Defect localization and characterization in eddy current nondestructive testing by change detection and global optimization

作     者：Kermadi, Majda Moussaoui, Said Brahimi, Abdelhalim Taieb Feliachi, Mouloud 

作者机构：Univ Sci & Technol Oran Mohamed Boudiaf Dept Elect Engn BP 1505 EL Naouer Oran 31000 Algeria Ecole Cent Nantes LS2N Nantes France IREENA St Nazaire France 

出 版 物：《COMPEL-THE INTERNATIONAL JOURNAL FOR COMPUTATION AND MATHEMATICS IN ELECTRICAL AND ELECTRONIC ENGINEERING》 (COMPEL Int J Comput Math Electr Electron Eng)

年 卷 期：2018年第37卷第2期

页      面：948-970页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Finite element method Eddy current testing Defect detection and localization Efficient global optimization Kernel change detection 

摘      要：PurposeThis paper aims to present a data-processing methodology combining kernel change detection (KCD) and efficient global optimization algorithms for solving inverse problem in eddy current non-destructive testing. The main purpose is to reduce the computation cost of eddy current data inversion, which is essentially because of the heavy forward modelling with finite element method and the non-linearity of the parameter estimation problem. Design/methodology/approachThe KCD algorithm is adapted and applied to detect damaged parts in an inspected conductive tube using probe impedance signal. The localization step allows in reducing the number of measurement data that will be processed for estimating the flaw characteristics using a global optimization algorithm (efficient global optimization). Actually, the minimized objective function is calculated from data related to defect detection indexes provided by KCD. FindingsSimulation results show the efficiency of the proposed methodology in terms of defect detection and localization;a significant reduction of computing time is obtained in the step of defect characterization. Originality/valueThis study is the first of its kind that combines a change detection method (KCD) with a global optimization algorithm (efficient global optimization) for defect detection and characterization. To show that such approach allows to reduce the numerical cost of ECT data inversion.