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Lamb wave tomography for defect localization using wideband dispersion reversal method.

Authors :
Ling, Feiyao
Chen, Honglei
Lang, Yanfeng
Yang, Zhibo
Xu, Kailiang
Ta, Dean
Source :
Measurement (02632241). Jul2023, Vol. 216, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

• A WDR method optimized tomography algorithm is developed for robust localization using Lamb waves. • WDR excitation is designed to alleviate the frequency selection problem in defect localization. • Reconstruction independent component analysis is adopted for mode separation. • Time-frequency index is calculated as the damage index in the tomography algorithm. Tomography imaging of defects using ultrasonic Lamb waves has attracted much attention in nondestructive testing of plates. However, there are two challenges for robust localization of defects: frequency sensitivity to defects, and multi-mode interference on damage index (DI) extraction. Aiming for that, a wideband dispersion reversal (WDR) method optimized tomography is developed. Pre-dispersive wideband excitations of a certain Lamb wave mode are generated based on the configuration of transducers, and reconstruction independent component analysis is used for wave mode separation. According to the acoustic reciprocity principle, self-compensation phenomenon of mode signals can be recorded on the intact path, where the signal energy concentrates at a fix self-compensation point in the time–frequency domain, yet such compensation effect would be impaired encountering defects. Thus, a time–frequency index can be used as the DI, which is calculated based on the weighted Euclidean distance from the self-compensation point to the pixel points in the time–frequency domain. Experimental results show the WDR optimized tomography has a robust performance for magnet-simulated defects imaging without excitation frequency optimization. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02632241
Volume :
216
Database :
Academic Search Index
Journal :
Measurement (02632241)
Publication Type :
Academic Journal
Accession number :
163846392
Full Text :
https://doi.org/10.1016/j.measurement.2023.112965