Depth Evaluation of Tiny Defects on or near Surface Based on Convolutional Neural Network

Resumen

This study concentrates on the field of intelligent nondestructive testing, presenting a CNN?based method for accurately evaluating the depth of micro?defects on or near a surface. The innovation in this study lies in several key aspects: (1) The establishment of a multi?feature correlation between defect depth and ultrasound time?frequency domain characteristics; (2) The full feature extraction via CWT and region of interest delineation of ultrasound signals aiming at a high training efficiency; (3) The targeted design and optimization of the CNN model.