文献类型：期刊文献

英文题名：Infrared-Induced Laser Shearography: Enhanced Multimodal Features Recognition for Interfacial Defects in SIR/GFRP Composite Structures

作者：Tu, Yanxin[1];Liu, Lishuai[2];Cao, Bin[1];Mei, Hongwei[1];Wang, Liming[1]

机构：[1]Tsinghua Univ, Inst Adv Technol Energy & Elect Engn IAT3E, Shenzhen Int Grad Sch, Shenzhen 518055, Peoples R China;[2]East China Univ Sci & Technol, Sch Mech & Power Engn, Shanghai Key Lab Intelligent Sensing & Detect Tech, Shanghai 200237, Peoples R China

年份：2024

卷号：73

起止页码：1

外文期刊名：IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT

收录：;EI(收录号：20241515880213);WOS:【SCI-EXPANDED(收录号:WOS:001201870800022)】；

基金：No Statement Available

语种：英文

外文关键词：Deformation; Speckle; Optical interferometry; Surface morphology; Mathematical models; Feature extraction; Optical surface waves; Dynamic deformation; feature extraction; infrared-induced laser shearography (IILS); non-destructive testing (NDT); tensor decomposition

摘要：The detection capability of laser shearography has not been fully developed due to neglecting the overall dynamic deformation process. In this article, we propose an infrared-induced laser shearography (IILS) method for composite structure detection that captures dynamic deformation data and enhances detection performance through feature extraction. Based on the temperature-deformation connection theory, we investigate the relationship between the dynamic deformation process and defects through simulations and experiments, demonstrating that the dynamic process contains a wealth of defect information. Using feature extraction algorithms, we perform denoising and enhance imaging of the shearogram sequence. Applying tensor robust principal component analysis (TRPCA), we extract a low tubal rank tensor that captures the intrinsic deformations and performs additional feature extraction. We validate the benefits of the proposed TRPCA-based feature extraction method in image enhancement through visual observation and evaluation using parameters such as two-dimensional entropy (TDE), contrast, and signal-to-noise ratio (SNR). In conclusion, the dynamic deformation-based IILS method significantly enhances the detection capability, reliability, and stability of interferometric modality in the field of industrial non-destructive testing.