文献类型：期刊文献

英文题名：Lamb wave phased array imaging based on phase-amplitude compounding algorithm

作者：Li, Xuan[1];Liu, Lishuai[1];Xu, Haiming[1];Hu, Zheng[1];Xiang, Yanxun[1];Xuan, Fu-Zhen[1]

机构：[1]East China Univ Sci & Technol, Sch Mech & Power Engn, Shanghai Key Lab Intelligent Sensing & Detect Tech, Shanghai 200237, Peoples R China

年份：2023

卷号：205

外文期刊名：MECHANICAL SYSTEMS AND SIGNAL PROCESSING

收录：;EI(收录号：20234314958049);WOS:【SCI-EXPANDED(收录号:WOS:001101966700001)】；

基金：This work was supported by the National Key Research and Development Program of China (Grant No. 2022YFF0605600) , the National Natural Science Foundation of China (Grant Nos. 12104155 and 12025403) , the Shanghai Chenguang Program (Grant No. 21CGA36) , and the Natural Science Foundation of Shanghai (Grant No. 21ZR1417100) .

语种：英文

外文关键词：Lamb wave phased array; Dispersion compensation; Total focusing method; Phase coherence factor; Multiple defects imaging

摘要：Aimed at improving the imaging performance of Lamb wave phased array based on Delay-andSum (DAS) of signal amplitude, a compounding imaging algorithm integrating amplitude and phase information of signal is proposed in this paper. By applying back propagation dispersion compensation, the pulse echoes caused by defects will be in-phase with the excitation signal, implementing signal focusing. In the proposed imaging algorithm, the amplitude imaging index is calculated by classical total focusing method (TFM) and the phase imaging index is calculated by phase coherence factor (PCF), which establishes the nonlinear mapping between imaging index and phase difference by sigmoid function with variable gradient. The final imaging results are the compound of two imaging indexes. The experimental validation is carried out on plates of different materials and dimensions with multiple types of defects based on uniform linear array. Compared with the imaging results of conventional TFM, the proposed imaging algorithm can effectively improve the signal-to-noise ratio (SNR) of the images and suppress artifacts, implementing threshold-free imaging.