Feature Extraction Approach for Defect Inspection in Eddy Current Pulsed Thermography

作     者：Pei-Pei Zhu Li-Bing Bai Yu-Hua Cheng Pei-Pei Zhu;Li-Bing Bai;Yu-Hua Cheng

作者机构：with the School of Automation EngineeringUniversity of Electronic Science and Technology of ChinaChengdu 610054 

出 版 物：《Journal of Electronic Science and Technology》 (电子科技学刊（英文版）)

年 卷 期：2021年第19卷第4期

页      面：390-400页

核心收录：

学科分类：08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

基　　金：the National Natural Science Foundation of China under Grants No.51607024 and No.61671109. 

主　　题：Eddy current thermography feature extraction machine learning non-destructive testing(NDT). 

摘      要：The eddy current pulsed thermography(ECPT)technique is a research focus in the non-destructive testing(NDT)area for defect inspection.Defect feature extraction for defect information analysis in ECPT is limited by image contrast,heat diffusion,background interference,etc.In this paper,a defect feature extraction approach in ECPT has been proposed to improve the quality of defect features,which is based on image partition,local sparse component evaluation,and feature fusion.This method can extract complete defect features by enhancing the defect area and removing background interference,such as noises and heating coil.Two typical steel specimens are utilized to testify the validity of the proposed approach.Compared with other three common feature extraction algorithms in ECPT,the proposed method can reserve more complete defect features and suppress more background interference.