Lamb wave TDTE super-resolution imaging assisted by deep learning  

作　　者：Liu-Jia Sun Qing-Bang Han and Qi-Lin Jin 孙刘家;韩庆邦;靳琪琳(College of Information Science and Engineering,Hohai University,Changzhou 213200,China)

机构地区：[1]College of Information Science and Engineering,Hohai University,Changzhou 213200,China

出　　处：《Chinese Physics B》2025年第1期357-366,共10页中国物理B(英文版)

基　　金：Project supported by the National Natural Science Foundation of China (Grant No. 12174085);the Key Research and Development Project of Changzhou, Jiangsu Province, China (Grant No. CE20235054);the Postgraduate Research and Practice Innovation Program of Jiangsu Province, China (Grant No. KYCX24 0833)。

摘　　要：Ultrasonic Lamb waves undergo complex mode conversion and diffraction at non-penetrating defects, such as plate corrosion and cracks. Lamb wave imaging has a resolution limit due to the guided wave dispersion characteristics and Rayleigh criterion limitations. In this paper, a full convolutional network is designed to segment and reconstruct the received signals, enabling the automatic identification of target modalities. This approach eliminates clutter and mode conversion interference when calculating direct and accompanying acoustic fields in time-domain topological energy(TDTE) imaging.Subsequently, the measured accompanying acoustic field is reversed for adaptive focusing on defects and enhance the imaging quality. To circumvent the limitations of the Rayleigh criterion, the direct acoustic field and the accompanying acoustic field were fused to characterize the pixel distribution in the imaging region, achieving Lamb wave super-resolution imaging. Experimental results indicate that compared to the sign coherence factor-total focusing method(SCF-TFM),the proposed method achieves a 31.41% improvement in lateral resolution and a 29.53% increase in signal-to-noise ratio for single-blind-hole defects. In the case of multiple-blind-hole defects with spacings greater than the Rayleigh criterion resolution limit, it exhibits a 27.23% enhancement in signal-to-noise ratio. On the contrary, when the defect spacings are relatively smaller than the limit, this method has a higher resolution limit than SCF-TFM in super-resolution imaging.

关 键 词：Lamb waves asymmetric defects fully convolutional network time-domain topological energy imaging SUPER-RESOLUTION 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP391.41[自动化与计算机技术—控制科学与工程]