Content area

Abstract

Eddy current testing is one of the conventional non-destructive testing (NDT) technologies which is widely used in metal defects detection. Defect imaging by eddy current tomography (ECT) has advantages of visualization of defects, large detection area, fast detection speed and avoiding mechanical scanning imaging error. Sensitivity matrix is crucial in reconstructing defect images of metal materials by ECT. This article presents a sensitivity matrix of high conductivity initial estimate for ECT detecting metal materials. A 4×4 eddy current planar coil array and a 2 mm thickness titanium plate with defects were designed by both simulation and experiment. Based on the proposed sensitivity matrix, reliability of ECT forward problem linearization was analyzed and image reconstruction with two typical regularization methods (L1 and L2) were investigated. Both simulation and experiment results show that ECT forward problem linearization was more accurate and reliable with the proposed sensitivity matrix especially at higher frequency. And L1 regularization method was verified to be more suitable to reconstruct image of small defects in metal materials. This work expands the original assumption of ECT forward problem linearization, which is of great significance to improve the metal defect image accuracy of ECT.

Details

Title
Reconstruction of Metal Defect Images Based on the Sensitivity Matrix of High Conductivity Initial Estimate for Eddy Current Tomography
Author
Xiao, Zhili 1 ; Ma, Zicheng 1 ; Li, Xiaohui 1 ; Tan, Chao 2 ; Dong, Feng 2 

 Civil Aviation University of China, College of Electronic Information and Automation, Tianjin, China (GRID:grid.411713.1) (ISNI:0000 0000 9364 0373) 
 Tianjin University, Tianjin Key Laboratory of Process Measurement and Control, School of Electrical and Information Engineering, Tianjin, China (GRID:grid.33763.32) (ISNI:0000 0004 1761 2484) 
Publication title
Volume
43
Issue
2
Pages
51
Publication year
2024
Publication date
Jun 2024
Publisher
Springer Nature B.V.
Place of publication
New York
Country of publication
Netherlands
ISSN
01959298
e-ISSN
15734862
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2024-04-25
Milestone dates
2024-04-02 (Registration); 2023-12-31 (Received); 2024-04-02 (Accepted)
Publication history
 
 
   First posting date
25 Apr 2024
ProQuest document ID
3266612357
Document URL
https://www.proquest.com/scholarly-journals/reconstruction-metal-defect-images-based-on/docview/3266612357/se-2?accountid=208611
Copyright
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Last updated
2025-10-30
Database
ProQuest One Academic