Damage imaging identification of plate structures based on linear array near-field MUSIC algorithm

The paper proposes a damage imaging identification method for plate structures based on piezoelectric Lamb waves and the MUSIC algorithm, focusing on enhancing the accuracy of damage identification by using the sensing signal mode separation technique, and on the MUSIC-algorithm-based damage level e...

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Bibliographic Details
Published inNondestructive testing and evaluation Vol. 40; no. 8; pp. 3545 - 3577
Main Authors Yan, Shi, Zhu, Ruifeng, Wang, Xuenan, Chen, Xiukun
Format Journal Article
LanguageEnglish
Published Taylor & Francis 03.08.2025
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ISSN1058-9759
1477-2671
DOI10.1080/10589759.2024.2405877

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Summary:The paper proposes a damage imaging identification method for plate structures based on piezoelectric Lamb waves and the MUSIC algorithm, focusing on enhancing the accuracy of damage identification by using the sensing signal mode separation technique, and on the MUSIC-algorithm-based damage level evaluation. The mode separation of damage scattering signals is realised by using pairwise geometric symmetry to simplify the processing of sensing signals and improving the accuracy of damage imaging. A damage factor constructed by using the maximum eigenvalue of the sensing signal matrix is proposed, and it is combined with imaging technology to realise the precise locating and preliminary evaluation of damage. A combination of finite element simulation and experimental validation is used to verify the effectiveness of the proposed method. The results show that accurate damage localisation imaging can be obtained by using a mode-separated damage scattering signal; the damage level has an approximately linear relationship with the damage factor, which can be used to initially recognise the damage level. Within a certain level of damage, the proposed method has high accuracy and stability, enhancing the effectiveness of the damage identification technology for plate structures based on the MUSIC algorithm.
ISSN:1058-9759
1477-2671
DOI:10.1080/10589759.2024.2405877