Damage Localization In Plates Research Articles

An efficient Lamb wave-based virtual refined time-reversal method for damage localization in plates using broadband measurements

This study proposes a modified virtual time-reversal (VTR) algorithm for baseline signal-free damage detection in plate-like structures. The physical actuation and sensing of Lamb waves are performed using a broadband Gaussian excitation instead of the conventional narrowband modulated tone burst excitations. The forward response and the reconstructed signal due to the time-reversal process for a narrowband input signal are then constructed virtually using the broadband transfer function. The method eliminates the possibility of numerical errors encountered in the conventional VTR method based on narrowband excitations. It is also more efficient than the traditional VTR algorithm because it can probe at multiple excitation frequencies using a single measurement for each sensing path. This modified VTR algorithm is employed in the recently developed refined time-reversal method (RTRM), which uses an extended signal length of the reconstructed signal for computing damage index (DI) and probes the structure at the best reconstruction frequency. The new method is termed the virtual refined time-reversal method (VRTRM). The DIs based on the VRTRM are used in the reconstruction algorithm for probabilistic inspection of defects to achieve baseline signal-free localization of damages. The efficacy of the proposed VRTRM for damage localization is experimentally verified with the established technique RTRM. Experiments are performed in an aluminium plate equipped with a network of surface-bonded piezoelectric patch transducers to illustrate the conventional VTR’s pitfalls and the modified VTR’s accuracy for a single mass damage scenario. The results show that the proposed VRTRM is as accurate as the established technique RTRM in estimating the reconstructed signals and localizing a block mass damage. Finally, the VRTRM is shown to localize in a dual damage scenario with excellent accuracy. In contrast, the conventional main mode-based VTR method fails to localize the damages with or without single-mode tuning.

Effective combination of modeling and experimental data with deep metric learning for guided wave-based damage localization in plates

Data-driven methods have emerged as promising approaches for guided wave-based damage localization. The success of the methods highly depends on the amount and the quality of the training data. Modeling training data are easy to obtain and abundant but could be unrealistic with biased model parameters and experimental uncertainties unconsidered. Experimental training data are realistic but scanty due to the high cost and low accessibility. To tackle this problem, this work utilizes both types of data to collect sufficient training data and learn a mapping function invariant to the modeling errors and experimental noises in a supervised manner, and thus to improve localization accuracy. Specifically, deep metric learning is conducted on the hybrid data to identify a distance metric, based on which the discrepancy between two sets of data is minimized, i.e., the distance metric is insensitive to the superfluous variations caused by modeling errors and experimental noises. Then, a representative non-parametric regression algorithm that relies on the distance metric, kernel regression, is used to predict damage locations. The performance of the proposed method is demonstrated on damage localization in plates and compared with several other data-driven methods. Results show that that proposed method can serve as a general strategy to overcome the shortage of labelled training data in data-driven methods for damage localization.11The data and code related to this article can be found at https://github.com/amazingheart/TensorFlow-implementation-of-deep-metric-learning.

Structural Damage Localization in Plates Using Global and Local Modal Strain Energy Method

This paper presents an improvement to the modal strain energy (MSE) method for identifying structural damages in plate‐type structures. A two‐step MSE‐based damage localization procedure, including a global step and a local step, is newly proposed to enhance the accuracy of detecting the location of structural damage. Firstly, the global step uses the mode shape data on the whole plate to locate the potentially damaged areas. Then, MSE is applied with a more dense mesh size on these local areas to detect damage in more detail. The proposed procedure’s feasibility is verified by analyzing an aluminum plate with various damaged scenarios. This study uses finite element analysis to acquire the plate's natural frequencies and mode shapes in intact and damaged states. A set of two damage detection capacity indicators are also newly presented to evaluate the precision of the proposed procedure. The diagnostic results demonstrate that the proposed approach uses less modal data than the original MSE method and accurately identifies the damage's locations in the plates with various edge conditions. Moreover, the combination of three first mode shapes and a damage threshold of 40% of the maximum normalized damage index gives the best results of damage localization.

Gaussian process regression model for damage localization in plates based on modal data

The applications of plate like structures in different fields of engineering are increasing. In this paper, a new damage detection method investigated based on Gaussian process regression model (GPR). GPR is an efficient learning machines which has been used in different fields of engineering. To identify damage, mode shaped and natural frequencies of damaged structures used to train GPR. Finite element modelling of numerical examples and Gaussian process regression (GPR) model are carried out within the MATLAB environment. To show the effectiveness of presented approach, a two-fixed supported plate and a cantilever plate was studied. In other work, a comparative study has been done using a cantilever plates. The natural frequencies were contaminated with noise in above mentioned numerical examples. Results reveal that the proposed method works well using the only first mode data which may be noisy. In other word, GPR can be trained using limited sample numbers for training.

Accurate baseline-free damage localization in plates using refined Lamb wave time-reversal method

In a recent study, Agrahari and Kapuria (J Int Mater Sys Struct, 27, 1283–1305, 2016) presented a Lamb wave based refined time reversal method (RTRM) for baseline-free damage detection in thin plate structures. In this method, it was proposed to conduct the probe at the frequency of best reconstruction and to use an extended wave packet ranging between two side bands accompanying the main mode of the reconstructed signal for computing the damage index. The method showed excellent sensitivity to damage in a single actuator-sensor path scenario. In the present work, the RTRM is integrated with a damage imaging algorithm called the reconstruction algorithm for probabilistic inspection of defects (RAPID) to develop an accurate baseline-free damage localization technique using a network of piezoelectric wafer patch transducers. Its performance is tested experimentally in an aluminium plate with a block mass damage. It is found that the proposed RTRM conducted at the best reconstruction frequency of the sensor network-plate system is able to predict the damage location with very good accuracy, whereas the other existing baseline-free methods such as the conventional TRM with single mode tuning and the reciprocity principle based method are either ineffective in localizing or give highly erroneous prediction of the damage location.

The Surface Interpolation Method for damage localization in plates

Abstract This paper presents a vibration based procedure for locating reductions of stiffness in plate-like structures. This procedure is a generalization to the two-dimensional case of the Interpolation Method (IM) previously published by the author. The method is based on the definition of a damage sensitive feature in terms of the accuracy of a spline function in interpolating the operational displacement shapes of the structure. In the previous works the IM was applied as a method of level 2 for damage identification that is able to detect and localize damage. In this paper an analytical relationship between the damage feature and the curvature discontinuity is proved. For two-dimensional structures, a bi-cubic spline surface is defined herein to interpolate the operational shapes. In order to account for the uncertainties related to random variations of the damage feature, an approach based on the definition of an acceptable value of the probability of false alarm was formerly proposed by the author. A simplified version of the algorithm is presented herein for the case whereby the statistical distribution of the damage feature in the original (undamaged) state is not available, and the damage diagnosis has to be carried out based on just two sets of responses recorded on the original and on the (possibly) damaged structure. The proposed two-dimensional Surface Interpolation Method (SIM) is checked herein via numerical simulations using the FE model of a plate and modeling local reductions of stiffness through a reduction of the elastic modulus of the material. Results demonstrate that the algorithm provides a reliable tool for damage identification of plate-like structures. The performance of the method can be affected by noise in recorded data, however a careful choice of the accepted probability of false alarm can reduce this drawback.

Damage localization in plates with use of the procedure based on Modal Filtration

Modal filtering has numerous applications in the analysis of object dynamics. One possible use of this technique, recently presented in the literature, is damage detection. The main idea behind it, is to compare system characteristics filtered with modal filter for damaged and undamaged state. If a structural change appears in the system the filter does not work perfectly and its output significantly differs from one obtained for the healthy structure. Method is based on the modal parameter variation due to damage but does not require the modal analysis for every diagnosis. Another advantages are: computational simplicity and robustness for ambient temperature changes. The method was extended in 2008 with the possibility of damage localization. The idea here was based on the fact that local damage disturbs mode shapes locally. Instead of one modal filter, set of local modal filters were identified and used for further processing. Area of the structure connected with the filter with the worst performance is suspected of containing the damage. The method was already presented and positively verified but only for the beam-like structures. In this paper, application for plate-like structures is shown.

Sensor requirements for in situ imaging of multiple damage by Lamb waves

Lamb waves are guided waves that propagate in plate-like structures. These waves are well suited for wide-area inspection, such as aircraft wing skins, because of their relatively slow geometrical decay with propagation distance. Recently, a computationally efficient algorithm for in situ imaging was derived based on the multi-static data matrix. Here, previous work on imaging a single circular inhomogeneity is extended to the case of structural damage spread over two distinct sites. Detailed results are presented for the rank and bandwidth of the data matrix, showing the dependence on the overall size of the damage cluster. The implications of these results for the practically important problem of determining minimum sensor requirements for image reconstruction are discussed. References C. T. Ng and M. Veidt. A Lamb-wave-based technique for damage detection in composite laminates. Smart Mater. Struct. , 18(7):074006, 2009. doi:10.1088/0964-1726/18/7/074006 J. E. Michaels and T. E. Michaels. Guided wave signal processing and image fusion for in situ damage localization in plates. Wave Motion , 44(6):482–192, 2007. doi:10.1016/j.wavemoti.2007.02.008 J. S. Hall and J. E. Michaels. Multi-path guided wave imaging for in situ monitoring of complex structures. AIP Conf. Proc. 1511:707-713, 2013. doi:10.1063/1.4789115 Z. Q. Su, L. Cheng, X. M. Wang and L. Yu. Diagnostic imaging for structural damage. Adv. Mater. Res. , 47–50:1157–1160, 2008. doi:10.4028/www.scientific.net/AMR.47-50.1157 L. R. F. Rose and C. H. Wang. Mindlin plate theory for damage detection: Source solutions. J. Acoust. Soc. Am. , 116(1):154–171, 2004. doi:10.1121/1.1739482 L. R. F. Rose and C. H. Wang. Mindlin plate theory for damage detection: Imaging of flexural inhomogeneities. J. Acoust. Soc. Am. , 127(2):754–763, 2010. doi:10.1121/1.3277217 C. H. Wang and L. R. F. Rose. Imaging damage using Mixed Passive and Active Sensors. 4th Asia-Pacific Workshop on Structural Health Monitoring, 2012 , Melbourne, Australia. C. H. Wang and L. R. F. Rose. Minimum Sensor Density for Quantitative Damage Imaging. 9th International Workshop on Structural Health Monitoring, 2013, Standford, USA . E. Chan, C. H. Wang and L. R. F. Rose. Characterisation of Part-through Damage in a Stiffened Panel by a Time-reversal Based Imaging Method. 9th International Workshop on Structural Health Monitoring, 2013, Standford, USA . Abaqus/Explicit 6.10 Dassault Systemes http://www.3ds.com/products-services/simulia/portfolio/abaqus/abaqus-portfolio/abaqusexplicit/

Damage Localization in Plates Using Mode Conversion Characteristics of Ultrasonic Guided Waves

The present study provides a concise description of wave propagation in cellular sandwich panels. A novel approach of damage detection based on mode conversion is proposed which can be useful for detecting relatively small damages in cellular sandwich structures using high frequency guided waves. The new methodology applies the continuous wavelet transform (CWT) and the cosine formula to extract the damage location from the time signal of displacements. Experiments conducted on a honeycomb and a metallic hollow sphere sandwich plate highlight the feasibility of the novel technique.

Damage localization in plate-like structure using built-in PZT sensor network

In this study, a Lamb-wave based damage detection approach is proposed for damage localization in plate. A sensor network consisting of three PZT wafer type actuators/sensors is used to generate and detect Lamb waves. To minimize the complication resulted from the multimode and dispersive characteristics of Lamb waves, the fundamental symmetric Lamb mode, S0 is selectively generated through designing the excitation frequency of the narrowband input signal. A damage localization algorithm based upon the configuration of the PZT sensor network is developed. Time-frequency analysis method is applied to purify the raw signal and extract damage features. Experimental result obtained from aluminum plate verified the proposed damage localization approach.

Non-Contact Nonlinear Acoustic Damage Localization in Plates. Part 2: Localized Resonance Through Dynamically Trapped Modes

This work is the second part of three that presents new tools to be used for damage localization in plates by nonlinear acoustical methods. It introduces an important in-plane localization technique, which is based on the existence of resonant spatially localized wave fields. The wave from the transducer is acting as a dynamic influence on the plate surface, making the waves reflect in a non-ideal way. The non-ideal reflections make the modes underneath the transducer have different resonant frequencies than the modes beside the insonified area. They appear both for contact and non-contact sources. In the nonlinear damage localization application, the trapped mode wave field interacts with another signal at lower frequency. This results in sidebands around the high frequency whose amplitudes are related to the amount of damage underneath the transducer.

Guided wave signal processing and image fusion for in situ damage localization in plates

A spatially distributed array of single element piezoelectric transducers is considered for monitoring the integrity of plate-like structures over large areas. When these permanently attached transducers are driven with an impulsive excitation, broadband Lamb waves are generated and received signals are complex, typically containing multiple modes as well as many boundary reflections. The complexity of the signals, including dispersive effects, can be reduced by digital bandpass filtering, and changes in these filtered signals over time can be monitored to detect and localize damage. Results are reported here from an experimental study whereby artificial damage was introduced in an aluminum plate in the form of through holes drilled at various locations. Time shift averaging algorithms were applied to differential signals filtered at multiple frequencies, resulting in many images for the same structural state, and these images were fused to improve damage localization and background noise. Individual and fused images were analyzed to quantify their ability to localize damage. The results show the efficacy of the imaging method as well as the significant improvement resulting from image fusion.