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A modal decomposition imaging algorithm for ultrasonic detection of delamination defects in carbon fiber composite plates using air-coupled Lamb waves.

Authors :
Wang, Bingquan
Shi, Weijia
Zhao, Bo
Tan, Jiubin
Source :
Measurement (02632241). May2022, Vol. 195, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

• A modal decomposition imaging (MDI) algorithm for detecting delamination defects in carbon fiber composite plates using air-coupled Lamb wave is proposed in this paper. • The proposed MDI algorithm contains modal decomposition process and rotating scanning defect probability imaging method. • The delamination defect measurement is realized by single-sided and pitch-catch method and circular scanning. • The proposed MDI algorithm is suitable for achieving accurate characterization of defects in situ testing and large-area rapid scanning of aerospace composite plates after quickly scanning. In this paper, a modal decomposition imaging (MDI) algorithm for detecting delamination defects in carbon fiber composite plates using air-coupled Lamb waves was proposed. Compared with the traditional time-domain imaging method using amplitude difference, the proposed MDI algorithm contained modal decomposition process and rotating scanning defect probability imaging method, which was more suitable for analyzing the nonlinear and non-stationary leakage Lamb waves signal. The cross-correlation coefficient of the instantaneous energy was constructed to be the damage index, which was obtained by the pretreatment of the relatively pure A0 mode Lamb waves. The effectiveness of MDI algorithm proposed in this paper for realizing the delamination defects of carbon fiber composite plates was verified by qualitative imaging and quantitative characterization comparing with the defect probability imaging (DPI) algorithm. It would be suitable for achieving accurate characterization of defects in situ testing and large-area rapid scanning of aerospace composite plates after quickly scanning. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02632241
Volume :
195
Database :
Academic Search Index
Journal :
Measurement (02632241)
Publication Type :
Academic Journal
Accession number :
156764938
Full Text :
https://doi.org/10.1016/j.measurement.2022.111165