patterns are applied to the CNT-enhanced structure, and hardware provides closed-loop feedback control. Ice-detection is based on effective heat capacity, where power is applied to CNT-enhanced laminates (termed fuzzy fiber reinforced plastic, or FFRP) for seconds, and the slope of the temperature rise can be correlated to the thickness of ice present. For de-icing (melting) and antiicing (prevention of ice formation) a resistive heating principal is used. Voltage is applied to the FFRP material, which heats rapidly due to the small but finite resistance imparted by the CNTs. Structural diagnostics is achieved by monitoring and mapping changes in electrical resistance across electrode grid paths.
Optimal Sensor Placement and Weighted Residual Method in Loads Estimation Supporting Structural Health Monitoring
This paper introduces a new methodology for estimating reaction forces going through an aerospace connector in six degrees of freedom (6DOF). The system uses a trained network approach to transform strain measurements from fiber optic gages to forces. A model of the noise is constructed and the uncertainty of the prediction is quantified. Finally, an optimal strain sensor placement algorithm is developed using the weighted residual method. This 6DOF load cell design is being used to support loads tracking for structural health prognosis in the connector.
Uncertainty Quantification in Transmissibility-Derived Features Used for Fault Detection
A common feature used in system identification procedures is transmissibility, which is the frequency-domain ratio between any two outputs and is formally defined as the relative admittance between those two measurements; it is often interpreted as the response normalized by a reference response instead of by the actual input. Several researchers have used the transmissibility, or other features derived from changes in it, for various structural health monitoring applications. In this paper, we consider a SIMO identification model and regard the change in transmissibility as a feature correlating with damage occurrence. Both inherent randomness due to the estimation process and external sources of noise contamination are included as sources of uncertainty in the transmissibility. Quantification of this uncertainty is necessary to group-classify the measurements into either undamaged or damaged (binary) conditions with a clearer understanding of Type I/II trade-offs in a way that facilitates proper decision-making. The paper uses Receiver Operating Characteristic (ROC) curves for individual frequency lines as the key performance metric across the entire frequency domain and use Area Under Curve (AUC) as the metric to quantify the performance of the ROC. The paper proves that regions near resonance will have the best hypothesis test performance in terms of sensitivity and specificity.
Quantifying Damage Measures for a Composite Steel Girder Bridge Using Finite Element Analysis
The purpose of bridge monitoring efforts in Connecticut is to monitor critical vulnerabilities in bridges. In doing so it is important to quantify anticipated changes in measurements resulting from different types and levels of damage with the intent of comparing these changes to the inherent variability in actual bridge measurements to identify the minimum level of vulnerability that can be identified through bridge monitoring. In this paper, three damage measures including, natural frequency, strain distribution, and neutral axis location, will be analyzed using a finite element model of a multi-girder composite steel girder bridge. The bridge examined here has been monitored by the University of Connecticut in conjunction with the Connecticut Department of Transportation for the past several years. Three different types of damage at various levels of severity were examined using an analytical model of the bridge. It was observed that cracking damage and deck deterioration is very difficult to detect showing very little change in any of the damage measures. Only noncomposite action of a girder appears to be consistently detectable showing significant changes in all four damage measures.
Streicker Bridge: The Impact of Monitoring on Decision Making
Bridge managers often make decisions based on experience or common sense, somehow regardless of the action suggested by instrumental monitoring systems. Managers weigh differently the monitoring results based on their prior perception of the state of the structure and make decisions keeping in mind the possible effects of the action they can undertake. We propose a rational framework to include the impact of these issues on decision making, based on the concept of Value of Information. The methodology is demonstrated through the case study of the Streicker Bridge, a newly built pedestrian bridge on Princeton University campus.
Advanced Sensing, Degradation Detection, Diagnostic and Prognostic Capabilities for Structural Health Management
Analatom is developing a Structural Health Monitoring (SHM) system which provides both corrosion and strain measurements. This combination of data provides critical assessment of structural health, leading to prediction of failure. The SHM systemâ€™s sensors can be permanently installed in high value structures, such as buildings, bridges, or aircraft, and are connected to data acquisition nodes where initial processing is performed. From the nodes, processed data is transmitted using a ZigBee/IEEE 802.15.4 compliant low-power, self-organizing, self-healing wireless network to a central PC hub for analysis and interpretation. Analatomâ€™s Î¼LPR corrosion sensors have been installed on a mock-up bridge cable at Columbia University as part of a large project on development of a corrosion monitoring system for main cables of suspension bridges. The sensors were placed inside a full-scale mock-up suspension bridge cable located in an environmentally controlled chamber subjected to accelerated corrosion conditions for one year. The Î¼LPR sensors recorded corrosion rate measurement at 8 different locations inside the cable showing excellent agreement with temperature measurements.
Acousto-Optic Measurements in CFRP Laminates Using Fiber Bragg Grating Sensors
In light of ongoing efforts to reduce weight but maintain durability, designers have examined the use of carbon composite materials for a number of aerospace and civil structures. Along with this research has been the study of determining reliable sensing and monitoring capabilities to avoid catastrophic failure. Fiber Bragg Grating (FBG) sensors are known to carry several advantages in this area one of which is their proven ability to detect acoustic emission (AE) lamb waves in composite structures. AE is produced in these materials by failure mechanisms such as resin cracking, fiber debonding, fiber pullout and fiber breakage. With such activity there is a noticeable change in Felicity Ratio (FR) in relation to the increase of accumulated damage. FR is obtained directly from the ratio of the stress level at the onset of significant emission and the maximum prior stress at the same AE level. The main objective of this paper is to describe the results of an acousto-optic experiment using FBG sensors and present FR as a potential way of determining accumulated damage in a carbon composite structure.
Uncertainties in Damage Identification and Lifetime Functions of Ageing Concrete Structures1871
Safety and usability of existing concrete structures actually depend on the level of degradation and obsolescence due to ageing. Performance-based approaches to infrastructure management have been recently defined in terms of life-cycle-cost optimization. Lifetime functions for concrete structures can be constructed from theoretical/experimental models and, if a Structural Health Monitoring system is installed on the structure, at any required time, lifetime functions can be updated by employing a damage identification process to the data obtained from the SHM system. With reference to a real case of permanent static monitoring systems, the paper is aimed at discussing the influence of the uncertainties affecting the damage identification process on the lifetime function representing the resistance versus time of reinforced concrete beams. Based on real data, the performance estimate of the damage detection algorithms through the Receiver Operating Characteristic (ROC) curve is discussed and the probabilities of damage detection and false alarms are also formulated in terms of a Bayesian model.
A Multi-Non-Linear Civil SHM Model for Decision Support
Civil engineering structures are characterized by numerous non-linearities that make damage detection with subsequent structural health monitoring difficult. Within the large European Research Project IRIS, a generic risk based model has been developed allowing establishing proper decision support for infrastructure owners. The presentation aims to explain the new risk paradigm and the contained non-linear approaches. Examples from various demonstration cases will be shown. The technology has been demonstrated at the following structures: Â· S101 bridge in Austria with subsequent progressive damage test Â· Donaukanal-bridges, Vienna Â· Safepipes-Mockup at MPA Stuttgart An international harmonization drive is underway to allow comparison of the various methodologies.
Hybrid Coherent/Incoherent Beam Forming Diagnostic Approach to Naval Assets
This paper presents a hybrid diagnostic algorithm that leverages a novel piezoelectric-based damage-localization method using ultrasonic waves. The goal of the present research was to monitor a Navy established â€œchallenge problemâ€â€”a large (1.8 x 0.9 m) aluminum plate with several geometric features such as cutouts and bolted doublers, which tend to confound most guided wave methods. The algorithms used were a hybrid collection of functions making use of both coherent and incoherent information in the data. Data for each sensor is processed separately, then ultimately summed in a weighted fashion across the test structure. Further logic is also deployed to eliminate anomalies and invalid features. Generally, this process is analogous to active sonar. Damage ("targets") are detected and/or localized by generating ultrasonic elastic waves and observing how they bounce off of potential targets. Because a test structure is arguably far more complex than the open ocean, producing potentially far more "false targets", this approach takes advantage of embedding probabilistic models into the wave propagation/scattering process so that likelihood-based judgments can be made about the damage targets. These judgments may be understood in appropriate performance termsâ€”probability of detection, probability of localization, etc.â€” which directly supports the uncertainty quantification needed for decision-making.
Research on Software Platform of Bridge Health Monitoring System Based on JAVA EE and Scientific Computing Engine
By combining Java EE with MATLAB featured products together, new software architecture for bridge health monitoring system (BHM) is proposed, which aims to implement the real-time analysis of data collected by the BHM on the internet and solve the related engineering structure health status evaluation and disease diagnosis problems at the same time. Servlet based web applications or software components are developed and deployed in the web server tier, which composed the interface to response to the userâ€™s various scientific computing requests and display the retrieved results. MATLAB Component Runtime (MCR) acts as a core application server, with responsibility for the scientific computing engine. By using MATLAB Builder JA, all scientific algorithms can be develop in MATLAB M-functions and built to a standalone java class or methods of a certain java class. These java classes are docked into well organized java class collections which cover all need of data analysis and structural diagnosis computing tasks. Practice indicates, by using of this proposed bridge health monitoring system software architecture, both the powerful MATLAB scientific computing ability and the superiority of the network platform based on Java EE are implemented and cooperated in same system, the scientific computing engine are seamless combined into B/S software platform. The more attractive merit is that the proposed techniques build a gapless cooperative environment for civil engineers, network system engineers, and web page designers.
Development and Performance Quantification of an Ultrasonic Structural Health Monitoring System for Monitoring Fatigue Cracks on a Complex Aircraft Structure
Aircraft structural components may have known â€œhot spotsâ€ where any initial damage is anticipated to occur or has consistently been observed in the field. Automated inspection of these areas, or hot spot monitoring, may offer significant time and cost savings for aircraft maintainers, particularly when the hot spots exist in areas that are difficult to access or where traditional NDE inspection methods will not work. This paper discusses the development of a hot spot monitoring system for a metallic lug component using ultrasonic elastic waves generated by piezoceramic elements. The development process utilizes a formal SHM system design framework developed by Boeing and AFRL and uses a multi-step approach progressing from simple coupon tests to the full scale component for system validation. A Probability of Detection (POD) approach is being developed to quantify the performance of the SHM system based on the selected operation scenario and demonstrate the capability relative to current Aircraft Structural Integrity Program (ASIP) requirements. Further POD verification and validation plans to address system reliability and operational conditions are discussed.
Hot-Spot Fatigue and Impact Damage Detection on a Helicopter Tailboom
Monitoring the health of aircraft components and identifying problems before they can affect airworthiness has been a long-term goal in aviation. Current maintenance procedures are performed on a conservative, calendar or usage-based schedule rather than condition-based. These scheduled maintenance practices are time-consuming, labor-intensive and expensive. Furthermore, as structures age, maintenance service frequency (often unscheduled) and costs increase while performance and availability decrease. A promising solution to these issues is the application and integration of Condition Based Maintenance (CBM) and Structural Health Monitoring (SHM) technologies and processes. To enable more efficient and effective airframe maintenance, fatigue cracking and impact damage detection technologies were developed and demonstrated on a commercial tailboom. This paper discusses the application of SMART Layer technology to detect damage caused by cyclic loads and ballistic impact on the tailboom. The damage locations and sizes were compared with the computed values from the SHM system.
Damage Identification in Structural Components Using Vibration and Wave Propagation Data. 1915
Two general approaches are being considered in an effort to develop an effective structural health monitoring system for composite structural components with relatively complex geometries. One is the global approach, which measures and analyzes frequency response functions (FRF) for damage-induced changes in the vibrational properties. The other is a local approach whereby changes in the characteristics of ultrasonic guided waves propagating across existing defects or created by emerging defects are measured and analyzed. Improved ultrasonic and vibration test setups, consisting of either distributed high-fidelity piezoelectric sensor arrays or laser vibrometer, data acquisition boards, signal conditioning and dedicated software have been implemented. A damage index is used to calculate the changes in fundamental physical parameters from the measured signals at a number of control points from two different states of the structure. In the global approach, either changes in FRF amplitude or curvature is used to define DI due to its sensitivity to the appearance of damage, whereas, in the local approach the changes in the energy content of the transient signals is used to calculate DI. Examples of low velocity impact damage are considered in composite structural components with relatively complex geometries. It is found that the damage indices are pronounced at the control points closer to the damage locations and that the DI increases with the severity of damage. A baseline free damage detection technique using wave propagation data is also developed as a potential alternative.
Damage Detection Techniques in Composite Structures Using Ultrasonic Guided Waves
In this paper a theoretical base required for the development of a reliable structural health monitoring system based on ultrasonic guided waves is considered. An exact theory is used for relatively rapid calculation of the PZT driven surface motion in a plate recorded in an ultrasonic experiment. The theoretical results are compared with those obtained from an explicit finite element code for their mutual verification, showing excellent agreement. Important characteristics of the ultrasonic signals recorded by the PZT patches in an experiment are carefully extracted and modeled to identify the behavior of the PZT patches used in the experiment. Some applications are presented mainly concerning composite plates subjected to low velocity impact damage or more general hidden defects. Finally an application to the beam forming technique is presented.
Reference-Free Structural Health Monitoring for Detecting Delamination in Composite Plates
This paper presents a new methodology that allows detection of delamination in a single wave propagation path without using prior baseline data or a predetermined decision boundary. This study shows that, if delamination exists along a wave propagation path, the first arrival anti-symmetric mode (A0) is followed by another A0 mode reflected off from the â€œinsideâ€ delamination. Unlike other conventional techniques, the proposed technique takes advantage of this A0 mode reflected off from the inside delamination to instantly detect the existence of delamination. First, Lamb wave signals are measured in a pitch-catch mode using a dual PZT composed of concentric ring and disk PZTs for excitation and two circular PZTs for sensing. Here, the dual PZT actuator is used to extract only the A0 mode at any desired driving frequency. Then, the response time signals are measured by the two circular PZTs, and the damage sensitive feature, which is the A0 mode reflected off from the delamination, is extracted. Because the proposed technique does not require baseline signals during the entire delamination detection process, it has been demonstrated that robust delamination detection can be achieved even under varying temperature conditions.
Ultrasonic Guided Wave SHM for Probabilistic Fatigue Crack Growth Prognostics
Ultrasonic guided waves are used to characterize the size of a fatigue crack growing from a fastener hole in a plate structure based on a transmission coefficient ratio. The measurement uses the S0 Lamb wave mode and two wave paths from a single transmitter; a test path that is partially obstructed by the hole, and a reference path that is effectively unaltered by fatigue crack growth. Thus, three piezoelectric disk transducers are employed. Results from four specimens are presented, and with the help of uncertainty modeling described in a companion paper, the bounds on predicted remaining useful life are determined.
Guided Wave Based SHM Approach Using SAFT-Algorithm for Impact Detection in Composite Materials
This work investigates the interaction of guided waves with low-velocity impact damage in carbon fibre reinforced plastics (CFRP) which are widely used in aerospace applications. The interaction of guided-waves with impact induced damage was already shown [1-2], but the defect localization is quite difficult because of anisotropic material behavior [3]. An adapted synthetic aperture focusing technique (SAFT) was used for defect localization in such anisotropic materials. In order to utilize the technique for composite materials the wave velocities have to be known. The velocities of different wave modes in CFRPs vary with frequency, mode order and the propagation angle. They can be computed from the stiffness coefficients of the material solving equation of motion for anisotropic case [4] or by the conduction of pitch catch or laservibrometric measurements and the subsequent computation of the angle dependent propagation velocities. This paper shows examples for both the theoretical and experimental approach to obtain the lamb wave propagation velocities. In the experimental work, the velocity data obtained while using laservibrometric measurements are used by the localization algorithm. Therefor an anisotropic CFRP-plate was equipped with a network of distributed piezo disc transducers. Then a low velocity impact was introduced into the structure. The successful imaging of this damage will be demonstrated.
Baseline-Free Crack Detection in Nuclear Power Plants
This paper presents a new methodology that allows instantaneous detection of structural defects in pipeline structures without using prior baseline data. The proposed technique is based on the fact that the multiple identical guided wave paths can exist in the cylindrical structures due to the axisymmetric geometry. This study instantaneously detected structural defects in the cylindrical specimen from the differences of multiple guided wave signals, which show axisymmetric geometry. For guided wave generation, four transducers were attached along the circumference of the cylinder with equal spacing at a certain axial location. For guided wave sensing, another four transducers were attached in the same way at the difference axial location. Each pair of transducer is used for guided wave generation and sensing in a pitch-andcatch manner. Since the wave propagation paths with different axisymmetric geometry have the different pitch-and-catch distance, all of measured signals can be grouped accordingly. When the test specimen is intact, all signals in each group will have almost similar waveforms. However, if any structural defect exists along the wave propagation path, the multiple response signals with the same pitch-and-catch distance show some discrepancy. Since the proposed technique does not require baseline signals in the whole process, it has been demonstrated that robust damage detection can be achieved even under varying temperature conditions.
Strain Monitoring and Damage Detection of Single-Lap Joint with Embedded FBGs
The use of adhesive bonding in composites is recently increasing because it has advantages over mechanically fastened joints, such as less sources of stress concentrations, more uniform distribution of load and better fatigue properties. Understanding the behavior of the adhesive joint is required for improving the reliability of a structure with bonding joints. We have developed the distributed strain measurement system based on optical frequency domain reflectometry (OFDR) system. It can measure a strain distribution with the high spatial resolution at an arbitrary position along long-length fiber Bragg grating (FBG) sensors. In this study, we embedded the long-length FBG sensors into the adhesive of a single-lap joint. We could successfully measure the strain distribution at the interface between the adhesive and the adherend in the tensile test. We could also detect damage of the adhesive joint.
Health Monitoring of Composite Structures Using Carbon Nanotube and Acoustic Sensors
Matrix-dominated damage initiation has a major impact on fiber composite performance and durability. Detection of the onset and evolution of this damage has wide practical implications for the life prediction of composite structures. The formation of a percolating network of carbon nanotube sensors in the polymer matrix at low nanotube volume fraction is minimally invasive and does not require complicated sensing equipment. In order to evaluate the damage accumulation in the cross-ply laminates using the carbon nanotube networks formed in the polymer matrix, incremental cyclic loading accompanied by real-time measurement of electrical property changes and microscopic edge replication has been conducted. In addition, simultaneous acoustic characterization was conducted using both the SMART Layer and carbon nanotube-based sensing approaches. The carbon nanotube monitoring system was able to detect both microcracks and localized damage/delamination in composite structures with very high sensitivity. The piezoelectric sensor based SMART Layer technique could complement and leverage the carbon nanotube system with accurate damage location and size.
Acousto-Ultrasonic In Situ Monitoring of Fatigue Cracking in an Aircraft Wing Skin Specimen
The concept of in situ Structural Health Monitoring (iSHM) involves incorporating a diagnostic capability to detect and monitor damage in structural â€˜hot spotsâ€™. These systems allow the introduction of Condition Based Monitoring (CBM) approaches for ageing aircraft fleets and thus could help significantly reduce through-life support costs and increase aircraft availability. The Australian Defence Science and Technology Organisation (DSTO) has a program of work aimed at developing autonomous, robust, reliable iSHM systems with the specific aim of retro-fitment to existing aircraft. A current laboratory demonstrator of the technology is focused on the application of an acousto-ultrasonic (AU)-based iSHM system for monitoring fatigue cracks on generic structurally-detailed lower wing skin (LWS) panel specimens. This particular scenario, which simulates the LWS on an F-111C aircraft, is considered an ideal developmental platform and springboard for future iSHM applications, since it captures a number of key issues that AU-based iSHM systems need to address to ensure robust reliable diagnostics, viz., complex structural geometry, crack closure and high operational loads. This paper describes the design, application and assessment of an AU-based iSHM system to detect and monitor growth of fatigue cracking in the generic complexgeometry LWS panel specimens subject to representative spectrum loading. Its performance is discussed and compared to measurements furnished by thermoelastic stress analysis and visual observation. Testing associated with this complex realistic panel specimen revealed several deficiencies in the design of the iSHM system.
Crack Detection Using Combinations of Acoustic Emission and Guided Wave Signals from Bonded Piezoelectric Transducers
Piezoelectric transducers are broadband devices and can operate over a large frequency range. In structural health monitoring (SHM) applications, piezoelectric transducers are commonly operated at ultrasonic frequencies to excite and sense guided waves, detect acoustic emission (AE) events, and record electro-mechanical impedance (EMI). The transducers can also measure lower frequency information, such as strains resulting from operational loads or vibrations due to environmental factors. This paper presents a crack detection experiment using piezoelectric transducers to provide signals measuring guided waves, AE events, EMI, and strain. The experimental test articles are aluminum dogbone coupons. Each coupon has a small hole drilled in the gage section to serve as a crack initiation point. Each coupon is instrumented with two transducers, both on the same face of the coupon and on either side of the gage section. Each coupon undergoes cyclic tensile loading to initiate and grow fatigue cracks. At various intervals, the fatigue cycling is paused and the coupon is visually inspected for crack initiation and growth. While the cycling is paused, guided waves are generated and sensed by the pair of transducers; each being used in turn as a transmitter or receiver. In addition, EMI measurements at each transducer are made with the cycling paused. Ideally, AE and strain measurements would be made continuously during the cycling. However, for these studies the available hardware did not allow continuous collection of data. As a result, the AE and strain measurements also are taken over limited time segments while the primary fatigue cycling is paused. Collection of data for the various sensing modes continues as the crack grows to the point of coupon fracture. Baseline crack detection performance is established using statistical pattern recognition methods applied to the guided wave data. Additional crack detection algorithms are designed and evaluated to demonstrate the potential benefits of using decision fusion methods applied to combinations of guided wave and AE data. Artificial AE data has been utilized since the current testing hardware did not allow for the collection of useful AE data. Future studies will address the collection of AE data and consider data fusion incorporating EMI and/or strain data.
Autonomous Structural Condition Monitoring Based on Dynamic Code Migration and Cooperative Information Processing in Wireless Sensor Networks
Wireless sensor networks have emerged in recent years as a viable alternative substituting conventional, tethered systems for structural health monitoring. Because of the limited internal resources of wireless sensor nodes, new and innovative concepts are needed to implement resource-efficient operation for reliable monitoring. This study explores the use of dynamic code migration and automated, cooperative information processing as a means to achieve resource efficiency and system reliability. Autonomous software agents are installed on the sensor nodes continuously executing simple resource-efficient routines to locally process the data sets measured from the structure. Upon the detection of potential anomalies in the data sets, specialized agents are physically migrating to the relevant sensor nodes to perform more complex â€“ and resource-consuming â€“ algorithms in order to analyze the local sensor data. Furthermore, a central information pool, used by the software agents and continuously being updated, is introduced to assess the system behavior. This paper presents a prototype system which demonstrates the implementation of dynamic code migration and cooperative information processing for autonomous condition monitoring.
An Intelligent Wireless Structural Health Monitoring Solution
Upon arriving at an incident site in the wake of a terrorist attack or a natural disaster, structures specialists from FEMAâ€™s Urban Search and Rescue (US&R) program are tasked with ensuring the structural stability of partially collapsed buildings. Successful building stabilization limits the risk to first responders as they strive to find and remove trapped victims, so it is vitally important that these specialists know immediately when changes occur within a structural system. To enhance the effectiveness of current search and rescue methods while offering first responders a safer operational environment, low-cost wireless sensors can be used to provide real-time structural health monitoring (SHM) data that speaks to the current condition and stability of a partially collapsed structure. In this paper, a new wireless solution is proposed for US&Râ€™s structural specialists. The architectural design of this wireless system is decomposed into two functional layers. The first layer consists of ultra low-power wireless sensors and is used to physically sense the behavior of the monitored structure and track the location of any first responders working within. The second layer contains more sophisticated wireless nodes that make automated decisions about the health of the damaged structure and relay this information to the relevant decision makers. The resulting system represents a low-cost, low-power, easy to deploy SHM solution for US&R. In addition to supporting an array of application-specific sensing transducers, this system transmits processed SHM information directly to trained structures specialists. Additionally, this system integrates an energy-aware multi-hop forwarding mechanism to maximize the lifetime of the monitoring system as a whole and utilizes routing and information coding techniques that are robust to node and/or communication failures, sudden changes in device position or configuration, etc.
Towards Low-Cost Structural Health Monitoring with Sensor Networks in Earthquake Damage Detection
Damage assessment in structural health monitoring (SHM) requires accurate acceleration data collected in real time. The recording systems for earthquake acceleration usually collect data at a sampling rate of 200 sps (samplings per sec) or higher in high resolution and high sensitivity using expensive devices. Wireless sensor network (WSN), on the other hand, has a potential capability to monitor damage conditions in a disaster by low cost. However, WSN would be faced with difficulty in collecting data at a high sampling rate due to restricted CPU power with batteries. This paper presents an acceptable reduction scheme of the sampling rate, and discusses effectiveness of WSN for SHM. We analyzed the acceleration data of the previous earthquake by cumulative distribution function (CDF) in the frequency domain.
Novel Optical-Fiber-Based Cure Monitoring Technique for Large-Scale Composite Structures by Hybrid Brillouin-Rayleigh System
Carbon fiber reinforced plastics (CFRP) have high specific strength and stiffness and have been used extensively in many industrial fields. Especially in a field of aircraft, their application extends to primary structures. Therefore, quality assurance of the composite materials is necessary and effective cure monitoring techniques of composite materials are becoming more and more important since quality of the materials is very dependent on their cure processes. Optical-fiber-based distributed sensing system is considered very useful for cure monitoring of composite structures due to their outstanding properties. Since they are light weight and small, they do not affect mechanical properties of composites in which optical fibers are embedded. However, since both strain and temperature changes affect outputs of the sensing systems, they cannot separate strain and temperature contributions. In order to overcome this limitation, a newly developed hybrid Brillouin-Rayleigh system is considered to be quite useful. This study demonstrates a new effective cure monitoring technique by applying the hybrid system to composite materials. One optical fiber for the system, an FBG sensor and a thermocouple were embedded in a CFRP specimen to measure thermal residual strain and temperature change in a cooling down period of cure process. The temperature and residual strain obtained by the hybrid system agreed well with the results by the FBG sensor and the thermocouple, confirming that the proposed cure monitoring technique is quite useful for separated strain/temperature measurements of composite materials. By applying the proposed technique to actual composite products, quality assurance for whole parts can be effectively accomplished.
Wireless Sensor Network for Guided Wave Propagation with Piezoelectric Transducers
Guided waves are widely used for structural health monitoring (SHM) applications especially for the observing of width structures. For exciting guided waves into structures piezoelectric transducers are common used. But for an effective observing of structures a network of piezoelectric transducers is needed and normally the connection between the different transducers is done with wires. For short distances between the nodes (e.g. 5 to 10 cm) this works well, but for longer distances the influence of the cables capacitance is quiet high. Also the more on weight is a drawback of wired sensor networks. Because of the above mentioned disadvantages of such wired sensor networks, researchers developed wireless sensor network systems for SHM. In this paper we present a wireless sensor network system which is designed for SHM application with piezoelectric transducers and guided waves. First, the different hardware components of the wireless sensor network system are described in detail. The hardware mainly consists of a PC connected via USB hub which remotely controls wireless the actuator â€“ sensor nodes. Each node in the sensor network can be used as actuator with an excitation voltage of about 60 V peak-to-peak, as well as sensor with a variable amplification to measure signals in the range between 0.5 and 100 mV. The frequency range covers 30 â€“ 300 kHz. Powered by the integrated battery, the nodes operate completely autonomously. The main novelty of this system is its simple handling because of the Graphical User Interface (GUI). The GUI enables the choice between the actuator or sensor mode for each device in few seconds. Also the number of active nodes in the network (up to 8 nodes) or the excitation frequency can be selected by a mouse click. After every measurement cycle the measured data from each sensor node is diagramed on the screen. Finally, the paper presents a laboratory test on an aluminum/foam sandwich plate with a removable artificial defect to accurately assess the performance merits and weaknesses of the integrated hardware and software.
Architecture of a Remote Impedance-Based Structural Health Monitoring System Used in Aircrafts
The essence of structural health monitoring (SHM) is to develop systems based on nondestructive inspection (NDI) technologies for continuous monitoring, inspection and detection of structural damages. The electromechanical impedance (EMI) method has been regarded as a promising tool for SHM. In this article, a new architecture of a remote SHM system based on electromechanical impedance measures is described. The proposed environment is employed to automatically monitor the structural integrity of aircrafts and is composed by sensor networks, signal conditioning and acquisition hardware, and a data processing system.
Implementation of a Receptance-Based SHM Algorithm on Wireless Smart Sensors
Wireless smart sensors (WSS) have been drawn significant attention for structural health monitoring (SHM) in recent decade. A number of smart sensor platforms have been developed for SHM purposes; however, not many software or embedded processing strategy has been implemented for structural damage detection. In this paper, a receptance-based damage detection algorithm based on the stochastic dynamic damage locating vector method is implemented on Imote2 wireless smart sensor platform based on the Illinois SHM Services Toolsuite. The damage detection module is then combined into comprehensive damage detection software including data measurement, system identification, and damage detection for decentralized wireless sensor platform. The software with Imote2 is experimentally validated on a lab-scale bridge structure.
Distributed Optical Fiber Smart Sensors for Structural Health Monitoring
In general, Structural Health Monitoring (SHM) can utilize either distributed smart sensors, or multiplexed optical fiber sensors. We demonstrate the implementation of Distributed Optical Fiber Smart Sensors (DOFSS) for SHM. That is, the distribution of both intelligence and sensors in an optical fiber based sensor network. Optical fibers offer advantages that make them highly desirable as sensors, the most important for SHM being versatility. For example, Fiber Bragg Gratings (FBGs) can be used to detect acoustic emissions, actively generated acoustoultrasonic signals, dynamic strain (e.g. vibration), static strain (e.g. load monitoring), etc. multiplexing is seen as the primary advantage of FBGs, enabling large numbers of sensors (1000), to be connected together. However, multiplexing of FBG sensors uses a single transmitter, receiver, processor, and fiber length. To ensure that a SHM system is robust, these components along with the sensors need to be distributed. This goes towards achieving NASAâ€™s goal of robust or ageless aerospace vehicles. To achieve this, we have developed a Smart Transducer Interface Module (STIM) which can be linked together giving a DOFSS network. The distribution of intelligence around the structure means that communications and power for the network are a significant consideration. Since optical fiber will be utilized for the sensing, then these â€œwiredâ€ links, can be utilized for the distribution of communications and power, using WDM to combine the signals together.
Deformation Monitoring of Shield Tunnel Based on Distributed Optical Fiber Strain Sensing Technology
n this paper, a deformation monitoring method for shield tunnel based on distributed optical fiber strain sensing technology is addressed. Firstly, a novel distributed optical fiber strain sensing technology based on pulse-pre-pump Brillouin Optical Time Domain Analysis (PPP-BOTDA) was introduced, including the packaging process and deployment methods of corresponding optical fiber sensors. Then, the relationship between structural distributed strain and longitudinal settlement was deduced based on the longitudinal equivalent continuous model of shield tunnel. Finally, a model experiment of Nanjing Yangtze River Tunnel was conducted to study the longitudinal deformation property of tunnel under locally even loads with the distributed optical fiber sensors. Experimental results show that the distributed strain measurement can reflect distribution of tunnelâ€™s longitudinal deformation, based on which, the structure damage can be detected precisely. It is also shown that the tunnelâ€™s longitudinal settlements derived by the proposed method agree well with those measured directly with the traditional displacement meters. Efficiency of this method is thus validated.
Efficient Guided Wave SHM Baseline Capture and Selection
Guided wave structural health monitoring is generally accomplished using baseline subtraction. This typically takes the form of acquiring a large baseline set over a long period to capture all conditions the structure will experience. In the case of many structures this range is unknown or it is simply impractical to collect a baseline set before use. The requirement for many baselines is complicated by the time that may be required to capture an individual baseline. This paper addresses these problems from two directions. Firstly by altering the physical data capture method the time taken to acquire signals can be reduced by an order of magnitude. Using a coded excitation signal, specifically a chirp, does this. This signal puts in more energy to the structure in line with the length of the chirp. In doing this, the effect on signal to random noise is the same as performing a greater number of averages. Thus the same performance can be achieved with a single firing rather than the use of multiple averages. To address the problem of acquiring a relevant baseline set to correct for environmental changes a method is proposed to add baselines to a data set based on their difference to any previously acquired dataset. This has the effect of adding a recorded value to the dataset if the value has changed more than some specified minimum difference. In doing this the baseline set grows rapidly initially but as the set covers the conditions the structure is exposed to this rate slows. It is shown that this approach can be used to develop a baseline set online without defining it before operation. In addition it is shown that this does not affect the ability to detect a damage event.
Use of Carbon Nanotubes for Strain Sensing of Epoxy Based Composites
The interest in structural health monitoring of carbon fiber reinforced polymers using electrical methods to detect damage in structures is growing because of its simplicity and feasibility. In order to get conductivity, polymer matrix must be turned conductive and the use of nanoreinforcement seems to be the most feasible method. In this work the behavior of nanoreinforced polymer with carbon nanotubes (CNTs) and composites with glass and carbon fibers with nanoreinforced matrices has been studied. These composites have been evaluated in tensile test by simultaneously measuring stress, strain and resistivity. During elastic deformation, a linear increase in resistance was observed and during fracture of the composite fibers stronger and discontinuous changes in the resistivity were observed. The percentage of nanotubes incorporated in the matrix has turned out to be an important factor in the sensitivity of the method.
Wireless Links for Global Positioning System Receivers
This paper deals with the application of wireless transmission technology to longterm monitoring GPS (Global Positioning System) receivers. They consist of five parts: antenna, receiver, user client computer, interface and power supply. The antenna is mounted on the structure to be monitored and is connected with the receiver by a coaxial-cable through which the radio frequency signals are transmited. The receiver unit acquires, tracks and demodulates the satellite signals and provides, through an interface made wireless, the resulting GPS raw data to the user client computer for being futher processed by a suitable positioning algorithm. The power supply reaches the computer by a wired link, while the other modules rely on batteries.
Automatic Wireless Transfer of Acquired Usage Monitoring Data
There is significant industry interest in automated wireless â€˜pushâ€™ of acquired flight data to a centralized database as it has value in a number of different applications, from flight safety monitoring (e.g. FOQA) applications to usage monitoring for Condition Based Maintenance (CBM). This paper looks at the requirements for transferring acquired flight data via a wireless link to the internet and on to a server housing a centralized database. The candidate technologies for this wireless transfer are then evaluated against these requirements with a view to identifying an optimum solution for realizing the automated wireless upload.
Sandwich Node Architecture for Task Preemption in Wireless Sensor Networks for Structural Health Monitoring Applications
In recent years, several hardware platforms of wireless sensor networks (WSN) have been developed and used for structural monitoring applications [1,2]. A typical design of a node includes a sensor board and a mote connected to it. Sensing units, analog filters and analog-to-digital converters (ADCs) are integrated on the sensor board and the mote consists of a microcontroller and a wireless transceiver. A WSN system based on this node lacks the capability of interrupting its scheduled task to start a higher priority task. This shortcoming is rooted in the hardware architecture of the node. The proposed sandwich-node architecture is designed to remedy the shortcomings of the existing one for task preemption. A prototype has been implemented using Imote2 and verified by an emulation in which one mote is triggered by a remote base station and then preempts the running task at the other mote for handling an emergency event.
Small Battery-Free Wireless Sensor Networks for Structural Health Monitoring
Battery-free wireless sensors developed at the University of Maine under a cooperative agreement with NASA enable a myriad of structural health monitoring (SHM) applications. Embedding these sensors in structures without the need for changing batteries, their rugged design to withstand harsh environments, and coded communication with multiple access features makes this new technology a desirable candidate for a variety of aerospace and civil infrastructure monitoring applications. This paper presents sensor characteristics, communication schemes, and multi tier networking strategies developed to deliver a reliable wireless sensor system for SHM. A large scale inflatable lunar habitat structure built by NASA and instrumented by UMaine is used as test-bed for technology demonstration. Various aspects of this system have been studied and results are published in conferences and journals as presented in the references section. These aspects are summarized in this paper and include: distributed sensing and coding, throughput optimization, channel estimation error analysis, signal detection in presence of interference, two-tiered networking, turbo coding and decoding in distributed sensor networks, cooperative relaying methods, and impact localization. Testing the developed battery free sensors in lab environment with multi-path and interference effects resulted in 16 ft operation range with under 20 mW power. This range can be even extended further if a second tier with battery-operated sensors is added to the network. Noting that several passive sensors and only a few active sensors is required to build this multi-tier architecture, the cost savings in power combined with coding gain is significant compared to conventional sensor networks.
Military-Standard Sensor Nodes for the SmartBrick Structural Health Monitoring Platform
The SmartBrick platform is an autonomous, wireless, and robust solution for structural health monitoring of civil infrastructures. The base station is currently in its third generation and has been laboratory and field tested in the United States and Italy. The platform has been presented in our previous publications; the focus of this paper is on recent developments made with the objective of complying with military standards for hardware, software, and communication. Specifically, we discuss the design and implementation of the second generation military-standard wireless sensor node for the SmartBrick platform, to facilitate its use in military applications, where interoperability, robustness, and reliability are of paramount concern. Two major enhancements to the sensor nodes are described in this paper. The first improvement is migrating from the DSPIC30F series to the latest DSCPIC33F series of microcontrollers. The second major improvement to the sensor node is replacing the Texas Instrument CC2480 Zigbee transceiver module with the MRF24J40MA from Microchip. These improvements have resulted in significantly lower power consumption and a longer communication range. We articulate the details of hardware and software development of the sensor node that incorporates this chip. We also describe laboratory and field tests, including underwater tests, carried out for validation of reliable operation and performance of the system.
Fiber Optic Method for Buried Pipelines Health Assessment after Earthquake-Induced Ground Movement
Real-time, automatic or on-demand assessment of damage to pipelines after the earthquake is essential for early emergency response, efficient preparation of rescue plans, and mitigation of the disastrous consequences. This paper presents a method for buried pipelines health assessment based on distributed fiber optic sensors, which are sensitive to strain at every point along their lengths. For the method validation purposes a thirteen-meter long real-size concrete pipeline was tested. The sensors were both installed onto the pipeline and embedded in the soil, in proximity of the pipeline. Earthquake induced ground movement was simulated by an imposed displacement of the movable part of the basin and it induced the damage to the pipeline by crushing the joints between the pipe segments. The sensor installed on the pipe successfully detected and localized the damage at the joints. The sensor installed in the soil detected and localized the ground movement. The results of the test validated general principles of the method.
Decentralized Fault Detection in Wireless Sensor Networks
This paper introduces a model-free and reference-free decentralized sensor fault identification algorithm ideally suited for wireless sensor networks. Since wireless sensor networks (WSNs) are adopted in many large-scale applications, fault detection of sensors becomes an important subject, especially for low-cost nodes. The common energy-limited characteristic of WSNs, however, makes centralized or complex fault detection algorithms unfavorable. We developed an energy efficient algorithm based on pair-wise comparison. The linear relationship between the outputs of sensor pairs is used to reveal the faulty sensors. The input of the system and knowledge of reference sensors are not required for this method. We also present how to pair sensors in order to minimize power consumption. The performance and limitations of the algorithm are discussed and verified by simulations. Results show that even when error power is comparable to the output signal power and the observation noise level is high, the algorithm is still able to detect most of the faults. Moreover, the decentralized approach reduces the power consumption of the WSN significantly when compared with the traditional centralized method.
Framework for Comparison Study of Stochastic Modal Identification Considering Accuracy and Efficiency
This paper presents a framework to compare the performance of the system identification methods by investigating the accuracy of the identified results and efficiency of the methods represented by computational costs. The successful identification reproduces the given structural system using accurate modal parameters with minimizing noise effect with the least computational cost. The accuracy of the algorithm is estimated through the distribution of identified modal parameters corresponding to the size of the transition state matrix instead of calculating errors compared to the exact values due to the insufficient information about modal parameters in a physical structure. Three modal parameters, vibration frequencies, damping ratios, and mode shapes, equally contribute to quantify the accuracy of the algorithm. As a measure of efficiency, two computational cost measures, number of operations and computational time in a single loop of each algorithm, are considered together to complement each other. Application of the framework for comparison study is performed for the acceleration data from the Riverton-Belvidere Bridge over the Delaware River. A Wireless Sensor Network (WSN) is implemented to acquire the response of the bridge due to ambient excitations. A total of eight sensor nodes are installed on the main span of the bridge, measuring the vertical and transverse accelerations. Based on the deployment of sensors, four sensors on each side, the system identification of the bridge is possible for vertical, torsional, and transverse modes. Four stochastic modal identification methods, including Eigensystem Realization Algorithm (ERA)-Observer Kalman Filter Identification (OKID), ERA-Natural Excitation Technique (NExT), ERA-NExT-AVG, and Auto-Regressive (AR) models, are used to identify modal parameters of the bridge and examine the identified results. The estimates of structural modes for frequencies are up to 20 Hz for all investigated methods. The comparison study shows that the proposed framework is effective to estimate the performance of system identification method.
Automated System Identification and Validation of Numerical Models of Offshore Wind Turbines as Basis for SHM-Analysis
System identification by measured data is an important procedure, necessary for many applications within the field of structural health monitoring. The resulting modal properties can be used for model- validation and updating, load estimation and damage detection to name a few possibilities. An automated algorithm for identifying a structureâ€™s modal properties from dynamic response data (accelerations) using Auto- Regressive (AR) models is presented here. New parameters to estimate the ARmodelâ€™s order a priori and to extract the physical from the mathematical models are introduced. Furthermore, a tool for automated model validation using several iterative techniques is presented as well. The algorithms are applied to data from two offshore structures. System identification and model updating are accessible through a graphic user interface (GUI) based on MATLAB.
Novel Sensor Concept for Monitoring of Wind Turbine Blades
Development in wind turbine blade design has accelerated impressively over the past decade as rated output power has increased up to 6 MW today. State of the art turbine blades have reached dimensions up to 65 meters, which only seems to be limited in terms of transportation. For this reason, German manufacturer Enercon has started to build hybrid blades, made of both, a composite and a steel section which are fit together at the construction site. Still blade fabrication is hardly automized which can result in divergence of quality. Even though design standards have improved, damages due to fabrication inaccuracy still are present. Regarding the consequences of one blade failure, the average inspection and repair time must be estimated taking five days of down time [1]. Hence, the load carrying structure should be monitored in order to minimize costs of maintenance and repair and to extend lifetime. Today, there are only three products on the market other than visual inspection [7][8]. None of these products have been certified for reliable damage detection. For this purpose an automated blade monitoring system for early damage detection is currently developed. It is based on an approach using the proportionality of maximum dynamic stress and maximum vibration velocity related to the first bending modes, in the edge- and flapwise direction. This approach already could be proven to indicate starting damage much earlier than a change in eigenfrequency. Both numerical calculations and laboratory testing could reveal that dependent on the location where damage occurs, the proportionality method can show tremendous changes compared to the initial level [6]. A smart technical platform is supplied by the project partner HBM, offering sensor technology fully orientated on the challenging environment of a turbine blade. Quickly changing climate conditions combined with a high risk of lightning strike which mostly is affecting the entire measurement system have been included into the development of a new deflection sensor which is absolutely immune to the influences mentioned.
Laboratory Validation of MEMS-Based Sensors for Post-Earthquake Damage Assessment
The EU-funded MEMSCON project aims to produce small size sensing nodes for measurement of strain and acceleration. These integrate Micro-Electro- Mechanical Systems (MEMS) based sensors and Radio Frequency Identification (RFID) tags in a single package; which can be incorporated in reinforced concrete buildings and can transmit data using a wireless interface. During the first phase of the project, sensor prototypes were produced by assembling preexisting components. In the second phase we developed miniaturized MEMS prototypes fulfilling the target application requirements. This paper outlines the accelerometer operating principles and the sensor architecture, and illustrates operation at both unit and network levels. It also reports on validation campaigns conducted in the laboratory to assess system performance.
Modal Identification of Steel Truss Bridges Using Wireless Sensor Network
Concerns regarding the functionality of existing infrastructure have motivated researchers to pursue efficient ways of structural health monitoring. Application of wireless sensor network (WSN) in health monitoring of infrastructure has presented exciting potentials in this area over the past few years. Using a WSN as a cost-efficient and easy to install tool, measurement of the dynamic response of infrastructure has become more convenient. Integrating the dynamic test of in-service bridge structures into their health monitoring provides considerable information about their global behavior which can help with their maintenance and management. A critical step toward the broad application of WSN in monitoring of infrastructure is their experimental validation. In this paper the deployment of wireless sensor networks (WSNs) on two different steel bridge structures is discussed. The responses of these bridges under their daily traffic and other ambient loads are measured and used for structural identification and evaluation of the bridge.
Challenges and Possibilities of WSN in the Dynamic Monitoring of Existent Structures
In the field of monitoring sensors, the progress of new technologies, such as wireless communications and Micro-Electro-Mechanical-Systems â€“ MEMS are of high interest as alternatives for the expensive and handle difficult wired-based sensors. The incorporation of these new technologies in the structural health monitoring and preservation of cultural heritage buildings would definitely represent a turning point of the testing techniques and experimental methodologies. This paper presents a detailed analysis of the Wireless Sensor Networks (WSNs) technology when used for carrying out dynamic monitoring studies in existent structures. For this purpose, commercial off-the-shelf (COTS) solutions as well as a new platform, especially developed in the University of Minho for performing operational modal analysis tests, were used in laboratory and real field tests. The results show that COTS systems are not accurate and reliable enough for these kinds of tests due to the low resolution of sensors, and ADCs embedded as well as the lack of implementation of communication protocols. On the other hand, the results of the new system evidenced high accurate time domain acquisitions which indicate precise estimations of the structural dynamic properties
Acoustic Emission Sensors Circular Array for Concrete Structure Damaging Source DOA Estimation
We designed circular Acoustic emission (AE) array (consisting of 8 element sensors uniformly spread over a circle of 12 cm) to detect internal structural damage from cracks propagating during the concrete. Uniform circular array acoustic emission array beamforming characteristics ( adaptive beamforming and conventional beamforing)were analyzed in simulation. Then the pencil break tests were carried on a concrete deck to discuss the AE array for damaging sources location performance. The concrete acoustic emission signal sources location was affected by the propagation mode characteristic and noise. The MVDR (Minimum varivance distortionless response) and multiple signal classification (MUSIC) methods are used to estimation circular array direction of arrival (DOA) performance. The experiment results show that the proposed method used in circular array improves the acoustic emission damaging sources location accuracy and gains good performance in limited area
Towards a Digital Image Correlation Based Strain Sensor
A need exists for a non-contact two-dimensional strain measurement system,which could provide information for field monitoring and greatly enhance theaccuracy of structural models through the development of larger data sets for model calibration. This paper introduces a potential technique for measuring displacement with a high degree of accuracy, which is required for a two-dimensional strain sensor, using relatively inexpensive digital cameras using the digital image correlation technique and a software package called GeoPIV. The basics of the digital image correlation technique are presented. The paper focuses on the importance of image texture in achieving accurate displacement measurements. As an illustration of this, compression tests on textured and untextured concrete cylinders are presented. Using a full displacement field analysis region, it was found that the cylinders with artificially added texture produced more accurate results than those without. These results are discussed to highlight the impact of image texture on the digital image correlation technique.
An Innovative Non-Contact ECG and Biopotential Sensor
This paper describes the development of a non-contact sensing platform to monitor the ECG and biopotential signals. The non-contact sensing will be based on capacitive coupling the bioelectricity produced by cardiovascular activities around the heart. High sensitivity sensor and electronics are designed to amplify the signals. Our preliminary study has pointed to the promise of this sensing concept. A sensor prototype was able to clearly detect the ECG signals from 10 cm away from the body. Research tasks continue improving the sensor design to detect the polarization in the ECG signals. The final goal is a non-contact sensing platform for ECG signals and for real time diagnostics of the mental distress and cardiovascular diseases.
Detection and Sizing of Subsurface Impedance Discontinuities Using Acoustic Wavefield Images
Consider a piezoelectric transducer that is attached to the back of a plate-like structure, such as is the case for guided wave structural health monitoring. This transducer may be excited to produce guided waves that propagate outward from the source through the structure. These waves interact with impedance discontinuities in the structure at defects, bond lines, plate boundaries, and other geometrical features. These propagating waves may be measured on the surface of the specimen using either a scanning laser vibrometer or a scanning air coupled transducer. When full wavefield data are obtained by recording complete waveforms on a spatial grid, these measurements contain a wealth of information that can be used for identification, localization and characterization of damage. Results are presented here from a study that uses full acoustic wavefield images of propagating guided waves to detect and size different defect types in aluminum plate specimens. Several detection and sizing algorithms have previously been considered, including frequency domain analysis, incident wave removal, and acoustic wave crest analysis. The acoustic wave crest analysis method, which was developed by the authors to study corrosion type defects in aluminum plates, is applied here to analyze wavefield interactions with fatigue cracks in an aluminum plate specimen. The methodology demonstrated here on aluminum plate specimens is appropriate for application to critical metallic structural components as part of an integrated health management system.
Terahertz Phonon Amplification and Sasing in Semiconductor Superlattice Structures2223
Sound amplification by teh stimulated emission of (acoustic) radiation, or saser, is the acousitc equivalent of laser.
An experiment was conducted to improve understanding of Lamb waves interacting with a T-joint on a plate fabricated from T-6061 aluminum for the purposes of structural health monitoring (SHM). The shape of the test article, similar to the orthogonality symbol (â”´), geometrically represents the complexity of many rib-like aircraft components. A small piezoceramic sensor, placed on the horizontal section of the structure, was used to generate Lamb waves at frequencies ranging from 100 to 300 kHz. A three-dimensional (3D) scanning laser Doppler vibrometer (LDV) system was used to measure the elastic wave interaction providing both in- and out-of-plane velocities. The scan grid, consisting of approximately 25,000 points at 1 mm spacing covered the front and back of the horizontal and vertical sections. The goal of this research was to measure how the wave's response to rapid changes in material thickness. Results clearly show the waves dividing into separate components as they travelled through the remaining sections of the structure and lower amplitude wave components reflecting back towards the sensor. A composite scan was also created by combining data from the top and bottom horizontal face of the structure to evaluate the symmetric and antisymmetric behavior of Lamb waves. Results shed light on the usefulness of Lamb wave investigative techniques in geometrically complex structures.
The Search for Optimal Sensor Network in Lamb Wave-based SHM Method
In this paper the investigation of a structural health monitoring method for thinwalled parts of structures is presented. The concept is based on the guided elastic wave propagation phenomena. This type of waves can be used in order to obtain information about structure condition and possibly damaged areas. Measurement of the wave field was realized using laser scanning vibrometer that registered the velocity responses at points belonging to a defined mesh. Determination of the optimal placement of sensors is a very challenging mission. In conducted investigation laser vibrometer was used to facilitate the task. The chosen mesh of measuring points was the basis for the investigation. The purpose was to consider arrays of piezoelectric sensors and find the optimal solution. Instead of using vast amount of piezoelectric sensors the earlier mentioned laser vibrometer was used to gather the necessary data from wave propagation. Sensors networks geometries were picked out from the measured points. Next, the signals gather by this non-contact method for the considered network were input to the damage detection algorithm. The results of damage detection for the selected networks were compared. The signal processing was conducted in MATLAB with the procedures developed by authors. Damage detection algorithm was based on a procedure that seeks in the signals the damage-reflected waves. Knowing the wave velocity in considered material the damage position can be estimated.
Experimental Studies of Structure Inspection and Damage Detection Based on Elastic Waves Energy Distribution2245
The paper presents an experimental study related to the inspection of an internal structure and damage detection in a tailplane of a helicopter. For this purpose guided elastic waves, excited by piezoelectric actuators, are used. Full field wave propagation measurements are carried out using Scanning Laser Doppler Vibrometer (SLDV). Presented approach is based on determining energy distribution of propagating waves. Created maps allow to investigate internal structure and localize the presumable damage.
Robust Vision-Based Approaches for Structural Health Monitoring
Automated health monitoring and maintenance of civil infrastructure systems is an active yet challenging area of research. Nondestructive evaluation techniques, including the use of optical instrumentation (e.g., digital cameras), image processing and computer vision are promising approaches for structural health monitoring to complement sensor-based approaches. This study applies and evaluates the underlying technical elements for the development of an integrated inspection tool that is based on the use of commercially available digital cameras. The proposed system can help an inspector to visually assess a target structure remotely, without the need of having to travel to the bridge site, and by bypassing needed traffic detouring. Also, a contact-less vision-based crack detection methodology is introduced and evaluated. Illustrative examples are provided to demonstrate the capabilities as well as the limitations of the proposed vision-based approaches
Visualization of Lamb Wave Interaction with a 5 mm Fatigue Crack using 1D Ultra High Frequency Laser Doppler Vibrometry
Elastic waves can travel across relatively large distances in thin metallic plates, and can be affected by discontinuities such as cracks. An important research area in guided wave SHM is the characterization of the lower limits of detectable damage and identification of measurement and signal processing techniques for reliable detection of damage at those limits. This paper presents the results of experimental measurements of Lamb waves collected using an ultra-high-frequency laser Doppler vibrometer (UHF-LDV). The two test articles were 3.175 mm thick aluminum plates with a small (1.59 mm) center hole added to facilitate growth of a fatigue crack. One plate was left undamaged while the second contained a 5 mm fatigue crack emanating from the hole. The UHF-LDV provides out-of-plane displacement measurements at a much greater temporal and spatial resolution than is possible with most other commercial LDV systems. Point spacing of approximately 0.5 mm was used in a 21 mm x 22 mm scan region centered on the hole and crack. PZT transducers were used to induce Lamb waves in the structure at frequencies from 400 to 600 kHz. The data show small but measureable differences in elastic wave propagation patterns between undamaged and damaged plates. Recommendations for additional analysis and future experiments are also provided.
Developing a Wireless Two-dimensional Image-based Crack Sensor for Concrete Structures
There is an increasing interest in assessing the health condition of Civil Infrastructure using wireless smart sensors network (WSSN) in recent years. The WSSN technology enables an evolutionary improvement of the mobility, cost efficiency and significantly reduction of installation effort by releasing the data acquisition system from extensive wiring, which benefits the development of localized monitoring such as crack propagation measurement. In this paper, the specification and the design of a new smart wireless two-dimensional crack sensor using image processing technique is presented. The sensor is able to measure two-dimensional crack propagation automatically which cannot be easily done by other crack sensors. In addition, the adoption of low-power microcontroller and wireless module simplifies the sensor installation and allows distributed monitoring strategy for sensor deployment on large scale civil structures. The progress of development, including hardware design, laboratory tests and computer simulation are presented in this paper.
Interaction of Lamb Waves with Fatigue Cracks in Aluminum
Elastic waves can travel across relatively large distances in thin metallic plates, and can be affected by discontinuities such as cracks. This paper presents an investigation of the interaction of Lamb waves with both open and closed low-cycle fatigue cracks in aluminum plates using a three-dimensional laser Doppler vibrometer (3D-LDV). The 3D-LDV provides measurements of both in- and out-of-plane velocity components over a uniform grid of up to ~27,000 points with approximately 0.7 mm spacing in the x- and y-directions. Images created from the 3D-LDV measurements clearly show the interaction of the elastic wave energy with the cracks. Comparisons between in- and out-of-plane components provide insight into whether and how the propagation behaviors of symmetric and antisymmetric Lamb wave modes differ upon encountering fatigue cracks.
Localization of Crack Initiation in a Pipe Structure Using a Laser Based Acoustic Emission Technique
This study presents a new acoustic emission technique that can localize a crack initiation event using training data obtained by surface-mounted MFCs and a pulsed laser excitation. First, an impulse response function of a sensing MFC mounted on the surface of a target structure is obtained by simulating an acoustic emission (AE) signal generated by a crack initiation with a non-contact pulsed laser excitation. Then, training impulse response functions are assembled by scanning the pulsed laser excitation over the surface of the target structure. Once a crack is initiated in the target structure, the AE signal generated from the crack initiation is recorded and compared with the training impulse functions using a unique concept of time reversal. Finally, the training impulse response function, which gives the maximum correlation with the actual crack initiation AE signal, is chosen from the training data set, and the crack initiation location is identified. The advantages of the proposed technique are that: (1) it can be applied even to complex structure without any additional geometric and/or temperature compensation; (2) only simple correlation calculation is required, making it attractive for real-time continuous monitoring; and (3) training is conducted using a non-contact pulsed laser excitation, which simulates the crack initiation event, and the existing sensors, which may already be installed for other structural health monitoring purposes. The effectiveness of the technique is validated on a SUS (Steel Use Stainless) pipe by imitating the crack initiation with a pencil-lead break.
Applications of the Vision-Based Monitoring System Using a Digital Image Correlation Technique to Long-Span Bridge Cables
Static or dynamic characteristics of civil infrastructures may generally differ from those of their initial design stage. Especially serviceability and stiffness degradation of structures, which are major factors used to verify structural conditions, could be identified by dynamic characteristics. As one of the most important measures to identify the dynamic characteristic of structures, displacement responses have been frequently measured for civil infrastructures even though they have some difficulties depending on the on-site condition of structures. In addition, the contact type displacement sensors may require temporary support frames to fix their sensor bodies or targets. As an alternative to reduce the installation expenses and enhance the reliability of measured data, a noncontact sensing method to measure the displacement responses in a remote distance without attaching sensors is needed. In this study, a method to measure multi-point displacement responses by using a digital image processing technique is suggested. Digital images are acquired by a commercial digital camcorder, which is the sensor to remotely measure displacement responses considering convenient and economical aspects for use. A digital image correlation (DIC) technique as one of digital image processing techniques is applied to develop the image processing algorithm and an image transform function (ITF) to correct the geometric distortion induced from the deformed images is used to increase the resolution of displacement responses. And, the shifting of image measurement equipment is also corrected to increase the resolution of displacement responses and modal frequencies.
In current work, Andrew plot is used as a new index to detect any probable damage in the structure. At the first step, using piezoelectric actuators and sensors, appropriate lamb wave is propagated and received through the structure. Then Principal Component Analysis is applied to the recorded data and prepares necessary data for Andrew curves. Andrew plots are depicted based on calculated principal components. It has been shown that comparing Andrew curves from baseline, structure without damage, with current statues of structure can identify any probable damages in the structure.
An Integrated MATLAB Toolbox for Optimal Sensor Placement Based on Multiple Optimization Strategies
Careful selection and placement of sensors are the critical issue in the construction and implementation of an effective structural health monitoring (SHM) system. A hybrid method termed the optimal sensor placement strategy (OSPS) based on the multiple optimization methods is proposed in this paper. Taking the scientific calculation software MATLAB as a platform, an OSPS toolbox, which is working as a black box, is developed based on the command-line compiling and GUI-aided graphical interface design. The characteristic and operation method of the toolbox are introduced in detail and the scheme selection of the OSP is carried out on the world tallest TV tower - Canton Tower based on the developed toolbox. The results indicate that the proposed method is effective and the software package has friendly interface, plenty of functions, good expansibility and is easy to operate, which can be easily applied in practical engineering.
Experimental Verification of Substructure Damage Detection Method Using ARX and ARMAX
A decentralized damage detection method for shear structure based on substructure approach is proposed, which is promising for application in parallel and distributed damage detection systems. This method requires only three sensors to identify localized damage in any story of a building. A substructure method was used in this method to divide a complete structure into several substructures. Each substructure has a considerably smaller number of degrees of freedom (DOFs) which makes fewer requirements on the computing power of the data processing system. Moreover the damage detection process can be independently conducted on each substructure. Thus, this method is very attractive especially when smart sensors that have the embedded computing power are used. To better assess the performance of the method proposed above, experimental verification of the proposed approach has been conducted, which shows the proposed method works quite well.
Application of Distributed Optical Fiber Strain Measurement into Geotechnical Engineering Monitoring
The characteristics of geotechnical engineering related structure such as tunnels, foundations and retaining walls are as follows: (1) The structure is normally buried underground and visual inspection of the health condition is not possible in most cases. (2) Due to the complicated geological and hydrological conditions, a number of uncertainties are involved in the design and construction of geotechnical structures. (3) Some of the geotechnical structures are super long and large. Therefore, the requirements of real-time and long-distance monitoring of these geo-structures are of great importance. Some key geo-structures such as large-span tunnel, underground facilities and foundations require the measurement accuracy in the order of micron or millimeter. Hence the conventional monitoring techniques cannot meet the demands for geo-structure health monitoring. Brilliouin Optical Time Domain Reflectometry/Analysis (BOTDR/A) is a fully distributed measurement technique, which utilizes Brilliouin spectroscopy and Optical Time Domain Reflectometer/Analyzer to measure strains generated in optical fibers as distributed in the longitudinal direction. Fiber Bragg Grating (FBG) is a qusaidistributed monitoring technique, which is a type of distributed Bragg reflector constructed in a short segment of optical fiber that reflects particular wavelengths of light and transmits all others. The reflected wavelength is proportional to the applied strain and temperature and the FBG sensor can therefore be used as a strain or temperature sensor. Because of the distinctive characteristics of the distributed optical fiber sensing technologies, they have been paid more and more attention and began to be used to construct monitoring systems of various geo-structures such as tunnels, embankments and soil nailed slopes. In this paper, the operation principles and merits of BOTDR/A and FBG are introduced; their application feasibility on the geostructure health monitoring are analyzed based on the authorsâ€™ research achievements and application cases; the related topics about application of BOTDR/A and FBG are discussed in detail, which include the installation methods of optical fiber, the impact of distance, temperature and humidity resolution on measurement results, the fatigue effect of optical fiber, the conversion from strain to deformation and the establishment
Structural Safety Monitoring During Construction of Shanghai Expo Puxi Entertainment Hall
Shanghai Expo Puxi Entertainment Hall (SEPEH) is retrofit from an existing workshop building. To meet new requirements of the hall, a structural column is removed and replaced with a box-section steel jacking beam. To evaluate the real-time structural state and ensure the structural safety of the hallâ€™s space truss roof during construction, a structural safety monitoring system is necessary. A structural safty monitoring system has been designed and applied in SEPEH. Three types of sensors have been installed to monitor the behavior of the structure during reconstruction: vibrating wire sensors; Fiber Bragg Grating (FBG) sensors; ForesightTM series of fiber optic distributed strain and temperature sensors (DSTS) based on BOTDA. Vibrating wire sensors and FBG sensors are installed to monitor the stress of member of the space truss structure; DSTS is installed to monitor the stress of the jacking beam and Vibrating wire sensors are installed to monitor the torsion of the jacking beam. Results show that the structural safety monitoring system works stably. The safety monitoring system reflects the real-time behaviour of the structure and controls the structural reconstruction safety effectively.
Finite Element Model Updating of Guangzhou Television and Sightseeing Tower Using Regularization Technique
Damage within a structure can be often inferred by comparing the modal properties identified from measurements with those obtained from a finite element (FE) model. Model updating aims to increase the accuracy and reliability of the FE model, which is essential for diagnosis and prognosis of the structureâ€™s health. This paper summarizes the modal analysis and model updating studies conducted using the monitoring data obtained from 610m-tall Guangzhou Television and Sight Seeing Tower, which was established as an international benchmark problem by the Hong Kong Polytechnic University. Modal properties of the tower were successfully identified using frequency domain decomposition and stochastic subspace identification methods. A fair agreement of the modal properties obtained from the measurements and the FE model was found. FE model updating using the measurement data was further performed to reduce the modal property differences between the measurements and the FE model. Over-fitting during the FE model updating was avoided by using optimization with regularization schemes.
New Software for Real-time Modal Identification
Framework of the structural health monitoring (SHM) is to detect and locate the damage in structures. SHM involves data collection, continuous monitoring and analyzing them in real-time. Changes in modal properties during structureâ€™s service life are strongly related to the damage potentials on the structure. Accurate estimation of modal properties (modal frequency, damping and mode shapes) is an essential step in SHM. Therefore, monitoring and accurate identification of real-time modal properties are crucial in order to have a good estimate in SHM. In this paper, a realtime modal identification technique for SHM applications has been developed. The technique is based on the modification of standard spectral analysis tools for real-time data, and utilizes running time windows to track time variations. A software package called KOERI-MIDS is developed for real-time modal identification. The software includes various user-selectable algorithms to identify modal properties, as well as options to plot their time variations and animations. The software has been tested with the ambient vibration data recorded from the Hagia Sophia Museum, a 1500 year-old historical structure in Istanbul. Modal properties of the structure have been identified accurately in real-time. Results of the Hagia Sophia test have been compared with the previous studies conducted by different researchers. Comparison shows that the results of the KOERI_MIDS are in good agreement with that of the previous studies
Proactive Condition Assessment in Civil Engineering Using Automated Multi-Sensor Systems
Infrastructure is subject to continuous ageing. This has given life cycle management of infrastructure an increasing role. Reliable inspection and monitoring tools are therefore an increasing demand. A combination of different non-destructive test methods is often necessary to receive reliable results for material characterization, flaw detection and the determination of component specific geometry parameters. Regarding concrete structures thickness measurements are combined with flaw detection and additional information about reinforcement and tendon ducts is required. Therefore, a multi-sensor measurement approach is necessary with a high degree of automation. Otherwise a time consuming succession of manual measurements has to be performed which would prevent practical applications. A modular control and data acquisition approach is described and the application of two different automated measurement devices is shown. The BetoScan system consists of a self-navigating mobile robot. The system is especially designed for the investigation of reinforced concrete floors exposed to de-icing salts. The data acquisition of the OSSCAR system a multi-sensor scanner is similar to the robot approach. These different applications are based on a similar kernel allowing the modular use of different contact and noncontact sensors. The described general concept of multi-sensor data acquisition and data analysis presented here is not limited to the field of civil engineering applications.
Operational Modal Analysis for a Benchmark High-Rise Structure
The 600 meter high Canton Tower is currently considered as a structural health monitoring (SHM) benchmark problem for high-rise slender structures. In the benchmark study task I, a set of 24-hour ambient vibration measurement data is provided to the research community for the output-only system identification and FE model updating. In this contribution, the vector autoregressive models (ARV) method is applied in the operational modal analysis (OMA) for this TV tower. The identified natural frequencies, damping ratios and mode shapes are presented and compared with the results obtained using the stochastic subspace identification (SSI) method. Furthermore, the environmental effects on the estimated modal parameters are also discussed.
An Efficient Sensor Placement Method for High-Rise Structuresâ€”A Case Study: The Canton Tower, China
An actual problem that should be solved by the engineer in the construction and implementation of an effective structural health monitoring (SHM) system is where the sensors should be located. The research on the optimal sensor placement (OSP) is carried out on the Canton Tower, the tallest TV tower in the world. To avoid the intensive computationally demanding problem in the dynamic analysis, the three dimension finite element (FE) model of the Canton Tower is first simplified to the equivalent series multi-DOF system. Considering that the sensors can be physically arranged only in the horizontal DOF of the structure, but not in the rotational DOF, the new thought of taking the horizontal DOF as the master DOF and rotational DOF as the slave DOF, and reducing the slave DOF by the model reduction is proposed. Then, the calculating model after reduction is gotten by the comparison of the reduction results of different methods. Finally, the configuration of the OSP of the Canton Tower is obtained after analyzing the implementation process of a kind of generalized genetic algorithm (GGA) and performing the parameter analysis.
Information Entropy-Based Algorithm of Sensor Placement Optimization for Structural Damage Detection
The structural health monitoring (SHM) benchmark study on optimal sensor placement for the Canton Tower, sponsored by the Asia-Pacific Network of Centers for Research in Smart Structures Technology (ANCRiSST), is first detailed in this paper. Then a two-step information entropy-based algorithm for sensor placement optimization is performed on the benchmark model. In the first step, mode shape change due to damage is extracted through modal analysis on the benchmark structure. In the second step, information entropy index is introduced to measure the uncertainties over the damage detection for each mode shape change, and then a multiobjective minimization problem in terms of different sensor placements is constructed. The optimal solution is determined as the one that provides almost equally informative data for all objectives. To validate the effectiveness of the determined optimal sensor placement, damage detection is performed on damage scenarios of the benchmark model using pre- and post-damage mode shapes obtained from the selected sensor placement. The results show that the obtained sensor configuration is able to provide information sensitive to damage.
SSA-Based Stochastic Subspace Identification of Structures from Output-Only Vibration Measurements
In this study the output-only system identification of civil structures via Stochastic Subspace Identification (SSI) is carried out. A newly developed signal processing technique, called Singular Spectrum Analysis (SSA), is capable to smooth a noisy signals is adopted for preprocessing the data. With the aim of finding accurate and true modal parameters, the SSA-based SSI-COV algorithm is implemented through the stabilization diagram, in which the identified system poles are plotted by increasing the size of data matrix. Comparative study on determining the model order and selecting the true system poles, with and without using SSA to pre-process the data, is examined through numerical simulation. Finally, identification task of the real large scale structure: Canton Tower, a benchmark problem for structural health monitoring of high-rise slender structures, using SSA-based SSI algorithm is carried out to extract the dynamic characteristics of the tower from output-only measurements.
SHM Benchmark for High-Rise Structures: Description of Host Structure and Measurement Data2406
The Canton Tower (formerly named Guangzhou New TV Tower) of 610 m high has been instrumented with a long-term structural health monitoring (SHM) system consisting of more than 700 sensors. Under the auspices of the Asian-Pacific Network of Centers for Research in Smart Structures Technology, an SHM benchmark problem for high-rise structures has been developed by taking the Canton Tower as the host structure. It aims to provide an international platform for direct comparison of various modal identification, model updating, and SHM algorithms with the use of real-world data from a large-scale structure. The development of a reduced-order finite element model (FEM) which serves as a baseline model for the benchmark study and field measurement data acquired from the instrumented structure, which is provided for modal identification and model updating studies, are detailed in this paper.
Model Assisted Probability of Detection Evaluation of a Health Monitoring System by Using CUDA Technology2437
In this work the authors propose a model-assisted POD application for SHM systems under uncertain crack configuration and system variability. The SHM system-related phenomena are studied via computer models. Other sources of variability are accounted for by adding empirical noise to the numerical results. Computers models are solved making use of parallel processing technology which significantly speeds up the simulation time.
Protocol for Reliability Assessment of Structural Health Monitoring Systems Incorporating Model-Assisted Probability of Detection (MAPOD) Approach
This paper will describe the progress in the development of a methodology for reliability assessment for SHM systems. The methodology consists of the development and use of appropriate statistical metrics of reliability for SHM systems that detect, localize, and/or size damage, and a protocol designed for utilizing empirical data, models, simulations, and uncertainty analyses for statistically characterizing these systems. The protocol comprises several critical steps: a procedure for analyzing all pertinent characteristics of the SHM system to identify the critical factors that affect system performance, a multistage approach to system validation, a modeling and experimental methodology for efficiently addressing a wide range of damage and operational conditions, and effective methods for evaluating the appropriate metrics of reliability depending on the SHM system type and function. A critical aspect of the protocol is that by addressing variability in the model and minimizing unexplained error in the representation, less experimental data will be required to address the total unknowns in the evaluation. The application of these methods in the protocol will be presented in detail including several demonstrations using simulation-based case studies.
The Need and Requirements for Validating Damage Detection Capability
Structural Health Monitoring (SHM) has been proposed to benefit the maintenance cost and reliability of aircraft structures through the early detection of damage during service and in support of condition-based maintenance. At the same time, if the integrity of an aircraft component is dependent upon the performance of an SHM system to detect damage, which has recently been referred to as an in-situ NDE system by two airframe OEMs [1,2], the reliability of the validated capability of the SHM system must also be ensured over the service life of the aircraft. To enable the calculation of risk, which is the metric used by the US Air Force (USAF) to manage the integrity of structures, the capability of any inspection process must be assessed and integrated into the risk calculation. Thus, a qualification plan is required for both the validated capability, i.e. POD and false-positive rate, and the durability of the sensing technique. These requirements were established by the Aircraft Structural Integrity Program (ASIP) Senior Leader for the USAF, Mr. Charles Babish [3]. Empirical assessment of the performance of an SHM system in such an environment is not a trivial manner and could readily be cost prohibitive. A protocol has been developed at the request of the AFRL Team Leader for Integrated System Health Assessment initiative that leverages current research and development efforts to minimize the amount of empirical data required for assessing the Probability of Detection (POD) of a damage detection system [4]. The on-going effort uses models and transfer functions to minimize the need for empirical data and is called Model-assisted Probability of Detection, or MAPOD [5,6]. The details defining these requirements and structure for the protocol to satisfy these requirements are presented.
Demonstration of Model Assisted Reliability Assessment Protocol on a Proposed Low Frequency Vibration Based Damage Sensing Case
This paper describes the progress on demonstrating a methodology for reliability assessment for structural damage sensing (SDS) systems. In particular, it presents the initial results obtained from the application of a protocol designed for utilizing empirical data, models, simulations, and uncertainty analyses for statistically characterizing SDS reliability for a damage detection case. The manufactured test article representing an aircraft structure of medium complexity consists of three plates connected by two lap joints with fasteners. Fatigue crack damage around the fastener holes was simulated by manually created thin cuts at selected locations. The test fixture design provides the capability to vary critical parameters of the system with a focus on force loading boundary conditions, joint fastener torque conditions, and temperature. The initial demonstration on this test article and fixture uses a low frequency vibration based damage detection method. Frequency domain metrics were utilized for studying changes in structural dynamics due to mechanical loading, thermal loading, and actual damage. For the demonstration, key factors that affect the capability to sense the effects of damage were assessed through controlled studies of (a) loading and unloading, (b) fastener torque, (c) boundary condition variation, (d) temperature variation and temperature gradients, (e) sensor bond quality and operation performance, (f) ambient noise, and (g) sensitivity to flaw growth. The design of the full validation study and the current results of the implementation are presented, highlighting general protocol feasibility while identifying remaining challenges for full demonstration and broad use of the methodology and protocol.
Challenges and Approach for SHM Technology Transition
A large number of aircraft currently in service have exceeded their design life. Many of these aircraft form the backbone of the operational fleet. Safety, reliability, and lifecycle costs are of great concern for these aging aircraft. Current inspection techniques require the aircraft to be removed from service and the structure to be disassembled, which is labor intensive and time consuming, and significantly adds to sustainment costs. Recent advances in sensor technology, material processing, damage modeling, and system integration have enabled new developments in inspection technologies and structural evaluation to overcome the shortcomings of existing inspection systems. Acellent Technologies is currently developing structural health monitoring systems utilizing permanently installed sensors to address these issues. This paper addresses the challenges involved in the development and transition of this technology including issues concerned with design, installation and validation methods for damage detection. Results of testing conducted with the system on simple and complex components will be discussed along with practical issues concerning the implementation and use of the system on aircraft structures. Particular focus will be on system development for detecting stress corrosion cracking on KC- 135 structure and pitting corrosion detection in multi-layered structural components, such as the XW155.024 chord of the F-15.
On the Performance Quantification of Active Sensing SHM Systems Using Model-Assisted POD Methods
System quantification is a critical and necessary step to provide an assessment of performance of any inspection technology, either classified to NDE or Structural Health Monitoring (SHM) techniques. For NDE techniques, the well-established method of probability of detection (POD) is widely accepted and adopted to quantitatively characterize and validate the reliability to detect a specified event (flaw) using the an NDE system. The resulting curves of system reliability correlate POD values with flaw sizes while statistical uncertainties are reflected by expressing the POD value together with a confidence level (CL). For most critical applications (like aerospace applications) 90/95 (POD/CL) is chosen as standard. Accordingly, a well defined and general applicable procedure need to be developed which allows appropriate quantification of SHM-based evaluation techniques, in particular with a view to active sensing systems. Along these lines, this contribution shows that the widely acknowledged procedure for NDE systems cannot be adopted directly for SHM systems without substantial changes. A broad variety of significant differences are inherent to the nature of SHM systems which occur in terms of main uncertainties (operator vs. environment), available test specimens (many vs. one unique), sensor configuration (moving vs. fixed), as well as test environment (fixed vs. varied). Based on these considerations, a model-assisted POD methodology for active SHM systems will be presented which allows to characterize the detection performance within a statistical framework mainly governed by the variability of environmental conditions that SHM systems will experience. In such a way, a similar POD/CL requirement can be established for SHM systems following a well defined protocol. To achieve this goal, missing key developments will be discussed as calibration techniques for model-assisted POD calculation, and appropriate damage simulators to mimic various damage scenarios in experimental tests.
Certification in Structural Health Monitoring Systems
Despite advances in health monitoring systems, the certification process for automated SHM systems remain rooted in the probability of detection (POD). POD is a fundamental part of the certification process, however, it is not the only measure of system validity. The process to certify a system must contain measures of accuracy and reliability. Disclosing the accuracy and reliability at the time of system design allows the end user to weigh differences among various SHM system architectures. In this manner, end users may identify the architecture that meets their specific overall system requirements. Further, it creates a benchmark from which system redesigns may be assessed and compared in order to improve overall system performance. In order to determine the appropriate measures of accuracy and reliability for the SHM system, first, the necessary output of such a system must be defined. Typically, the system is built in order to identify and assess structural damage. The appearance of damage is a detection problem whereas the extent of damage (crack length and location) is an estimation problem. Thus, the proper certification of a SHM system must incorporate measures of accuracy and reliability for both the detection and estimation of structural damage. These include probabilities related to detection such as the probabilities of true and false alarms as well as positive and negative predictive values. Confidence intervals must be defined as measures of the reliability of these probability estimates. Measures for the accuracy of the location and extent of structural damage include summary measures of the estimation process or model as well as the predicted location or crack length and its associated confidence interval. Establishment of the certification process as related to SHM will lead to better quantification of system performance for both detection and estimation and ultimately better system designs. These criteria may then act as a springboard for certification in subsequent prediction of structural failure, time remaining until structural failure, and other general aspects of risk analysis related to structural health.
FAA Research and Development Efforts in SHM
SHM systems are being developed using networks of sensors for the continuous monitoring, inspection and damage detection of commercial aircraft structures in order to improve safety, reduce costs and human induced damage. Aircraft OEMs, SHM system developers and airlines are interested in leading the way in more widespread SHM use. There is a need for an overarching plan that will guide near and long-term research activities that will comprehensively support the evolution and adoption of SHM practices in civil aviation. The Federal Aviation Administration is addressing these issues through the development of an SHM Research and Development roadmap.
Condition-Based Maintenance Plus and Maintenance Credit Validation
The Department of Defense (DoD) is currently maintaining the aircraft operability and functionality past the original design intention for many military aircraft. This practice imposes an additional burden on the inspection systems at the DoD logistic centers to ensure the aircraft in operation are airworthy and will be able to complete mission assignments for a specified period of time. Condition-Based Maintenance Plus (CBM+) has evolved into the U.S. Army leader priority program and becomes a critical technology for the future of the Army to reduce the logistic footprint, maximize the aircraft availability, and increase the component time on wing. To achieve these goals, the Army Research Laboratory (ARL) has initiated the CBM+ Science and Technology (S&T) Enterprise that spreads across ARL research organizations and supports the Army Research, Development, and Engineering Command CBM+ initiative in the Army fleet. The CBM+ S&T Enterprise has three Integrated Product Teams (IPTs), which focus on Hardware and Sensing, Prognostics and Diagnostics, and Data Transfer and Fusion Architecture technologies. The fourth IPT is the Technology Demonstration and Integration. It has been established that CBM, when joined with the system and/or sub-system prognostic capability (CBM+), could result in tremendous inspection savings, improved aircraft safety and availability, and decreased aircraft downtime and maintenance costs. Under these IPTs, diverse research efforts are being conducted and coordinated by the Technology Focus Working Groups (TFWGs) to combine diagnostics and prognostics capabilities. TFWGs concentrate on many technologies and processes including Structural Health Monitoring (SHM) and Maintenance Credit Validation. One of the challenges for researchers has been the development of the SHM capability that is not only effective and reliable but also relatively low cost and easy to install and maintain while performing the desired function of monitoring DoD systems and sub-systems for loss of structural integrity. SHM methods can be used to monitor the condition of critical structural components and, with other technologies, can determine the structural remaining useful life. As a result, potential maintenance credits, e.g., increased time-between-overhaul or fatigue life adjustment, can be
A Wavelet-Based Spectral Finite Element Method for Simulating Elastic Wave Propagation
In the present paper, a novel formulation of the wavelet-based finite element method (WSFEM) is proposed and applied to the in-plane wave equations in orthotropic plate structures. By computing the exact values of the connection coefficients of Daubechies compactly supported wavelets over a finite interval, the wavelet-Galerkin method is employed. Subsequently, the elastodynamic equations are decoupled with respect to the transformation parameter. Contrary to more conventional transformed domain methods which have difficulties in handling relatively complex geometries, the response in the transformed (wavelet) domain is fully discretized in analogy with FEM. However, unlike the conventional FEM, the basis functions in the proposed WSFEM are functions of the wavenumbers in the transformed domain. It is shown in the paper that the proposed WSFEM converges faster than FEM with linear or quadratic basis functions with substantially fewer number of time sampling points. Since the present approach allows for solving the transformed governing equations for each wavelet point separately, the method is inherently suitable for parallel computation. In addition, the temporal discretization is not influenced by the FE mesh.
A Method to Detect Structural Damage Using High-Frequency Seismograms
instrumented civil structures. An automated damage detection method that analyzes recorded data has application to building types that are susceptible to a signature type of failure, where locations of potential structural damage are known a priori. In particular, this method has application to the detection of brittle fractures in welded beam-column connections in steel moment-resisting frames (MRFs). Such a method would be valuable if it could be used to detect types of damage that are otherwise difficult and costly to identify. The method makes use of a prerecorded catalog of Greenâ€™s function templates and a matched filter method to detect the occurrence and location of structural damage in an instrumented building. This technique is different from existing acoustic methods because it is designed to recognize and use seismic waves radiated by the original brittle failure event where the event is not known to have occurred with certainty and the resulting damage may not be visible. The method is outlined as follows. First, identify probable locations of failure in an undamaged building. In pre-Northridge steel MRFs, which are susceptible to brittle failure of welded beam-column connections, those connections would be the locations of probable failure for this type of building. Second, obtain a Greenâ€™s function template for each identified location of probable failure by applying a short-duration high-frequency pulse (e.g. using a force transducer hammer) at that location. One underlying assumption of this method is that the Greenâ€™s function template specific to a potential location of failure can be used to approximate the dynamic response of the structure to structural damage at that location. Lastly, after a seismic event, systematically screen the recorded high-frequency seismograms for the presence of waveform similarities to each of the catalogued Greenâ€™s function templates in order to
Development of SEM-Based PESEA Code for Modeling PZT Induced Acousto-Ultrasonic Waves Propagating in Metallic and Composite Structures
This paper presents the development of 3D spectral element based PESEA (PZT Enabled Spectral Element Analysis) code to simulate PZT-induced acousto-ultrasonic wave propagation in metallic and composite structures. PESEA solves coupled electromechanical governing equations for a given arbitrary voltage input to a piezoelectric actuator and outputs voltage response of piezoelectric sensors. In case of modeling composites, one element per ply is computationally expensive and smeared material properties may give inaccurate results; hence a layered solid spectral element (SE) is introduced. This layered solid SE can model several plies per element and uses combined nodal quadrature and Simpsonâ€™s â…“ integration rule to calculate mechanical stiffness matrix of each element. Rayleigh damping model is used to account for the viscoelastic nature of carbon fiber reinforced polymer (CFRP) laminated composites.
Nonlinear Guided Waves: Theoretical Considerations and Applications to Thermal Stress Measurement in Continuous Welded Rails
The interest in nonlinear guided wave propagation has increased dramatically in the last few decades mainly because of the great potential in using nonlinear features of elastic waves in the nondestructive evaluation of structures. Generation of double harmonic and internal resonance phenomena in nonlinear isotropic waveguides have been analyzed in the past for simple geometries where an analytical solution for the waveguide modes is available. In this work the classical Semi-Analytical Finite Element formulation is extended to the nonlinear regime and is implemented into a commercial code. The usefulness of the approach is demonstrated through the study of the internal resonance conditions in a rail track.
Local Interaction Simulation of Guided-Wave Propagation in Composite Plates Using CLoVER Transducer
This paper presents numerical simulations based on local interaction simulation approach (LISA) for guided wave (GW) propagation in laminated composite plates. The GW is generated by the composite long-range variable-direction emitting radar (CLoVER) transducer. A brief overview of the LISA formulation is presented, with highlights to the new components introduced to the solution. The resulting iterative equations are used to simulate GW propagation in uni-ply [0]12T and cross-ply [0/90]3S laminates. The simulated results are validated against laser vibrometry experiments.
Predictive Modeling of Ultrasonics SHM with PWAS Transducers
This paper presents a set of analytical and numerical results on the use of guided waves for structural health monitoring application. The aim of the work presented in this paper is to provide tools to extend modeling capacities and improve quality and reliability of guided wave propagation models using commercially available finite element (FE) packages. Predictive simulation of ultrasonic non-destructive evaluation (NDE) and structural health monitoring (SHM) in realistic structures is challenging. The principle of guided wave propagation is studied and an analytical model is developed to obtain the analytical waveform and theoretical frequency contents solution of arbitrary engineering situations. Two benchmark problems, one 1-D and the other 2-D to achieve reliable and trustworthy predictive simulation of ultrasonic guided wave SHM with FEM codes have been proposed. The proposed 1-D benchmark problem will be a simple pitch-catch arrangement between a transmitter PWAS and receiver PWAS in a plate. The proposed 2-D benchmark problem will be the pitch-catch arrangement in a full 2-D plate involving circular-crested guided waves between a transmitter PWAS and receiver PWAS. In addition, a circular through hole of defined size ratio could be added to the 2-D problem to simulate the detection of damage, and assess the detectability threshold since closed-form solution exists for this problem too. The paper finishes with summary, conclusion, and suggestions for further work.
Lamb Wave Techniques for Damage Detection in CFRP-Componentsâ€”Is This Really Possible?
Waves (LWs) enables in principle a testing of components on demand without time consuming scanning. Their excitation and reception is easily possible with piezoelectric transducers (PZTs). LWs can penetrate large areas with a small attenuation and interact with defects. The localization of damage requires a network of PZTs on the component. However, in spite of a narrowband excitation in minimum two modes are generated (S0 and A0). Both modes are dispersive and propagate with different velocities. The interaction between both LW modes and defects is very complex and the received signals are difficult to evaluate. Especially composite components additionally show anisotropic velocities. The DLR part of the European AISHA II project is the detection of impact damages in the sandwich composite structure of an Eurocopter EC135 Tailboom. In order to get reliable information it is useful to visualize the wave propagation and the interaction with defects. At DLR the aircoupled ultrasonic technique has been successfully enhanced for this visualisation. The investigations of long-range wave propagation show mode conversions at all stiffness discontinuities. This paper describes damage detection based on mode conversions which enable clearer signals than techniques with bonded PZTs for excitation and receiving. This new method requires only a few actuators for the S0 mode and a network of air-coupled sensors which are sensitive for the A0 mode.
System Identification with Generalized Impulse and Frequency Response Function
This paper introduces a wave-based approach for system identification of high-rise structures with a pair of seismic recordings, which can be used to evaluate structural integrity and detect damage in post-earthquake structural condition assessment. The fundamental of the approach is based on wave features of generalized impulse and frequency response function (GIRF and GFRF), i.e., wave responses at one structural location to an impulsive motion at another reference location in time and frequency domains respectively. With a pair of seismic recordings at the two locations, GFRF is obtainable as Fourier spectral ratio of the two recordings. With an appropriate continuous model for the structure, a closed-form solution of GFRF, and subsequent GIRF, can also be found, which are related to structural physical properties above the impulse location. Matching the two sets of GFRF and/or GIRF from recordings and the model helps identify structural parameters such as wave velocity or shear modulus. For illustration, this study examines ten-story Millikan Library in Pasadena, California with recordings of Yorba Linda earthquake of September 3, 2002.
Propagation of Guided Elastic Waves in Aircraft Structural Elements by the Spectral Finite Element Method
Certain results of numerical simulations obtained by the use of the Spectral Finite Element Method (SFEM) are presented by the authors. They are selected in order to show the effectiveness of the SFEM for investigation of various problems associated with propagation of guided elastic waves in shell-type aircraft structural elements. In this paper a section of the helicopter stabilizer is investigated. Results of these simulations are subsequently evaluated in order to detect and localize simulated damage and compared against results of experimental measurements by the use of laser scanning vibrometry.
SHM of Structural Materials by Means of Highly Nonlinear Solitary Waves
A novel nondestructive technique for the health monitoring of structural materials such as aluminum and cement is presented. In this technique the time of flight and the amplitudes of highly nonlinear solitary waves (HNSWs) are monitored. HNSWs are mechanical waves that can form and travel in nonlinear systems, such as one-dimensional chains of particles. A novel actuator/sensor electronically controlled is used to excite and detect HNSWs in a chain of spherical particles. This chain of particles is interfaced to the structural material being monitored to evaluate one of the following: strength, stiffness, bonding condition. It is hypothesized that the propagation characteristics of the waves in terms of time of flight and reflection amplitudes from the actuator/structural material interface are dependent on the properties of the structure. The experimental results relative to a cement paste and aluminum lap-joints are presented.
Interaction of Elastic Waves with Delaminations in CFRP Structures: A Numerical Study Using the Spectral Element Method
In many SHM applications elastic waves are used to determine the health of a structure. Especially in case of thin walled structures, guided waves have shown a high potential to detect damages or irregularities. Surface bonded or integrated piezoelectric elements excite the structure and induce elastic waves. The wave propagation at particular positions can also be sensed by piezoelectric elements. Many experiments are necessary to design an optimum sensor configuration in real SHM-applications to detect specific kind of damages. The present work discusses a typical damage type and the interaction with the elastic waves for a CFRP structure. Delamination is one of the most common failure mechanisms in laminated structures. To simulate the wave propagation and the interaction with the damage the time domain spectral element method (SEM) with 2D flat shell spectral elements is used. For materials with a symmetrical layup the result is a diagonal mass matrix. This advantage leads to a significant saving of memory and to a reduction of complexity of the time integration algorithm. Within the spectral element model the delaminated area is modelled by using separated upper and lower elements. A contact formulation is used to prevent the penetration between the separated layers. Different interaction effects of the elastic waves with the delamination will be shown by numerical studies.
Combining Guided Waves and Electromechanical Impedance Method for SHM Applications
In this paper the simultaneous use of ultrasonic testing and impedance-based technique to monitor the health of waveguides is proposed. Methods based on the propagation of guided waves are increasingly used in all those structural health monitoring (SHM) applications that benefit from built-in transduction, moderately large inspection ranges, and high sensitivity to small flaws. In the meantime, impedance-based SHM has shown promising success in assessing structural integrity of local areas. Leveraging the fact that both wave-based and impedance-based approaches can be used by deploying piezoelectric transducers (PZT) bonded or embedded to the structure being monitored, this paper describes a unified SHM paradigm where these techniques are employed simultaneously, using the same sensing/hardware/software. Specifically, we propose to use two PZTs controlled by a National Instrument PXI running under LabView. An ad hoc LabView Virtual Instrument controls signal output and input as well as processing and storage. To assess the feasibility of this unified system an aluminum plate was monitored. Damage was simulated by changing the boundary conditions of the plate. The results show that the proposed system is robust and can be developed further to address the challenges associated with the SHM of complex structures.
Coupling Sensor-based Structural Health Monitoring with Finite Element Model Updating for Probabilistic Lifetime Estimation of Wind Energy Converter Structures
The worldwide demand for green energy systems is evident. In this context, wind energy converters will play a paramount role. Extending the service life of a wind energy converter translates into significant economic savings as well as ecological earnings. New opportunities for the management and operation of the wind energy converters make it beneficial to know the structural condition and the remaining life span of wind energy converters at each point in time during their operation. This paper presents the implementation of an integrated framework for probabilistic lifetime estimation of wind energy converter structures coupling sensor-based structural health monitoring with finite element model updating.
Aspects of Automatization of Wind Farm Monitoring on the Example of a Diagnostic Center
The paper presents selected aspects of the design and implementation of the Diagnostic Center as an innovative concept of systems of monitoring and diagnosis system (SM&D) for wind farms. Current SM&D systems are faced not only with exponentially growing disc storage handling, but also with accessibility enhancement, optimization of discriminatory signal features selection, and finally with signal analysis automatization. The concept presented by the authors is a pioneering solution, which combines modern hardware and software technologies accompanied by implementation of latest discoveries in vibration signal processing. In the paper, the authors illustrate selected features of the Diagnostic Center with the emphasis on the automatization of vibration analysis of wind farms.
In-Operation Identification of a Wind Turbine Structure via Non-Stationary Parametric Models
The in-operation identification of a wind turbine structure via non-stationary parametric Time-dependent AutoRegressive (TAR) models is presented. The identification is based on a single vibration acceleration response signal obtained at the tower of a NegNicon NM52/900 wind turbine under normal operating conditions. Following preliminary non-parametric analysis, Smoothness Priors TAR (SP-TAR) and Functional Series TAR (FS-TAR) models are identified and analyzed. The results of the study confirm the cyclo-stationary and/or non-stationary nature of the dynamics, and indicate three main types of dynamical behavior: That due to the wind characteristics, those due to the low and high speed shafts of the transmission system, and strongly cyclo-stationary dynamics associated with blade rotation.
Structural Integrity Monitoring of the Critical Zones in the Wind Turbine Composite Blades with the Use of Integrated Sensorsâ€”SESS Project
The wind turbine blade is the second most expensive part of a wind turbine, constituting 20-22% of the total cost. According to one study, during the lifetime of a wind turbine, rotor blades contribute to 34% of overall system downtime. Associated maintenance costs, by some estimates, are 1.5-2% of a new generation wind turbine investment. All of these affect the profitability of wind generation. This paper presents modern approach for structural integrity monitoring and damage detection in the wind turbine blades. Composite structure of the blade is affected by the environmental issues and cycling load. These lead to possibility of occurrence different failure modes affecting structural integrity of composite as well as bond joints. For that reason during the quality control in manufacturing as well as for inservice inspection appropriate techniques must be applied to monitor such structures. This article assume integrated sensors approach with the use of elastic waves generation for the bonding joint monitoring of the wind turbine blade. One of the proposed solution is the SESS system. The SESS â€“ Smart Embedded Sensor System is the health monitoring system for the assessment the integrity of the critical zones in the wind turbine blade. The SESS is designed to be a system for early damage detection which will: ïƒ˜ Focus on â€˜hot spotsâ€™ located on the wind turbine blade; ïƒ˜ Identify key damage types which are associated with selected â€˜hot spotsâ€™; ïƒ˜ Give the user an appropriate knowledge base and analysis tool to assess the damage and schedule repairs and maintenance on an asneeded basis. Article presents the design of the state of the art system with sensors array which will be integrated with the blade. Moreover the information about the algorithms, data processing, hardware solutions will be delivered. The most important will be the information about the verification tests in the lab as well as on the component (blade).
Lightning Protected Monitoring System for Wind Turbine Rotor Blades
Lightning strike is one of the most frequently causes of defect for wind turbine rotor blades. Because of the tremendous magnetic inductions caused by lightning conductor current use of metallic wiring for communication and power supply is quite impossible. The work describes a monitoring system based on acoustic emission and acousto ultrasonic techniques combined with acceleration measurements for rotor blades. The sensors are distributed over the surface of the rotor blade and the Backbone for data transfer and power supply is realized by optical components. Monitoring techniques and technical realization of such a sensing network as well as first results of acoustic emission and acousto ultrasonic measurements in rotor blades will be presented. Challenges and solutions of such a monitoring system like sensor application, optical wiring, data collection and signal processing for the acoustic applications will be described.
A Full-Scale Fatigue Test of 9-m CX-100 Wind Turbine Blades
This paper presents the SHM result of a 9m CX-100 wind turbine blade under fullscale fatigue loads. The test was performed at the National Renewable Energy Laboratory. The 9-meter blade was instrumented with piezoelectric transducers, accelerometers, acoustic emission sensors, and foil strain gauges on the surface of the blade. The blade underwent fatigue excitation at 1.8 Hz for defined intervals, and data from the sensors were collected between and during fatigue loading sessions. The data were measured at multi-scale, high frequency ranges for identifying fatigue damage initiation, and low-frequency ranges for assessing damage progression. High and Low frequency response functions, time series based methods, and Lamb wave date measured by piezoelectric transducers were utilized to analyze the condition of the turbine blade, along with other sensing systems (acoustic emission). A specially designed hardware developed by Los Alamos National Laboratory was also implemented for performance comparison. This paper summarizes considerations needed to design such SHM systems, experimental procedures and results, and additional issues that can be used as guidelines for future investigations.
Assessment of Structural Monitoring Techniques for a Small Wind Turbine Test Stand
This paper presents the research activities performed on a Small Wind Turbine (SWT) test stand. A commercially available turbine was modified towards incorporation of sensors for condition monitoring to measure angular shaft position, applied torque, rotational speed and vibration acceleration. Wind data are also acquired through an anemometer. A dedicated interface was initially developed to allow automatic and remote control of the Data Acquisition System. After each session, all acquired signals are stored in a database from where can be accessed for further processing. Once the reference response of the system is characterized, typical faults or dangerous operating conditions are simulated to obtain more information on the effects of these events on the response.. In particular, order tracking is used to identify anomalous vibration level at different RPMs.
Appropriate Rigid Body Correction for Analyzing the Dynamics of Rotating Structures Using 3D Digital Photogrammetry
Stereophotogrammetry techniques have been used to measure high-speed dynamic systems for several years and are now being used to measure the motion of rotating systems, such as wind turbines and helicopter rotors. The blade vibratory motion of these systems is often considerably smaller than their rigid body dynamics, and to better understand the hidden structural dynamics of these structures, the extraneous movements can be subtracted from the collected data using rigid body correction (RBC) algorithms. Unfortunately, performing rigid body corrections on rotating systems is not always straightforward and the incorrect use of these algorithms can distort the measured dynamics of a system. Dynamic measurements have previously been taken on a rotating turbine and a RBC was performed on all rotor measurement points yielding unexpected dynamic behavior. This behavior was observed by processing the data using all measurement points on the turbine and observing the displacement versus time data for a single measurement point at the tip of one of the blades. A second RBC was performed using only the hub measurement points and the resulting processed dynamic behavior was very different. To better understand how RBC can affect the measured dynamics of rotating systems, a sensitivity study was conducted on the same rotating turbine. The results of this sensitivity study are presented within this work and conclusions on the size of the measurement point region that can be used in the RBC for this particular turbine and measurement point layout are made.
Integrated Sensor System for Structural Integrity and Load Monitoring of Wind Turbines
Development of an integrated Fiber Bragg Grating (FBG) structural health monitoring (SHM) system for a composite horizontal axis wind turbine blade is reported in this article. The SHM systems are expected to make significant reduction in the operational cost of wind turbines by optimizing the maintenance, yielding maximum service life of the wind turbine at minimum maintenance cost. Recently, the SHM systems are receiving even more attention due to the current trend in designing larger wind turbines in order to increase the efficiency. Increasing their size subjects them to larger operational loads and thus demands precise and real-time information about how the system is performing. The FBG sensor as SHM sensor has many advantages over other conventional sensors. Providing real-time information about structural integrity and operational load can be used in conjunction with other methods to decrease the overall energy cost. This paper discusses laboratory scale experimental setup for validation of FBG as a strain sensor to be used in SHM. Validation methods include a comparison of static strain measured with a resistive strain gauge to the FBG, and a modal analysis done with the FBGs compared to accelerometers.
Structural Health Monitoring: An End Userâ€™s Point of View
The Structural Health Monitoring (SHM) concept has been developed in the early 1990s to improve the monitoring and safety of civil works and aeronautical structures. SHM consists more precisely to define a periodical and/or continuous monitoring strategy for all the life of such structures (old or not). A period of 15-20 years of worldwide SHM use has proven that this concept is today mature. The EDF group is one of the world's largest electricity producers , with a solid position in Europe and industrial operations in Asia and the United States. The civil engineering patrimony is composed in part of 58 nuclear PWRs in France (pressurized water reactors) of an average age of about 22 years, 447 hydroelectric power plants and 32 generation units of fossile-fired energy. Heavily involved in managing its power plants, EDF set up its own civil engineering works monitoring policy to perform the best monitoring of its civil works. EDF is continuously attempting to improve its method and means of monitoring its works and equipment as part of its approach as the responsible operator. So EDF R&D decided to evaluate the SHM methodology and to compare it to its own methodology and to its operating experience. This article aims to : - expose the results of a large bibliographic study on the SHM monitoring methodology, - give the EDF R&D point of view on the SHM methodology as operator, - give an EDF application of the SHM concept : optical fiber application for monitoring of dams [1].
PZT Active Frequency Based Wind Blade Fatigue to Failure Testing Results for Various Blade Designs
This paper summarizes NASA PZT Health Monitoring System results previously reported for 9 meter blade Fatigue loading to failure conducted at The National Renewable Energy Lab Wind blade testing facility results using the on the CX-100, TX-100 and BSDS designs. A collaborative effort between Sandia National Laboratories (SNL) and NASA KSC has been performed to evaluate the viability of a NASA Developed PZT Piezoelectric sensor/actuator for structural health monitoring (SHM) of Wind turbine blades. The innovation behind the NASA developed sensors in the combination of signal data processing with the development of a unique sensor/actuator consisting of piezoelectric materials in a thin and highly sensitive configuration. This paper summarizes previous NASA PZT system testing and includes results of the Fatigue testing of a 9 Meter Wind blade fatigue test referred to as the Sensor Blade which was based on the CX-100 design. This configuration had internal instrumentation/video and consisted of an internal manufacturing known defect. The defect provided an opportunity to demonstrate the PZT Health monitoring performance.
Ultrasonic Structural Health Monitoring of Cable Structures
In an effort to detect and localize damages in engineering structures, the research field of Structural Health Monitoring (SHM) has emerged rapidly. SHM involves regular evaluation of the structural state by means of integrated actuators and sensors. Among potential damage detection methods, ultrasonic wave-based techniques are widely used because of their versatility and affordability. One target for SHM applications in the realm of civil engineering are cable structures, such as overhead transmission lines and stay cables in bridges. These are subject to static and dynamic loads, aging, corrosion and accidental events. The excitation of ultrasonic waves in cylindrical media generates guided waves, which can propagate long distances. This allows for monitoring large sections of a cable with a single actuator and sensor. On the other hand, guided wave propagation in cylinders is multimodal, which complicates analysis and synthesis of wave motion. This work addresses several aspects of guided wave propagation in cylindrical structures, with the objective of developing an SHM methodology for cable structures.