scholarly journals Lamb wave generation using nanosecond laser ablation to detect damage

2017 ◽  
Vol 24 (24) ◽  
pp. 5842-5853 ◽  
Author(s):  
Naoki Hosoya ◽  
Ryosuke Umino ◽  
Atsushi Kanda ◽  
Itsuro Kajiwara ◽  
Atsushi Yoshinaga
Keyword(s):  
Laser Ablation ◽  
Damage Detection ◽  
Lamb Wave ◽  
Lamb Waves ◽  
Wave Generation ◽  
Nanosecond Laser ◽  
Large Area ◽  
Contact Damage ◽  
Contact Type ◽  
Aluminum Alloy 2024

This paper proposes a non-contact damage detection method based on Lamb waves generated by laser ablation (LA). Previously, Lamb waves generated by contact-type sensors such as acoustic emission or piezoelectric zirconate titanate devices have been studied to detect damage. Lamb wave generation systems with embedded contact-type excitation devices to objective structures to be inspected may quickly realize large-area damage detection on a huge object such as an aircraft. However, replacing contact-type devices with non-contact devices in Lamb wave generation systems, the systems will have sufficient potential to excite under the specific conditions such as submerged target structures in liquid and high-temperature substances. The LA-generated Lamb waves that have amplitudes several hundred times larger than those generated by conventional laser-thermoelastically generated Lamb waves are of advantage from the viewpoint of the signal-to-noise ratio in the measurements. When the laser fluence reaches 1012–1014 W/m2, which is greater than that for laser-thermoelastic regime, a LA regime is induced. The amplitudes of the LA-generated Lamb waves might be higher than those of the laser-thermoelastically generated Lamb waves; this is within the scope of the assumption. Since the LA process entails a number of nonlinear processes such as melting, vaporization, and sublimation, it is important to confirm that LA could generate a Lamb wave and its mode. In this paper, Lamb waves that contain broadband frequency elements of more than several hundred kHz are generated by non-contact impulse excitation using LA, which is common in vibration tests in the high-frequency range, laser peening, propulsion of micro-aircraft, bolt loosening diagnosis, etc. The present method is evaluated by comparing the measured and calculated propagation phase and group velocities of the Lamb waves. Furthermore, the feasibility of our approach is demonstrated by non-contact damage detection against an aluminum alloy 2024 plate with a crack.

Lamb-Wave Based Damage Detection in Anisotropic Composite Plates

2014 ◽  
Vol 627 ◽  
pp. 1-4 ◽  
Author(s):  
Z. Sharif-Khodaei ◽  
M.H. Aliabadi
Keyword(s):  
Damage Detection ◽  
Lamb Wave ◽  
Lamb Waves ◽  
Composite Plates ◽  
Detection Algorithm ◽  
Damage State ◽  
Anisotropic Composite ◽  
Cfrp Composite ◽  
The Difference ◽  
Imaging Algorithms

Damage detection in anisotropic composite plates based on Lamb wave technique has been investigated. A network of transducers is used to detect barely visible damage caused by impact. A CFRP composite plate has been impacted and tested to verify the proposed damage detection algorithms. The difference in the propagational properties of Lamb waves in the pristine state and the damage state is used through data fusion and imaging algorithms to detect, locate and characterise the damage. The influence of directionality of the velocity on the validity of the detection algorithm is examined and some results are presented.

scholarly journals Machine Learning-Enriched Lamb Wave Approaches for Automated Damage Detection

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1790
Author(s):  
Zi Zhang ◽  
Hong Pan ◽  
Xingyu Wang ◽  
Zhibin Lin
Keyword(s):  
Machine Learning ◽  
Feature Extraction ◽  
Feature Selection ◽  
Damage Detection ◽  
Lamb Wave ◽  
Lamb Waves ◽  
Feature Selection Method ◽  
Support Vector ◽  
Time Frequency ◽  
Damage States

Lamb wave approaches have been accepted as efficiently non-destructive evaluations in structural health monitoring for identifying damage in different states. Despite significant efforts in signal process of Lamb waves, physics-based prediction is still a big challenge due to complexity nature of the Lamb wave when it propagates, scatters and disperses. Machine learning in recent years has created transformative opportunities for accelerating knowledge discovery and accurately disseminating information where conventional Lamb wave approaches cannot work. Therefore, the learning framework was proposed with a workflow from dataset generation, to sensitive feature extraction, to prediction model for lamb-wave-based damage detection. A total of 17 damage states in terms of different damage type, sizes and orientations were designed to train the feature extraction and sensitive feature selection. A machine learning method, support vector machine (SVM), was employed for the learning model. A grid searching (GS) technique was adopted to optimize the parameters of the SVM model. The results show that the machine learning-enriched Lamb wave-based damage detection method is an efficient and accuracy wave to identify the damage severity and orientation. Results demonstrated that different features generated from different domains had certain levels of sensitivity to damage, while the feature selection method revealed that time-frequency features and wavelet coefficients exhibited the highest damage-sensitivity. These features were also much more robust to noise. With increase of noise, the accuracy of the classification dramatically dropped.

scholarly journals Damage Detection of Composite Plates by Lamb Wave Ultrasonic Tomography with a Sparse Hexagonal Network Using Damage Progression Trends

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
C. J. Keulen ◽  
M. Yildiz ◽  
A. Suleman
Keyword(s):  
Damage Detection ◽  
Lamb Wave ◽  
Composite Structures ◽  
Composite Plates ◽  
Reconstruction Algorithm ◽  
Detection Algorithm ◽  
Ultrasonic Tomography ◽  
Large Area ◽  
Sparse Network ◽  
Damage Progression

Lamb wave based structural health monitoring shows a lot of potential for damage detection of composite structures. However, currently there is no agreement upon optimal network arrangement or detection algorithm. The objective of this research is to develop a sparse network that can be expanded to detect damage over a large area. To achieve this, a novel technique based on damage progression history has been developed. This technique gives an amplification factor to data along actuator-sensor paths that show a steady reduction in transmitted power as induced damage progresses and is implemented with the reconstruction algorithm for probabilistic inspection of damage (RAPID) technique. Two damage metrics are used with the algorithm and a comparison is made to the more commonly used signal difference coefficient (SDC) metric. Best case results show that damage is detected within 12 mm. The algorithm is also run on a more sparse network with no damage detection, therefore indicating that the selected arrangement is the most sparse arrangement with this configuration.

Finite Element Simulation of Lamb Wave with Piezoelectric Transducers for Composite Plate Damage Detection

2009 ◽  
Vol 79-82 ◽  
pp. 1095-1098 ◽  
Author(s):  
Wen Zhong Qu ◽  
Li Xiao
Keyword(s):  
Finite Element ◽  
Damage Detection ◽  
Finite Element Simulation ◽  
Lamb Wave ◽  
Composite Plate ◽  
Lamb Waves ◽  
Piezoelectric Transducers ◽  
Thin Plates ◽  
Diagnostic Tools ◽  
Element Simulation

Structural health monitoring (SHM) is an emerging research area with multiple applications. Lamb waves are ultrasonic elastic waves that travel inside and along thin plates and is frequently used as diagnostic tools to detect damage in plate-like structures. In this paper, a transient dynamic finite element simulation of Lamb wave with piezoelectric transducers for damage detection in a composite plate is carried out. The embedded cross-shaped piezoelectric active sensor arrays were used to generate and receive guided Lamb waves propagating in the plate structure. A full-scale FEM model for the laminate was created using three-dimensional eight-node layered structural solid element and piezoelectric active sensors were created using coupled field elements on the commercial finite element code ANSYS platform. The beam forming technique of Lamb waves is used to locate damage in the plate .The results of the numerical simulation demonstrate the effectiveness of the approach.

Impact of Changing Temperature on Lamb Wave Propagation for Damage Detection

2013 ◽  
Vol 588 ◽  
pp. 140-148 ◽  
Author(s):  
Rafal Radecki ◽  
Wieslaw Jerzy Staszewski ◽  
Tadeusz Uhl
Keyword(s):  
Wave Propagation ◽  
Damage Detection ◽  
Lamb Wave ◽  
Structural Damage ◽  
Clustering Algorithm ◽  
Lamb Waves ◽  
Ultrasonic Waves ◽  
Effect Of Temperature ◽  
Propagation Parameters ◽  
Lamb Wave Propagation

Lamb waves are the most widely used guided ultrasonic waves for structural damage detection. One of the major problems associate with Lamb wave propagation is the effect of temperature on wave propagation parameters. It is important that these parameters are more sensitive to damage than to varying temperature. The paper demonstrates how amplitude and arrival time of Lamb waves are affected by temperature. The analysis is performed for the experimental data gathered from Lamb wave propagation in a damaged aluminium plate. A simple clustering algorithm is used to distinguish between "undamaged" and "damaged" conditions in the presence of changing temperature.

Damage Detection Using Cointegration Technique and Wavelet Analysis of the Post-Cointegrated Lamb Waves

2013 ◽  
Vol 569-570 ◽  
pp. 908-915
Author(s):  
Phong B. Dao ◽  
Wieslaw Jerzy Staszewski
Keyword(s):  
Time Series ◽  
Wavelet Analysis ◽  
Damage Detection ◽  
Temperature Effect ◽  
Lamb Wave ◽  
Lamb Waves ◽  
Experimental Results ◽  
Temperature Variations ◽  
Multi Level ◽  
Stationary Behaviour

This paper presents an application of Lamb-wave-based damage detection under varying temperature conditions. The method used is based on the cointegration technique and wavelet analysis that are partially built on the analysis of non-stationary behaviour and multi-resolution decomposition of time series, respectively. Instead of directly using Lamb wave data for damage detection, two approaches are used: (1) analysis of cointegrating residuals obtained from the cointegration process of Lamb wave responses and (2) analysis of stationary characteristics of the multi-level wavelet decomposed cointegrating residuals. These two approaches are tested on undamaged and damaged aluminium plates exposed to temperature variations. The experimental results show that the method can isolate damage-sensitive features from the temperature effect and reliably detect damage.

Lamb Wave Generation Based on Laser Ablation with Damage Prevention

2017 ◽  
Vol 2017 (0) ◽  
pp. 441
Author(s):  
Atsushi YOSHINAGA ◽  
Yohei OKUMURA ◽  
Naoki HOSOYA ◽  
Atsushi KANDA ◽  
Saya IWASAKI ◽  
...  
Keyword(s):  
Laser Ablation ◽  
Lamb Wave ◽  
Wave Generation ◽  
Damage Prevention

scholarly journals Weighted Structured Sparse Reconstruction-Based Lamb Wave Imaging Exploiting Multipath Edge Reflections in an Isotropic Plate

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3502
Author(s):  
Caibin Xu ◽  
Zhibo Yang ◽  
Mingxi Deng
Keyword(s):  
Lamb Wave ◽  
Isotropic Plate ◽  
Lamb Waves ◽  
Correlation Coefficients ◽  
Sparse Reconstruction ◽  
Imaging Method ◽  
Structured Sparsity ◽  
Large Area ◽  
Prediction Technique ◽  
Wave Imaging

Lamb wave-based structural health monitoring techniques have the ability to scan a large area with relatively few sensors. Lamb wave imaging is a signal processing strategy that generates an image for locating scatterers according to the received Lamb waves. This paper presents a Lamb wave imaging method, which is formulated as a weighted structured sparse reconstruction problem. A dictionary is constructed by an analytical Lamb wave scattering model and an edge reflection prediction technique, which is used to decompose the experimental scattering signals under the constraint of weighted structured sparsity. The weights are generated from the correlation coefficients between the scattering signals and the predicted ones. Simulation and experimental results from an aluminum plate verify the effectiveness of the present method, which can generate images with sparse pixel values even with very limited number of sensors.

scholarly journals Lamb Wave Based Structural Damage Detection Using Stationarity Tests

Materials ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 6823
Author(s):  
Phong B. Dao ◽  
Wieslaw J. Staszewski
Keyword(s):  
Damage Detection ◽  
Unit Root ◽  
Lamb Wave ◽  
Structural Damage ◽  
Lamb Waves ◽  
Structural Damage Detection ◽  
Kpss Test ◽  
Wave Data ◽  
Lamb Wave Propagation ◽  
Adf Test

Lamb waves have been widely used for structural damage detection. However, practical applications of this technique are still limited. One of the main reasons is due to the complexity of Lamb wave propagation modes. Therefore, instead of directly analysing and interpreting Lamb wave propagation modes for information about health conditions of the structure, this study has proposed another approach that is based on statistical analyses of the stationarity of Lamb waves. The method is validated by using Lamb wave data from intact and damaged aluminium plates exposed to temperature variations. Four popular unit root testing methods, including Augmented Dickey–Fuller (ADF) test, Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test, Phillips–Perron (PP) test, and Leybourne–McCabe (LM) test, have been investigated and compared in order to understand and make statistical inference about the stationarity of Lamb wave data before and after hole damages are introduced to the aluminium plate. The separation between t-statistic features, obtained from the unit root tests on Lamb wave data, is used for damage detection. The results show that both ADF test and KPSS test can detect damage, while both PP and LM tests were not significant for identifying damage. Moreover, the ADF test was more stable with respect to temperature changes than the KPSS test. However, the KPSS test can detect damage better than the ADF test. Moreover, both KPSS and ADF tests can consistently detect damages in conditions where temperatures vary below 60 °C. However, their t-statistics fluctuate more (or less homogeneous) for temperatures higher than 65 °C. This suggests that both ADF and KPSS tests should be used together for Lamb wave based structural damage detection. The proposed stationarity-based approach is motivated by its simplicity and efficiency. Since the method is based on the concept of stationarity of a time series, it can find applications not only in Lamb wave based SHM but also in condition monitoring and fault diagnosis of industrial systems.

Damage Detection in Thick Steel Beam Using Lamb Waves

2008 ◽  
Author(s):  
Kai Sun ◽  
Guang Meng ◽  
Fucai Li ◽  
Lin Ye ◽  
Ye Lu
Keyword(s):  
Damage Detection ◽  
Lamb Wave ◽  
Lamb Waves ◽  
Fem Simulation ◽  
Wave Mode ◽  
Thin Plates ◽  
Steel Beams ◽  
Thick Steel ◽  
Number Of Cycles ◽  
Detection And Localization

Different from the mostly concerned Lamb wave-based damage detection for thin plates, this paper presents a diagnosis procedure on thick steel beams with thickness of 34 mm. The diagnosis strategy and specimens were first described, and some parameters, such as the frequency and the number of cycles of the diagnostic waveform, were discussed. Based on finite element method (FEM) simulation, the experiment configuration was addressed, results from which show good similarity between the outcomes from the simulations and those from the experiments. Wavelet transform was further used to process the acquired Lamb wave signals for the purpose of damage detection and localization. Meanwhile, the velocity of the Lamb waves was calculated, illustrating that the fundamental anti-symmetric (A0) Lamb wave mode was excited in this case. The results demonstrate that Lamb waves can also be applied to some thick structures for the purpose of structural health monitoring.

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