Defect detection of carbon fiber deflectors based on laser infrared thermography and experimental modal analysis

doi:10.1016/j.ymssp.2024.111763

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	Defect detection of carbon fiber deflectors based on laser infrared thermography and experimental modal analysis
	Zhou, Guangyu 1; Ong, Zhi Chao 2,3; Zhang, Zhijie 1; Yin, Wuliang 4; Chen, Haoze 5; Ma, Huidong 1; Fu, Yu 6
	2024-12-01
发表期刊	MECHANICAL SYSTEMS AND SIGNAL PROCESSING
ISSN	0888-3270
卷号	221
摘要	In this study, we integrate two techniques, laser infrared thermography (LIT) and experimental modal analysis (EMA), to inspect carbon fiber deflector plates using a combination of online and offline modes. In the LIT phase, we employed line laser scanning to detect the defects in each row, pinpointed their locations, and compiled a dataset correlating the presence of defects with the peak normalized temperature. In the EMA phase, separate tests were conducted at the front and back of the carbon fiber deflector. The front test aims to capture the modal information of the sample, whereas the back test aims to explore the effects of local defects. To establish the relationship between defects and vibration amplitude efficiently, we propose a sensitive modal identification method based on Long Short-Term Memory (LSTM). Using this method, we constructed a dataset comprising defect parameters corresponding to the peaks of the differential amplitude response in the sensitive modes. Finally, we developed an LIT-EMA-support vector machine (LE-SVM) defect parameter prediction model based on an SVM. The results demonstrated that the prediction accuracy of the bivariate model surpassed that of the univariate model. In particular, the R2 value of the evaluated results for defect depth reached 0.99959, with a maximum prediction error of only 0.032 mm. Similarly, the R2 value of the evaluated results for the internal defect size reached 0.99969 with a maximum prediction error of only 0.18 mm. These experimental findings validate that the integration of the two methods not only enables comprehensive structural health inspection of carbon fiber deflector plates from overall to localized structural health detection but also yields more precise parameter evaluation results.
关键词	Carbon fiber deflector Laser infrared thermography Experimental modal analysis LSTM based sensitive modal recognition LE-SVM based defect parameters evaluation
其他关键词	DEPTH ESTIMATION ; IDENTIFICATION
DOI	10.1016/j.ymssp.2024.111763
收录类别	SCIE
语种	英语
WOS研究方向	Engineering
WOS类目	Engineering, Mechanical
WOS记录号	WOS:001281028400001
出版者	ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
原始文献类型	Article
EISSN	1096-1216
文献类型	期刊论文
条目标识符	http://ir.library.ouchn.edu.cn/handle/39V7QQFX/171585
专题	国家开放大学
通讯作者	Zhang, Zhijie
作者单位	1.North Univ China, Sch Instrument & Elect, Taiyuan 030051, Peoples R China; 2.Univ Malaya, Fac Engn, Dept Mech Engn, Kuala Lumpur 50603, Malaysia; 3.Univ Malaya, Fac Engn, Ctr Res Ind CRI 4 0 4 0, Kuala Lumpur 50603, Malaysia; 4.Univ Manchester, Sch Elect & Elect Engn, Manchester M13 9PL, England; 5.Yanshan Univ, Sch Elect Engn, Qinhuangdao 066004, Peoples R China; 6.Shanxi Open Univ, Inst Technol, Taiyuan 030027, Peoples R China
推荐引用方式 GB/T 7714	Zhou, Guangyu,Ong, Zhi Chao,Zhang, Zhijie,et al. Defect detection of carbon fiber deflectors based on laser infrared thermography and experimental modal analysis[J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING,2024,221.
APA	Zhou, Guangyu.,Ong, Zhi Chao.,Zhang, Zhijie.,Yin, Wuliang.,Chen, Haoze.,...&Fu, Yu.(2024).Defect detection of carbon fiber deflectors based on laser infrared thermography and experimental modal analysis.MECHANICAL SYSTEMS AND SIGNAL PROCESSING,221.
MLA	Zhou, Guangyu,et al."Defect detection of carbon fiber deflectors based on laser infrared thermography and experimental modal analysis".MECHANICAL SYSTEMS AND SIGNAL PROCESSING 221(2024).