Structural Health Monitoring Methodology Research Articles

Delamination detection in composites using wave modulation spectroscopy with a novel active nonlinear acousto-ultrasonic piezoelectric sensor

A novel structural health monitoring (SHM) methodology, based on nonlinear wave modulation spectroscopy, is presented for the detection of delamination cracks in composites. The basic element is a novel active nonlinear acousto-ultrasonic piezoelectric sensor enabling low-cost and wide-frequency operational bandwidth. The active sensor configuration involves two piezoceramic wafer actuators, each one excited with a low- and high-frequency signal respectively, and a piezoceramic sensor, all permanently bonded on the tested structure. Experiments are conducted on two sets of composite strips containing delamination cracks of different sizes. Measured results illustrate first the efficiency of the nonlinear ultrasonics methodology to detect delamination cracks, as well as, the potential and benefits of the new active sensor. The sensitivity of the active sensor response to the crack size and the applied high-frequency carrier signals at the actuators, vary at various frequency and voltage levels indicating the appropriate testing setup. Additionally repeatability of proposed SHM methodology is studied.

Application of System-Identification Techniquest to Health Monitoring of On-Orbit Satellite Boom Structures

The integration of composites into spacecraft is challenged by the risk of damage initiation andpropagation during storage, launch, and service life. Elastically deployable composite booms are being developed for space utility.Matrix cracks are considered a primary form of damage caused by packaging before launch. However, while on orbit, most damages are induced by the environmental effects on the polymers. A well-developed structural health monitoring system will provide information for the dynamic control of the satellite and the condition of the deployable mechanisms on the space vehicle. A structural health monitoring methodology, based on the system-identification techniques, is proposed to identify the structural degradation in laminated composite booms. Nondestructive evaluation techniques, frequency-response analysis and autoregressive with exogenous input models are used to approximate the transfer functions between input and output sensing signals. Structural degradation is identified by examining the change of transfer functions at different storage states. A single-input/single-output approach is adopted in this paper. The proposed methodology is validated through experimentation in which matrix cracking is gradually induced by packaging the sample.

Instantaneous baseline structural damage detection using a miniaturized piezoelectric guided waves system

In recent years, new Structural Health Monitoring (SHM) methodologies with a concept of “instantaneous baseline damage detection” are being developed by many researchers since it has been found that the most of SHM technologies are too vulnerable to environmental and/or operational variations. In this context, this paper presents online instantaneous baseline structural damage detection using a low cost and low power, in-situ piezoelectric guided waves-SHM system. Firstly, four small, low cost and light weight smart Piezoelectric Ceramic (PZT) patches are surface-mounted and assumed to have the same bonding conditions to detect structural defects on an aluminum plate. Then, a miniaturized low power guided waves-SHM system with a Digital Signal Processing (DSP) module is employed for signal generation/excitation, signal sensing, and data processing. The instantaneous baseline damage detection based on Wavelet Transform (WT) and Cross Correlation (CC) analysis is carried out on the DSP module. Finally, effects of Lamb waves due to artificial ‘cut-damage’ at different locations are investigated using both “pitch-catch” and “pulse-echo” wave propagation schemes. Conclusively, this study shows a good potential for online and in-situ crack monitoring on panel structures such as an aircraft wing.

Damage assessment of structures - an US air force office of scientific research structural mechanics perspective

This paper presents the perspective of the Structural Mechanics program of the Air Force Office of Scientific Research (AFOSR) on the damage assessment of structures for the period 2006-2009 when the author was serving as Program Manager at AFOSR. It is found that damage assessment of structures plays a very important role in assuring the safety and operational readiness of US Air Force fleet. The current fleet has many aging aircraft, which poses a considerable challenge for the operators and maintainers. The nondestructive evaluation technology is rather mature and able to detect damage with considerable reliability during the periodic maintenance inspections. The emerging structural health monitoring methodology has great potential, because it will use on-board damage detection sensors and systems, will be able to offer on-demand structural health bulletins. Considerable fundamental and applied research is still needed to enable the development, implementation, and dissemination of structural health monitoring technology.

Manufacturing and testing composite overwrapped pressure vessels with embedded sensors

In this research programme, methodologies for structural health monitoring (SHM) of composite overwrapped pressure vessels (COPV) were addressed. So, this work is part of the development of a COPV laboratorial prototype incorporated with non-destructive sensing technologies. The aim is to detect and identify critical aspects that can happen during operation, in order to reduce possible safety problems. Fibre Bragg grating (FBG) optical sensors and polyvinylidene fluoride (PVDF) polymeric piezoelectric were the selected sensing technologies. These sensors were embedded in the liner–composite interface during its manufacturing and monitored the prototype while tested under cyclic internal pressure loading. The measurements collected from the sensors were compiled with the analysis of test data and are presented in this paper. Also, the suitability of the two sensing technologies, issues related to sensor embedding and the monitoring strategy are discussed.

Structural Health Monitoring for Civil Structures: From the Lab to the Field

The field of structural health monitoring (SHM) is rapidly growing to provide robust diagnosis and prognosis of many engineering systems spanning from civil and transportation infrastructures to aerospace and military applications. The development and deployment of a robust SHM scheme is pivotal to ensure the safe and cost-effective operation of any engineering system. SHM is mainly a process of (i) observing or tracing the performance of an engineering structure/system under environmental and operational loads by sensors and instrumentation devices, (ii) evaluating the performance of the structure/system for any development of defect or damage by use of the measured data and analytical tools, and (iii) issuing an alarm when the designated performance criteria are exceeded. Compared to other engineering fields, the research on SHM is relatively young and therefore most of the work has been conducted at universities or companies that have an interest in research and development. This special issue of the journal is mainly dedicated to those SHM strategies that after being successfully proven in the laboratory were or are currently deployed in the field for field testing and validation. This special issue contains twelve research papers and three review articles. The topics dealt with in these papers cover a wide variety of SHM methodologies (in alphabetical order): acoustic emission, electromechanical impedance, fiber optics, guided ultrasonic waves, imaging, time-domain reflectometry, and vibration measurements. These methods are applied to one of the following: (1) detection of damage in an ASCE benchmark structure, composite materials, concrete structures, dikes, precast concrete box girders railroads, and water and wastewater pipelines; (2) evaluation bridge scour; (3) measurement of stress or strain in oil and gas pipes, concrete structures, or cables; (4) detection of low to medium energy impact in wind turbine blades; (5) detection of water leaks; (6) identification of modal parameters; (7) measurement of vibration of high-rise reinforced concrete building. Thanks are given to the issue’s guest editors Dr. Yi Qing Ni from The Hong Kong Polytechnic University and Dr. Jinying Zhu from The University of Texas for help in soliciting papers, keeping track of submissions, reviews, rebuttals, and followups. Also, special thanks go to Dina Attia for help in the organization of the accepted papers and the final production of the special issue.

Extracting guided waves from cross-correlations of elastic diffuse fields: Applications to remote structural health monitoring

Due to their apparent complexity, diffuse fields are not commonly used by conventional structural health monitoring methodologies. However, recent theoretical and experimental studies have demonstrated that local Green's functions (GFs) can be estimated from the cross-correlation of elastic diffuse fields (CDFs) recorded between any points of a sensor grid and generated by sources located remotely from the monitoring area. Hence, this CDF technique effectively transforming each measurement point into a virtual elastic source, thus allowing to measure the local structural response (or GF). Theoretical and experimental studies are conducted to assess the broadband performance of the CDF technique for the extraction of low-frequency coherent Lamb waves (4-90 kHz) propagating in a thin aluminum plate of complex geometry using a scanning laser Doppler vibrometer. The coherent signal-to-noise ratio and the accuracy of the phase and group velocity measurements of the coherent A(0) mode obtained from CDF are also measured to quantify the influence of the spatio-temporal characteristics of the recorded diffuse field, the number and spatial configuration of the remote ultrasonic sources, and the influence of incoherent measurement noise (e.g., sensor noise). In addition, a criterion to assess the emergence rate of late coherent coda arrivals from CDF is also formulated.

450 非線形電気機械インピーダンス変調法 : き裂を有するはりのモデル化と解析(構造物および機械の診断,OS-11 システムのモニタリングと診断,総合テーマ「伝統を,未来へ!」)

In this paper, a nondestructive, self-sensing, baseline free structural health monitoring methodology is presented, based on a nonlinear piezoelectric impedance modulation phenomenon which is induced by the contact acoustic nonlinearity (CAN) at the local structural damages of contact-type, i.e. damages and failures which come along with generation, growth and/or changes of contacting surfaces, such as cracks, debonding, preload-loss in bolted joints, etc. For an illustrative example, a mathematical model of a straight beam including a single transverse crack, coupled with a surface- bonded piezoelectric element is derived, utilizing the linear time- varying system theory. The time-varying admittance of the piezoelectric element is formulated in terms of a Zadeh's time-varying transfer function, and its first and second-order approximation is derived. The appropriateness of the first-order approximate which is called frozen-parameter solution is then discussed, and a damage evaluation index is presented based on this solution.

Seismic Interferometry of a Soil-Structure Interaction Model with Coupled Horizontal and Rocking Response

This article presents a system identification analysis of a soil-structure interaction model with coupled horizontal and rocking response based on a combination of Fourier analysis, wave travel-time analysis, and a relationship between fixed-base, rigid-body, and system frequencies. The study provides insight into the coupling of the structural and soil vibrations useful for interpretation of seismic recordings in structures. The structural model captures one-dimensional shear-wave propagation in the structure. The analysis shows that the system functions with respect to foundation horizontal motion are those of the coupled soil-structure system, which differs from conclusions of earlier studies based on a model without foundation rocking. The energy of the system vibrational response is concentrated around the frequencies of vibration of the system, which depend on the properties of the structure, soil, and foundation. The analysis shows that the structural fundamental fixed-base (uncoupled) frequency f 1 is related to the wave travel time τ (from the base to the top) by f 1=1/(4 τ ) and that accurate measurement of τ , unaffected by soil-structure interaction, can be obtained from impulse response functions, provided that the data are sufficiently broadband. This is an important result for structural health monitoring because it shows that structural parameters unaffected by soil-structure interaction ( τ , as well as f 1 for structures deforming primarily in shear) can be estimated from seismic monitoring data with minimum instrumentation (two horizontal sensors, one at the base and one at the top). This extends the usability of old strong-motion data in buildings, most of which have not been extensively instrumented, and lessons that can be learned for development and validation of structural health monitoring methodologies. The presented results correspond to a model of the north–south response of the Millikan Library in Pasadena, California, which has become a classical case study for soil-structure interaction.

123 非線形圧電インピーダンス変調とき裂モニタリングヘの応用

This paper concerns a structural health monitoring (SHM) methodology that can detect and characterize local structural damages in early stage, developed by combining the concepts of two existing SHM principles, a piezoelectric impedance-based methodology and a nonlinear wave modulation spectroscopy. When the structure is subjected to a dynamic load at low-frequencies, the nonlinear vibro-acoustic interaction between the low-frequency vibration and the high-frequency wave field in the vicinity of "contact-type" damages causes the change in the driving-point mobility at the high frequency range. Therefore, if the piezoelectric element bonded on the structural surface is driven by a fixed amplitude high-frequency harmonic voltage source, the nonlinear modulation of the coupled electro-mechanical admittance can be observed as the amplitude and phase modulation of the current flowing through the piezoelectric element. A simplified modeling study of this phenomenon successfully leads to a damage evaluation index that assesses the intensity of the modulation of the modal stiffness. Experiments using a cracked beam are conducted to see how the stiffness modulation can be observed and to examine the performance of the proposed method.

Stochastic change detection in uncertain nonlinear systems using reduced-order models:classification

A reliable structural health monitoring methodology (SHM) is proposed to detect relativelysmall changes in uncertain nonlinear systems. A total of 4000 physical tests were performedusing a complex nonlinear magneto-rheological (MR) damper. With the effective (or‘genuine’) changes and uncertainties in the system characteristics of the semi-active MRdamper, which were precisely controlled with known means and standard deviation of theinput current, the tested MR damper was identified with the restoring force method(RFM), a non-parametric system identification method involving two-dimensionalorthogonal polynomials. Using the identified RFM coefficients, both supervised andunsupervised pattern recognition techniques (including support vector classification andk-means clustering) were employed to detect system changes in the MR damper. Theclassification results showed that the identified coefficients with orthogonal basis functioncan be used as reliable indicators for detecting (small) changes, interpreting the physicalmeaning of the detected changes without a priori knowledge of the monitoredsystem and quantifying the uncertainty bounds of the detected changes. Theclassification errors were analyzed using the standard detection theory to evaluate theperformance of the developed SHM methodology. An optimal classifier designprocedure was also proposed and evaluated to minimize type II (or ‘missed’) errors.

Genetic optimisation of a neural network damage diagnostic

AbstractThis paper presents an automated optimisation procedure for the feature selection stage of a previously proposed structural health monitoring methodology using a genetic algorithm. The same diagnostic is used in the attempt to progress up the levels of damage detection to location and severity. It was validated experimentally on a Gnat aircraft wing. An artificial neural network is used as a classifier and the work is compared with the previous selection strategy based on engineering judgement.

Development and validation of a strain-based Structural Health Monitoring system

An innovative Structural Health Monitoring (SHM) methodology, based on structural strain measurements, which are processed by a back-propagation feed-forward Artificial Neural Network (ANN), is proposed. The demonstration of the SHM methodology and the identification of its capabilities and drawbacks are performed by applying the method in the prediction of fatigue damage states of a typical aircraft cracked lap-joint structure. An ANN of suitable architecture is developed and trained by numerically generated strain data sets, which have been preprocessed by Fast Fourier Transformation (FFT) for the extraction of the Fourier Descriptors (FDs). The Finite Element (FE) substructuring technique is implemented in the stress and strain analysis of the lap-joint structure, due to its efficiency in the calculation of the numerous strain data, which are necessary for the ANN training. The trained network is successfully validated, as it is proven capable to accurately predict crack positions and lengths of a lap-joint structure, which is damaged by fatigue cracks of unknown location and extent. The proposed methodology is applicable to the identification of more complex types of damage or to other critical structural locations, as its basic concept is generic.

Stochastic change detection in uncertain nonlinear systems using reduced-order models:system identification

The reliable detection of relatively small changes in the characteristics of monitoredsystems, which simultaneously involve nonlinear phenomena as well as uncertainparameters, is a challenging problem whose resolution is crucial to the development ofpractical structural health monitoring methodologies slated for use with complex physicalsystems. This paper reports the results of a comprehensive experimental study involving anadaptive nonlinear component (an actively controlled magnetorheological damper) thatwas used to investigate the representation and propagation of uncertainties in aprobabilistic format that provides a convenient means for reliable detection ofsmall changes in uncertain nonlinear systems. In experimental studies of the MRdamper, the uncertainty of the system characteristics was precisely controlled withknown input-current statistics. A total of 4000 tests were performed, and the MRdamper was identified using the restoring force method with both orthogonal andnon-orthogonal basis functions. The identification results show that the identifiedcoefficients involving orthogonal basis functions have several desirable features that areideal for condition assessment purposes when dealing with complex nonlinearsystems whose underlying physics is not amenable to easy modeling: (1) no a prioriknowledge of the systems characteristics is required; (2) the orthogonal coefficients arestatistically unbiased with respect to model complexity; and (3) the distributions ofthe orthogonal coefficients can be reliably used to detect changes in uncertainnonlinear systems, even if a reduced-order model is used in the identificationprocess.

Application of Structural Health Monitoring Techniques to Track Structural Changes in a Retrofitted Building Based on Ambient Vibration

One of the issues complicating the reliability assessment of structural health monitoring (SHM) methodologies slated for implementation under field conditions for damage detection in conjunction with typical infrastructure systems, is the paucity of experimental measurements from such structures. Particularly lacking is the availability of experimental data from physical structures, where quantifiable changes are made in the structure while SHM studies are being performed. That is precisely the focus of this paper. As a result of the 1994 Northridge Earthquake, a critical six-story building in the metropolitan Los Angeles region was found to need significant seismic mitigation measures. The building was instrumented with 14 state-of-the-art strong-motion accelerometers that were placed at various locations and in different orientations throughout the building. The instrumentation network was used to acquire extensive ambient vibration data sets at regular intervals that covered the whole construction phase, during which the building evolved from its original condition to the retrofitted status. This paper evaluates the usefulness of the natural excitation technique (NExT) in conjunction with the eigensystem realization algorithm (ERA) to determine the evolution of the modal properties of the subject building during the various phases of its retrofit process. Further, an assessment is made of the influence on the system identification results of significant user-selectable parameters such as: data window size and overlap; reference degree-of-freedom; and the dimensions of the associated Hankel matrix. In spite of the very low levels of ambient excitation, and the low spatial resolution of the sensors, use of the NExT/ERA algorithm yielded excellent identification results of the dominant modes of the building. Changes in the identified structural frequencies are correlated with the time that specific structural changes were made. It is shown that this unique collection of data can be extremely useful in calibrating the accuracy and sensitivity of various SHM schemes, as well as in providing useful identification parameter guidelines that can assist in the planning and deployment of sensor networks and associated data collection schemes for SHM applications.

Damage Assessment of Structures - An Air Force Office of Scientific Research Structural Mechanics Perspective

This paper presents the perspective of the Structural Mechanics program of the Air Force Office of Scientific Research on the damage assessment of structures. It is found that damage assessment of structures plays a very important role in assuring the safety and operational readiness of Air Force fleet. The current fleet has many aging aircraft, which poses a considerable challenge for the operators and maintainers. The nondestructive evaluation technology is rather mature and able to detect damage with considerable reliability during the periodic maintenance inspections. The emerging structural health monitoring methodology has great potential, because it will use on-board damage detection sensors and systems, will be able to offer on-demand structural health bulletins. Considerable fundamental and applied research is still needed to enable the development, implementation, and dissemination of structural health monitoring technology.

Genetic fuzzy system for online structural health monitoring of composite helicopter rotor blades

A structural health monitoring (SHM) methodology is developed for composite rotor blades. An aeroelastic analysis of composite rotor blades based on the finite element method in space and time and with implanted matrix cracking and debonding/delamination damage is used to obtain measurable system parameters such as blade response, loads and strains. A rotor blade with a two-cell airfoil section and [ 0 / ± 45 / 90 ] s family of laminates is used for numerical simulations. The model based measurements are contaminated with noise to simulate real data. Genetic fuzzy systems (GFS) are developed for global online damage detection using displacement and force-based measurement deviations between damaged and undamaged conditions and for local online damage detection using strains. It is observed that the success rate of the GFS depends on number of measurements, type of measurements and training and testing noise level. The GFS work quite well with noisy data and is recommended for online SHM of composite helicopter rotor blades.

Structural Health Monitoring via Measured Ritz Vectors Utilizing Artificial Neural Networks

Abstract: A pattern recognition approach for structural health monitoring (SHM) is presented that uses damage-induced changes in Ritz vectors as the features to characterize the damage patterns defined by the corresponding locations and severity of damage. Unlike most other pattern recognition methods, an artificial neural network (ANN) technique is employed as a tool for systematically identifying the damage pattern corresponding to an observed feature. An important aspect of using an ANN is its design but this is usually skipped in the literature on ANN-based SHM. The design of an ANN has significant effects on both the training and performance of the ANN. As the multi-layer perceptron ANN model is adopted in this work, ANN design refers to the selection of the number of hidden layers and the number of neurons in each hidden layer. A design method based on a Bayesian probabilistic approach for model selection is proposed. The combination of the pattern recognition method and the Bayesian ANN design method forms a practical SHM methodology. A truss model is employed to demonstrate the proposed methodology.

A methodology for structural health monitoring with diffuse ultrasonic waves in the presence of temperature variations

Diffuse ultrasonic waves for structural health monitoring offer the advantages of simplicity of signal generation and reception, sensitivity to damage, and large area coverage; however, there are the serious disadvantages of no accepted methodology for analyzing the complex recorded signals and sensitivity to environmental changes such as temperature and surface conditions. Presented here is a methodology for applying diffuse ultrasonic waves to the problem of detecting structural damage in the presence of unmeasured temperature changes. This methodology is based upon the prediction and observation that the first order effect of a temperature change on a diffuse ultrasonic wave is a time dilation or compression. A multi-step procedure is implemented to (1) record a set of baseline waveforms from the undamaged specimen at temperatures spanning the expected operating range, (2) select a waveform from the baseline set whose temperature is the closest to that of a subsequently measured signal, (3) adjust this baseline waveform to best match the signal, and (4) calculate an error parameter between the signal and the adjusted waveform and compare this parameter to a threshold to determine the structural status. This procedure is applied to experimental data from aluminum plate specimens with artificial flaws. Probability of detection and the minimum flaw size detected are presented as a function of the size of the baseline waveform set. It is shown that a probability of detection of over 95% can be achieved with a small number of baseline waveforms.

Two-Stage Structural Health Monitoring Approach for Phase I Benchmark Studies

This paper presents a two-stage structural health monitoring methodology and applies it to the Phase I benchmark study sponsored by the IASC-ASCE Task Group on Structural Health Monitoring. In the first stage, modal parameters are identified using measured structural response from the undamaged system and then from the (possibly) damaged system. In the second stage, these data are used to update a parametrized structural model of the system using Bayesian system identification. The approach allows one to obtain not only estimates of the stiffness parameters but also the probability that damage in any substructure exceeds any specified threshold expressed in terms of a fractional stiffness loss. It successfully identifies the location and severity of damage in all cases of the benchmark problem.