Damage In Plate-like Structures Research Articles

Polar coordinate-based guided wave beamforming imaging using scanning LDV

In this paper, we propose a technique for efficiently detecting damage in plate-like structures using guided waves, polar coordinate-based beamforming imaging, and filtering techniques. The proposed technique uses a laser Doppler vibrometer and a scanning mirror-tilting device for ultrasonic wave imaging, with single-frequency excitation provided by a mounted piezoelectric transducer. Frequency-wavenumber domain filtering and directional filtering are implemented in polar coordinates for efficient detection of damage-reflected waves by removing any incident wave components. The filtered waves are then processed using a delay-and-sum beamforming algorithm within local-area laser scanning through a circular array sensing system. The polar coordinate-based laser scanning system improves the damage detection capability and processing time by removing the need for coordinate transformation in frequency-wavenumber domain filtering and directional filtering. Finally, the proposed technique is validated through experiments on composite and aluminum plates with various types of damage, where it demonstrates improved accuracy and speed when estimating the exact damage location.

Experimental and Numerical Study on Vibration-Based Damage Detection and Localization in Laminated Composite Plates

Damage detection in composite materials is crucial for ensuring the safety and reliability of engineering structures. Conventional methods often face challenges in accurately identifying damage in plate-like structures, particularly in scenarios involving multiple damages or small-scale delamination. This study focuses on investigating the detection and localization of delamination in composite plates by employing both experimental and numerical modal analysis. An eight-ply woven Glass-Epoxy composite laminate with and without damage was prepared with the aid of hand lamination technique. Laminate was fixed to a Clamped-Free-Free-Free (CFFF) boundary condition for experimental modal analysis by introducing controlled damage to examine its impact on modal properties. To validate the natural frequencies (NFs) of damaged and undamaged composite laminates, a numerical analysis was conducted using ANSYS Parametric Design Language (APDL). Further, to advance the understanding of using modal shapes and their spatial derivatives for damage localization in composite plates under various damage situations, post-processing of simulation results was conducted using MATLAB. Finite Difference Method has been employed to calculate the derivatives, and a novel damage index (DI) is proposed to enhance damage localization capabilities. The results affirm that the proposed DI is effective and precise in identifying damage in plate-like structures, both for individual and multiple damage scenarios. This research study presents a novel approach for identifying and pinpointing damage in composite plates, thereby making a valuable contribution to the field of structural health monitoring (SHM) applications

Feature extraction and visualization for damage detection on adhesive joints, utilizing lamb waves and supervised machine learning algorithms

In recent years, the aeronautical industry has grown with the adoption of new materials for structural applications, and adhesives emerged as an alternative to standard methods to join parts. This has sparked the use of nondestructive testing and structural health monitoring methods, namely, those based on Lamb waves to assess the integrity of structures and detect damage. Methods using time-series sensor data and machine learning algorithms have shown great promise in classifying the extent of damage in plate-like structures. Despite this, robust methods are still missing for choosing relevant features of Lamb waves that optimize the learning process to classify damage. In this paper, a powerful time-series specialized feature extraction method is implemented to detect and classify weak adhesion, meaning a zero-volume defect denoting any intermediate level of adhesion between complete adhesion and kissing bond. Initially, over 75 different types of features, with varying internal parameters, are extracted from raw data. Then, using the Benjamini-Hochberg procedure, some of these features are selected as relevant for the damage classification problem. After the initial selection, the features are handled with machine learning techniques, namely the Naïve Bayes and random forest classifiers, which not only lead to high classification metrics using all features, but also reveal and isolate those features that yield the best differentiation between damage categories. The selection methodology accounts for robustness by utilizing different layers of selection and classification, validating the feature relevance in relation to the appropriate set of classes. As such, different damage types and ranges can be adopted in the proposed multi-class classification pipeline.

Lamb wave imaging with actuator network for damage quantification in aluminum plate structures

Lamb waves have been widely used for damage detection on plate-like structures. However, there are still considerable interests on quantifying damage with complex profile. In this article, quantification of complex damage in plate-like structures using a network of actuators and time-space Lamb wavefield is investigated. The actuator network inspection system is implemented with multiple PZT transducers for Lamb wave actuation in round robin pattern and scanning laser Doppler vibrometer for wavefield sensing. The PZT network is arranged in a way that the target area is fully enclosed and Lamb waves come to the damage from all directions. Waves induced by the damage are subsequently obtained through frequency-wavenumber filtering, using the experimentally acquired dispersion curves presented in the paper. The filtered waves from all wave actuators are then used to generate a synthetic image of the damage being inspected. Two cases of complex damage are evaluated on aluminum plates, mass loss with triangular profile and mass addition with a three-letter cluster profile. Our results show that the damages are not only detected but also their profiles are clearly outlined in the images. We believe the subject methods provide improved evaluation of damage profile for Lamb wavefield based damage quantification.

Localized damage identification in plate-like structures using self-powered sensor data: A pattern recognition strategy

This study presents a novel strategy for localized damage identification in plate-like structures based on the binary data provided by self-powered wireless sensors that use a pulse switching communication architecture. The energy-aware pulse switching communication architecture uses single pulses instead of multi-bit packets for information delivery resulting in discrete binary data. A system employing such an energy-efficient technology requires dealing with power budgets for sensing and communication that leads to unique time delay constraints. This paper presents a new paradigm for localized damage detection using time-delayed and sometimes limited binary data. The binary data from the sensor nodes resembles an image, or pattern. Data analysis using pattern recognition (PR) framework incorporating PR methods and a conditional probability chain is thus presented. Numerous features extracted from cumulative acceleration on dynamically loaded plates are used to determine damage indication parameters. Performance of the proposed damage detection strategy was evaluated through finite element simulations for the case of a simply supported aluminum plate under distributed harmonic loading. Different damage states were considered to calibrate the damage detection algorithm, and an uncertainty analysis was performed by superposing random noise to the input vectors. Results show that the proposed PR framework is capable of identifying damage even in the presence of high noise levels. The findings demonstrate satisfactory performance of the localized damage detection strategy, and the applicability of PR to detect and localize damage in plate-like structures from the time-delayed binary data generated by self-powered sensors.

Plate-like structures damage detection based on static response and static strain energy using gaussian process regression (GPR)

This study investigates the applicability of an emergent learning algorithm called Gaussian process regression (GPR) algorithm to predict damage in plate-like structures as an inverse problem. The presented method is based on static responses and static strain energy as input parameters to GPR model. The performance of the presented methods has been evaluated using two numerical examples, namely, four fixed and cantilever plates. Also, an examination has been performed in which only translational DOFs are selected as measured DOFs. In another work, the effect of noise in static data has been investigated. The model results were compared using mean square errors. The obtained results show the effectiveness of GPR in damage detection and estimation of plate-like structures using static data which may be noisy.

Phase Congruency for damage mapping with guided wavefields

The Phase Congruency for damage mapping method utilizes full guided wavefield measurements to visualize the extent of subsurface damage in plate-like structures. The method exploits the phase of wavefield components calculated from a filter bank decomposition of the wavefield in space. Testing for alignment of phase between components over the measurement domain generates a plot of discontinuities in the wavefield. Discontinuities in the wavefield indicate the existence and extent of damage in the specimen considered. Damage maps for a host of cases ranging from simple changes in thickness to complex impact damage are presented.

Mode shape-based damage detection in plate structure without baseline data

In this paper, a mode shape curvature-based method for detection and localization of damage in plate-like structures is described. The proposed algorithm requires only the mode shape curvature data of the damaged structure. The damage index is defined as the absolute difference between the measured curvature of the damaged structure and the smoothed polynomial representing the curvature of the healthy structure. To examine the advantages and limitations of the proposed method, several sets of numerical simulations are carried out. Simulated test cases considering different levels of damage severity, measurement noise and sensor sparsity are studied to evaluate the robustness of the method under the noisy experimental data and limited sensor data. Applicability and effectiveness of the proposed damage detection method are further demonstrated experimentally on an aluminium plate containing mill-cut damage. The modal frequencies and the corresponding mode shapes are obtained via finite element models for numerical simulations and by using a scanning laser vibrometer for the experimental study. Copyright © 2016 John Wiley & Sons, Ltd.

A comparison and extensions of algorithms for quantitative imaging of laminar damage in plates. I. Point spread functions and near field imaging

Real-time structural health monitoring (SHM) and safety prognostics require quantitative and continuously updated information on damage size and severity. A unified theoretical solution is presented for three distinct approaches that have been used for in situ imaging of structural damage in plate-like structures. These approaches are based on (i) linearised inverse scattering (or generalised diffraction tomography), (ii) beamforming, and (iii) reverse time migration. In all three approaches, the damaged region is regarded as a weak scatterer. Such an approach is appropriate for early damage detection that is of great practical interest. The linearised inverse is based on a rigorous mathematical formulation, whereas beamforming and reverse time migration are based on heuristic arguments, but the latter are more convenient for practical implementation. It is shown that, in the far-field approximation, the three imaging algorithms have a very similar mathematical structure. Analytical expressions are derived for the point spread functions (PSFs), which represent the reconstructed image for a point-like scatterer. Although the analytical expressions for the PSFs are different, the corresponding profiles are virtually identical. Based on these observed mathematical similarities, modified versions of the diffraction tomography and time-reversal algorithms are presented that combine the advantages of the various approaches. These modified algorithms are extensively evaluated using analytical solutions of a circular scatterer. The resulting algorithms are shown to provide accurate estimates for damage size and damage severity over a range of size and severity that is consistent with the weak scatterer approximation.

Tikhonov's regularization approach in mode shape curvature analysis applied to damage detection

In this paper an on-going research effort aimed at detecting and localizing damage in plate-like structures by using mode shape curvature based damage detection algorithm is described. The proposed damage index uses exclusively mode shape curvature data from the damaged structure. This method was originally developed for beam-like structures. In this paper, the method is generalized to plate-like structures which are characterized by two-dimensional mode shape curvature. To calculate mode shape curvatures from the measured mode shapes, three approaches are proposed: the first one is the well-known central difference approximation, the other two are classical approaches based on Tikhonov's regularization technique with smoothing functional. The applicability and effectiveness of the proposed damage detection algorithms are demonstrated experimentally on an aluminium plate containing mill-cut damage. The validity of the method is assessed by comparing the identification results of the experimental test case to the results obtained from the simulated test case. The modal frequencies and the corresponding mode shapes of the aluminium plate are obtained via finite element models for numerical simulations and by using a scanning laser vibrometer (SLV) for the experimental study.

Numerical and Experimental Study on the Application of Mode Shape Curvature for Damage Detection in Plate-Like Structures

The paper describes on-going research effort at detecting and localizing damage in plate-like structures using mode shape curvature based damage detection algorithm. The proposed damage index uses data on exclusively mode shape curvature from the damaged structure. This method was originally developed for beam-like structures. The article generalizes the method of plate-like structures characterized by two-dimensional mode shape curvature. To examine limitations of the method, several sets of simulated data are applied and the obtained results of the numerical detection of damage are validated by comparing them with the findings of the case of the experimental test. The simulated test cases include the damage of various levels of severity. In order to ascertain the sensitivity of the proposed method for noisy experimental data, numerical mode shapes are corrupted with different levels of random noise. Modal frequencies and corresponding mode shapes of an aluminium plate containing mill-cut damage are obtained via finite element models for numerical simulations and by using a scanning laser vibrometer (SLV) for the experimental study.

Instantaneous and local wavenumber estimations for damage quantification in composites

The continued and expanded use of composite materials in aerospace applications necessitates structural health monitoring and/or nondestructive evaluation techniques that can provide quantitative and detailed damage information for layered plate-like components (such as composite laminates). Guided wavefield methods are at the basis of a number of promising techniques for the detection and the characterization of damage in plate-like structures. Among the processing techniques that have been proposed for guided wavefield analysis, the estimation of instantaneous and local wavenumbers can lead to effective metrics that quantify the size and the depth of delaminations in composite laminates. This article reports the application of both instantaneous and local wavenumber damage quantification techniques to guided wavefield data for delaminated composite laminates. The techniques are applied to experimental data for a simple single delamination case and to simulated data for a more complex multi-ply delamination case. The two techniques are compared in terms of accuracy in damage characterization and computational demand. The proposed methodologies can be considered as steps toward a hybrid structural health monitoring/nondestructive evaluation approach for damage assessment in composites.

Damage localisation in plate like-structures using the two-dimensional polynomial annihilation edge detection method

The topic of non-destructively detecting localised damage in plates is addressed in this article. Since the presence of a crack or a delamination causes a discontinuity in the mode shape first derivatives, a numerical method for detecting discontinuities in smooth piecewise functions and their derivatives, based on a polynomial-annihilation technique is presented. The method, already proposed for beam-type structures, has been extended to enable the detection and localisation of damage in plate-like structures for which only post-damage mode shapes are available. Applying finite element analysis, the mode shapes of an isotropic plate with a saw-cut and a multi-layered composite plate with a delamination have been calculated and the performance of the approach evaluated for increasing amounts of noise. Encouraging results indicate that further development of the technique for non-destructive testing of plate-like structures would be highly worthwhile.

A particle filter method for damage location in plate-like structures by using Lamb waves

SUMMARY This paper proposes a probabilistic approach for localizing damage in plate-like structures by using particle filter (PF) method with considerations of the uncertainties from modeling and measurement. A piezoelectric sensor network is deployed on the plate-like structures to excite and receive diagnostic Lamb waves before and after damage. The damage-scattered waves that contain characteristic information about the damage are then obtained and used for damage localization. A complex Morlet wavelet transform is employed to highlight the time-of-arrival of the scattered waves in each actuator–sensor path to help measuring the time-of-flight values. After that, damage localization is formulated as a Bayesian state estimation problem with the damage location and the wave velocity as the unknown state parameters. A PF procedure is developed to iteratively estimate the unknown parameters simultaneously. Numerical study for an aluminum plate and experimental study for a stiffened aluminum panel are conducted to demonstrate the effectiveness and applicability of the proposed PF-based localization method. Copyright © 2013 John Wiley & Sons, Ltd.

DAMAGE IDENTIFICATION IN A PLATE-LIKE STRUCTURE USING MODAL DATA

In this paper, an on-going research effort aimed at detecting and localising damage in plate-like structures by using mode shape curvature–based damage detection algorithms is described. Two alternative damage indexes are examined. The first one uses exclusively mode shape curvature data from the damaged structure. This method was originally developed for beam-like structures. In this paper, the method is generalised to plate-like structures that are characterised by two-dimensional mode shape curvature. To examine limitations of the method, several sets of simulated data are applied and damage detection results are compared to the damage identification method that requires mode shape information from both the undamaged and the damaged states of the structure. The modal frequencies and the corresponding mode shapes for the first 15 modes of a plate are obtained via finite element models. Simulated test cases include damage of various levels of severity. In order to ascertain the sensitivity of the proposed method to noisy experimental data, numerical mode shapes are corrupted with different levels of random noise.

Lamb wave damage detection using time reversal DORT method

Among structural health monitoring methods, Lamb waves are frequently used as a diagnostic tool to detect damage in plate-like structures. The decomposition of the time reversal operator (DORT) method is a selective detection and focusing technique using an array of transmit–receive transducers. Unlike body waves, the propagation of Lamb waves is complicated due to their dispersive and multimode characteristics. So it is hard to locate different scatterers on the plate directly using the DORT method because of the asymmetry of the time reversal transfer matrix. In the present paper a damage detection technique to make the transfer matrix symmetric for the Lamb wave DORT method is proposed. It is found that the number of significant eigenvalues is not exactly equal to the number of damage targets and two significant eigenvalues are associated with one damage target. An experiment is carried out to distinguish and locate two simulated points of damage on an aluminum plate. The behavior of reflected multimode waves is analyzed by studying the eigenvalues and eigenvectors of the time reversal operator matrix. This method, which uses a PZT array and operates under multimode pulse-echo mode, can estimate the position of the damage zone in the 2D image by numerically backpropagating a selective eigenvector using the A0 and/or S0 Lamb wave propagation analytical solution. The experimental results illustrate the proposed method.

A Bayesian approach for damage localization in plate-like structures using Lamb waves

This paper presents an investigation of the applicability of a Bayesian system identification theory for localizing damage in plate-like structures, while considering the uncertainties from modeling and measurement. Diagnostic Lamb waves are excited and received by a piezoelectric sensor network before and after damage to obtain scattered waves that contain characteristic information about the damage. After the time-of-flight (ToF) of the scattered waves in each actuator–sensor path is measured by a continuous wavelet transform (CWT), a Bayesian approach is developed to identify the damage location and wave velocity. By combining the prior information and the measured ToF data, Bayes’ theorem is used to update the probability distributions of the parameters about the damage location and wave velocity. In particular, a Markov chain Monte Carlo (MCMC) method is employed for sampling the posterior distributions of the unknown parameters. A numerical study for an aluminum plate and experimental studies for a stiffened aluminum panel and a composite laminate are conducted to validate the proposed Bayesian damage localization approach.

Damage detection in plate-like structures using High-Order mode shape derivatives

This paper investigates the application and reliability of using high-order mode shape derivatives especially, the fourth derivative in damage detection of plate-like structures. Numerical analyses have been carried out for low- and high-order mode shapes of simply supported and cantilever steel plate models. Six scenarios of damages are studied for plate models to represent different damage characteristics. The influence of artificial noise on the damage identification using changes in fourth derivative of mode shapes has been investigated. Based on the numerical studies, it is shown that the fourth derivative of mode shape is promising in detecting and locating structural damage in plate-like structures since it is localized at the damage locations even for a small amount of damage using only one of the mode shapes. Both low- and high-order mode shapes give successful results. Also, damage indices of the fourth derivatives give smoother localization and consequently better damage identification than those of curvature of mode shapes. Furthermore, using high-order modes (which can be measured by advanced sensors) does not improve the results of damage identification using the fourth derivative. Unfortunately, damage detection using changes in fourth derivative of mode shapes is sensitive to measurement noise.

Temperature Influence Compensation for Lamb Wave Damage Detection

Among structural health monitoring (SHM) techniques, Lamb waves is frequently used as diagnostic tools to detect damage in plate-like structures. Temperature variation can cause significant changes in guided-wave propagation and transduction for SHM. In this paper, controlled experiments examine changes in Lamb wave propagation and transduction using PZT-5A piezoelectric wafers under quasi-statically varying temperature (from 5°C to 60°C). The baseline selection method and baseline signal stretch method are used to compensate the temperature influence on Lamb wave propagation. The results of the experiments demonstrate the effectiveness of the temperature compensation approach and the simulated damage on the plate can be detected effectively under elevated temperatures environment.

Correlative sensor array and its applications to identification of damage in plate-like structures

SUMMARY Lamb waves, the guided elastic waves in thin plate/shell structures, have been the core of intensive research for developing cost-effective damage identification techniques over decades. In this regard, appropriate and optimal allocation of actuators and sensors in a sensor array/network is a pivotal concern for achieving sufficient information to describe the damage and meanwhile for minimising interferences of multiple wave modes and complex wave reflection from structural boundaries. An active sensor array comprising a number of miniaturised piezoelectric wafers aligned strategically was developed in the study, named correlative sensor array (CSA) to reflect its mechanism based on signal correlation processing. Using the time differences of different Lamb waves captured by individual array members, a CSA is able to facilitate awareness of structural damage and subsequently to locate it. To ascertain time difference accurately, a signal processing algorithm capitalising on signal correlation and moving-window-based likelihood searching was integrated with the array. The CSA with integrated signal processing algorithm was then numerically and experimentally applied to the identification of a through-thickness hole in an aluminium plate, and the identification results have shown the feasibility and effectiveness of the CSA for pinpointing damage in plate-like structures. As supplement, limitations of CSA-based damage detection in terms of the effective detection area and sensitivity were explored. Copyright © 2011 John Wiley & Sons, Ltd.