Impedance-based Structural Health Monitoring Research Articles

An outlier analysis of MFC-based impedance sensing data for wireless structural health monitoring of railroad tracks

This paper presents an outlier analysis for damage detection of railroad tracks using a macro-fiber composite (MFC) impedance-based wireless structural health monitoring (SHM) system. The impedance-based SHM method has some limitations because the measured impedance data may have considerable deviations caused by environmental or operational condition changes, including temperature, humidity, external loadings, or MFC patch bonding conditions. Thus, the method sometimes gives false-positive indication even for healthy structures. In order to overcome this limitation, an outlier analysis based on Mahalanobis squared distance (MSD) was proposed by taking root mean square deviation (RMSD) values of impedance signatures as a damage-sensitive feature vector. Optimal threshold values for both RMSD and MSD were determined through the proposed outlier analysis. The results showed that the use of MSD improved the damage detection capability with a lower threshold level as compared to that of RMSD. In this study, the applicability of the proposed method was experimentally verified by detecting three types of the railroad track damage, including head damage, web damage, and flange damage, which were simulated under the laboratory setting.

Frequency Range Selection for Impedance-Based Structural Health Monitoring

Impedance-based structural health monitoring uses collocated piezoelectric transducers to locally excite a structure at high frequencies. The response of the structure is measured by the same transducer. Changes in this response indicate damage. Frequency range selection for monitoring with impedance-based structural health monitoring has, in the past, been done by trial and error methods or has been selected after analysis by engineers familiar with the method. This study aims to determine if, in future applications, it is possible to automatically select preferred frequency ranges based on sensor characteristics, perhaps even before installing the system. In addition, the paper demonstrates a method for determining preferable frequency ranges for monitoring. The study examines the analysis of the measurement change through a damage metric and relates the results of the analysis to characteristics of the measurement. Specifically, outlier detection concepts were used to statistically evaluate the damage detection ability of the transducers at various frequency ranges. The variation in undamaged measurements is compared to the amount of change in the measurement upon various levels of damage. Testing was performed with both solid piezoceramic transducers and macrofiber composite piezoelectric devices of different sizes bonded to aluminum and fiber reinforced composite structures. The results indicate that characteristics of the structure, not the sensor alone, determine the optimal monitoring frequency ranges.

Electro-Mechanical Impedance-Based Wireless Structural Health Monitoring Using PCA-Data Compression and k-means Clustering Algorithms

This article presents a practical method for an electro-mechanical impedance-based wireless structural health monitoring (SHM), which incorporates the principal component analysis (PCA)-based data compression and k-means clustering-based pattern recognition. An on-board active sensor system, which consists of a miniaturized impedance measuring chip (AD5933) and a self-sensing macro-fiber composite (MFC) patch, is utilized as a next-generation toolkit of the electromechanical impedance-based SHM system. The PCA algorithm is applied to the raw impedance data obtained from the MFC patch to enhance a local data analysis-capability of the on-board active sensor system, maintaining the essential vibration characteristics and eliminating the unwanted noises through the data compression. Then, the root-mean square-deviation (RMSD)-based damage detection result using the PCA-compressed impedances is compared with the result obtained from the raw impedance data without the PCA preprocessing. Furthermore, the k-means clustering-based unsupervised pattern recognition, employing only two principal components, is implemented. The effectiveness of the proposed methods for a practical use of the electromechanical impedance-based wireless SHM is verified through an experimental study consisting of inspecting loose bolts in a bolt-jointed aluminum structure.

Circuit Analysis of Impedance-based Health Monitoring of Beams Using Spectral Elements

A model is generally not needed for the basic damage identification problem when using the electromechanical impedance-based method of structural health monitoring (SHM). However, modeling becomes necessary when more information is needed for more complex functions of the SHM system, such as estimation of remaining life. In addition, suitable models would aid in more accurately identifying and locating damage and in designing the SHM system. Since impedance-based SHM relies on high frequency excitation of the structure using piezoelectric patches, finite element modeling may not be computationally efficient. In this study, the spectral element method (SEM) is used in combination with electric circuit analysis for impedance modeling. SEM more accurately models higher frequency vibrations than finite element methods since the mass is modeled exactly and it incorporates higher order models more easily. Simulations of sensor multiplexing, high frequency response, and the inclusion of damage are presented. Experimental verification is also included.

Structural health monitoring using piezoelectric impedance measurements

This paper presents an overview and recent advances in impedance-based structural health monitoring. The basic principle behind this technique is to apply high-frequency structural excitations (typically greater than 30kHz) through surface-bonded piezoelectric transducers, and measure the impedance of structures by monitoring the current and voltage applied to the piezoelectric transducers. Changes in impedance indicate changes in the structure, which in turn can indicate that damage has occurred. An experimental study is presented to demonstrate how this technique can be used to detect structural damage in real time. Signal processing methods that address damage classifications and data compression issues associated with the use of the impedance methods are also summarized. Finally, a modified frequency-domain autoregressive model with exogenous inputs (ARX) is described. The frequency-domain ARX model, constructed by measured impedance data, is used to diagnose structural damage with levels of statistical confidence.

Impedance-based Health Monitoring for Aeronautic Structures using Statistical Meta-modeling

In this work, techniques of impedance-based structural health monitoring are applied to aeronautical structures using statistical meta-modeling methods. First, a procedure is developed to find the best test conditions through factorial designs. Also, Taguchi robustness techniques are used to reduce noise influence in damage detection processes. Further, based on meta-models, a procedure is developed for damage identification and characterization, as applied to a vertical fin of an unmanned aerial vehicle (UAV). Structural changes are obtained by using localized adding masses at several determined points along the structure. Finally, by using two meta-models, namely a probabilistic neural network model and a surface response model, it is possible to identify as well as to characterize damage in the structure.

Multiple Crack Detection of Concrete Structures Using Impedance-based Structural Health Monitoring Techniques

This paper presents a feasibility study for practical applications of an impedance-based real-time health monitoring technique applying PZT (Lead–Zirconate–Titanate) patches to concrete structures. First, comparison between experimental and analytical studies for damage detection on a plain concrete beam is made. In the experimental study, progressive surface damage inflicted artificially on the plain concrete beam is assessed by using both lateral and thickness modes of the PZT patches. Then, an analytical study based on finite element (FE) models is carried out to verify the validity of the experimental result. Secondly, multiple (shear and flexural) cracks incurred in a reinforced concrete (RC) beam under a third point bending test are monitored continuously by using a sensor array system composed of the PZT patches. In this study, a root mean square deviation (RMSD) in the impedance signatures of the PZT patches is used as a damage indicator.

A Smart Health Monitoring System with Application to Welded Structures using Piezoceramic and Fiber Optic Transducers

Large welded structures, including ships and offshore structures, are normally in operation under cyclic fatigue loadings. These structures include many geometric as well as material discontinuities due to weld joints, and the fatigue strength at these hot spots is of critical importance for the structural performance. In the past, various Non-Destructive Evaluation (NDE) techniques have been developed to detect fatigue cracks and to estimate their location and size. However, important limitations of most of the existing NDE methods are that they are off-line; the normal operation of the structure has to be interrupted and the device often has to be disassembled. In this context, a new impedance-based structural health monitoring system employing piezoceramic transducers is developed with a special interest in applying the technique for welded structural members in ship and offshore structures. In particular, the impedance-based structural health monitoring technique that employs the coupling effect of piezoceramic (PZT) materials and structures is investigated. Moreover, a preliminary study of using fiber Bragg grating (FBG) type optical fiber sensors for the stress measurement of a typical weld structure is investigated. The final goal is to extend the fiber optic sensor technique for the global and local stress measurements of ship or offshore structures.

Non-linear feature identifications based on self-sensing impedance measurements for structural health assessment

This paper presents the application of a non-linear feature identification technique for structural damage detection. This method is coupled with the impedance-based structural health monitoring (SHM) method, which utilises electromechanical coupling properties of piezoelectric materials. The non-linear feature examined in this study is in the form of autoregressive coefficients in the frequency domain autoregressive model with exogenous (ARX) inputs, which explicitly considers non-linear system input/output relationships. The applicability of this non-linear feature for damage identification is investigated in various frequency ranges using impedance signals measured from a laboratory-test structure. The performance of the non-linear feature is also compared with those of linear features typically used in impedance methods. This paper reinforces the utility of non-linear features in SHM and suggests that their sensitivity in different frequency ranges may be leveraged for certain applications.

Simultaneous Health Monitoring and Vibration Control of Structures Using Smart Materials

Large welded structures, including ships and offshore structures, are normally in operation under cyclic fatigue loadings. These structures include many geometric as well as material discontinuities due to weld joints, and the fatigue strength at these hot spots is very important for the structural performance. In the past, various Non-Destructive Evaluation (NDE) techniques have been developed to detect fatigue cracks and to estimate their location and size. However, an important limitation of most of the existing NDE methods is that they are off-line; the normal operation of the structure has to be interrupted and the device often has to be disassembled. In this study, a new impedance-based structural health monitoring system employing piezoceramic transducers is developed with a special interest in applying the technique for welded structural members in ship and offshore structures. In particular, the impedance-based structural health monitoring technique that employs the coupling effect of piezoceramic (PZT) materials and structures is investigated.

Simplified Modeling for Impedance-Based Health Monitoring

A new model of impedance-based structural health monitoring (SHM) using the spectral element method (SEM) and electric circuit analysis has been developed. This model provides additional information for more accurately identifying and locating damage and in designing the SHM system. Complex functions of the SHM system such as estimation of remaining life are also made possible with the use of the model. The circuit analysis can be applied to any type of structural model. However, since impedance-based SHM relies on high frequency excitation of the structure using piezoelectric patches, finite element modeling may not be applicable and instead the spectral element method (SEM) is used. SEM more accurately models higher frequency vibrations since the mass is modeled “exactly” and incorporates higher order models more easily. Model and experimental results are presented for damaged and undamaged specimens.

An outlier analysis framework for impedance-based structural health monitoring

This paper presents the use of statistically rigorous algorithms combined with active-sensing impedance methods for damage identification in engineering systems. In particular, we propose to use statistical pattern recognition methods to address damage classification and data mining issues associated with the examination of large numbers of impedance signals for health monitoring applications. In this paper, in order to diagnose damage with statistical confidence, the impedance-based monitoring is cast in the context of an outlier detection framework. A modified auto-regressive model with exogenous inputs (ARX) in the frequency domain is developed and the damage-sensitive feature is obtained by quantifying the differences between the measured impedance and the output of the ARX model. Furthermore, because of the non-Gaussian nature of the feature distribution tails, extreme value statistics is employed to develop a robust damage classifier. This paper concludes with a numerical example on a 5 degree-of-freedom system and an experimental investigation on a multi-story building model to demonstrate the performance of the proposed concept.

Electromechanical Impedance-Based Structural Health Monitoring with Evolutionary Programming

An impedance-based structural health monitoring technique is presented. By analyzing the in-plane vibration of a thin lead–zirconate–titanate (PZT) patch, the electromechanical impedance of the PZT patch is predicted. The force impedances of a beam and a plate with damage are calculated by Ritz method using polynomial as shape functions. The damage is then identified from the changes of the impedance spectra caused by the appearance of damage. A hybrid evolutionary programming is employed as a global search technique to back-calculate the damage. A specially designed fitness function is proposed, which is able to effectively reduce the inaccuracy in representing the real structure using analytical or numerical models. Experiments are carried out on a beam and a plate to verify the numerical predictions. The results demonstrate that the proposed method is able to effectively and reliably locate and quantify the damage in the beam and the plate.

Detecting Damage in Graphite/Epoxy Composites Using Impedance-Based Structural Health Monitoring

The impedance-based structural health monitoring method is used to successfully detect different damage mechanisms in composites and to correlate the changes in impedance measurements with the changes in the structure. Specifically, graphite/epoxy composite samples are manufactured and tested. Piezoceramic (PZT) patches are attached to the composite coupons to actuate the structure with high-frequency excitations. Bonding the patches to the sample allows changes in the structural mechanical impedance to be monitored with the electrical impedance of the PZT. Samples are tested using quasi-static tensile loading to introduce damage. To determine the extent of damage incurred, impedance signatures are acquired before and after the tensile load is applied. A change in impedance from the baseline shows the presence of damage. The amount of damage is characterized using a damage metric. Radiography is used to verify the extent of damage.

Improving Accessibility of the Impedance-Based Structural Health Monitoring Method

This paper presents current research on impedance-based structural health monitoring technique. The basic principle behind this technique is to apply high-frequency structural excitations (typically higher than 30 kHz) through the surface-bonded piezoelectric transducers, and measure the impedance of structures by monitoring the current and voltage applied to the piezoelectric transducers. Changes in impedance indicate changes in the structure, which in turn can indicate that damage has occurred. Three examples, including a bolted joint, gas pipeline, and composite structure, are presented to illustrate the effectiveness of this health monitoring technique to a wide variety of practical field applications. Although many proof-of-concept experiments have been performed using the impedance methods, the impedance-measuring device (HP4194A) is still bulky and expensive. Therefore, an operational amplifier-based turnkey device that can measure and record the electric impedance of a PZT has been developed. The performance of this miniaturized and portable device has been compared to our previous results and its effectiveness has been demonstrated. This paper summarizes the experimental setup, procedures, and considerations needed to implement the device in field applications.

Overview of Piezoelectric Impedance-Based Health Monitoring and Path Forward

In this paper we summarize the hardware and software issues of impedance-based structural health moni- toring based on piezoelectric materials. The basic concept of the method is to use high-frequency structural excitations to monitor the local area of a structure for changes in structural impedance that would indicate imminent damage. A brief overview of research work on experimental and theoretical stud- ies on various structures is considered and several research papers on these topics are cited. This paper concludes with a discussion of future research areas and path forward. Piezoelectric materials acting in the manner pro- duce an electrical charge when stressed mechanically. Con- versely, a mechanical strain is produced when an electrical field is applied. The direct piezoelectric effect has often been used in sensors such as piezoelectric accelerometers. With the converse effect, piezoelectric materials apply local- ized strains and directly influence the dynamic response of the structural elements when either embedded or surface bonded into a structure. Piezoelectric materials have been widely used in structural dynamics applications because they are lightweight, robust, inexpensive, and come in a variety of forms ranging from thin rectangular patches to complex shapes being used in microelectromechanical systems (MEMS) fabrications. The applications of piezoelectric mate- rials in structural dynamics are too numerous to mention and are detailed in the literature (Niezrecki et al., 2001; Chopra, 2002). The purpose of this paper is to explore the importance and effectiveness of impedance-based structural health mon- itoring from both hardware and software standpoints. Imped- ance-based structural health monitoring techniques have been developed as a promising tool for real-time structural dam- age assessment, and are considered as a new non-destructive evaluation (NDE) method. A key aspect of impedance-based structural health monitoring is the use of piezoceramic (PZT) materials as collocated sensors and actuators. The basis of this active sensing technology is the energy transfer between the actuator and its host mechanical system. It has been shown that the electrical impedance of the PZT material can be directly related to the mechanical impedance of a host structural component where the PZT patch is attached. Uti- lizing the same material for both actuation and sensing not only reduces the number of sensors and actuators, but also reduces the electrical wiring and associated hardware. Fur- thermore, the size and weight of the PZT patch are negligible compared to those of the host structures so that its attach- ment to the structure introduces no impact on dynamic char- acteristics of the structure. A typical deployment of a PZT on a structure being monitored is shown in Figure 1. The first part of this paper (Sections 2 and 3) deals with the theoretical background and design considerations of the impedance-based structural health monitoring. The signal processing of the impedance method is outlined in Section 4. In Section 5, experimental studies using the impedance approaches are summarized and related previous works are listed. Section 6 presents a brief comparison of the imped- ance method with other NDE approaches and, finally, sev- eral future issues are outlined in Section 7. 2. Theoretical Background

Experimental research on evaluating structure damage with piezoelectric dynamic impedance

A dynamic impedance-based structural health monitoring technique is introduced. According to the direct and the converse piezoelectric property of piezoelectric materials, the piezoceramic ( PZT ) can be used as an actuator and a sensor synchronously. If damages like cracks, holes, debonding or loose connections are presented in the structure, the physical variations of the structure will cause the mechanical impedance modified. On the basis of introducing the principle and the theory, the experiment and the analysis on some damages of the structure are studied by means of the dynamic impedance technique. On the view of experiment, kinds of structural damages are evaluated by the information of dynamic impedance in order to validate the feasibility of the method.

Impedance-Based Structural Health Monitoring with Artificial Neural Networks

Impedance-Based Structural Health Monitoring with Artificial Neural Networks

Impedance-Based Structural Health Monitoring with Artificial Neural Networks

This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based structural health monitoring technique, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations (typically >30 kHz), this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors. In order to quantitatively assess the state of structures, multiple sets of artificial neural networks, which utilize measured electrical impedance signals for input patterns, were developed. By employing high frequency ranges and by incorporating neural network features, this technique is able to detect the damage in its early stage and to estimate the nature of damage without prior knowledge of the model of structures. The paper concludes with experimental examples, investigations on a massive quarter scale model of a steel bridge section and a space truss structure, in order to verify the performance of this proposed methodology.

Impedance-Based Structural Health Monitoring for Temperature Varying Applications.

A new structural health monitoring technique capable of in-service, on-line incipient damage detection has been proposed by the Center for Intelligent Material Systems and Structures, Physical changes in a structure cause changes in the mechanical impedance. Due to the electromechanical coupling in piezoelectric materials, this change causes a change in the electrical impedance of the piezoelectric sensor. Hence, by monitoring the electrical impedance and comparing this to a baseline measurement, we can determine when structural damage has either occurred or is imminent. However, in almost all practical health monitoring applications, the structure being monitored is constantly undergoing change due to the effect of external boundary conditions. One of the important factors that leads to this change is the temperature variations. In this paper, temperature effects on the electrical impedance of piezoelectric materials and the structures have been investigated. A computer algorithm was developed which incorporates temperature compensation into our health monitoring applications. Three experimental investigations were performed successfully under the temperature varying condition, in the range of 25 to 75°C, including a bolted pipe structure, composite reinforced aluminum and precision part such as gears. It was found that, by this compensation procedure, the impedance based health monitoring tehcnique is able to detect damage in the incipient stage, even with the presence of significant temperature variation.