DocumentCode
1429125
Title
Fast flaw reconstruction from 3D eddy current data
Author
Badics, Zsolt ; Pavo, Jozsef ; Komatsu, Hidenobu ; Kojima, Sota ; Matsumoto, Yoshihiro ; Aoki, Kazuhiko
Author_Institution
Ansoft Corp., Pittsburgh, PA, USA
Volume
34
Issue
5
fYear
1998
fDate
9/1/1998 12:00:00 AM
Firstpage
2823
Lastpage
2828
Abstract
An eddy current flaw reconstruction strategy based on the minimization of nonlinear least-squares error functionals is developed for problems with arbitrary specimen, probe and defect shapes. A fast 3D forward solver is created to rapidly predict eddy current signals in the inversion shell. The high speed of the signal evaluation comes by utilizing a reaction data set constructed before performing the inversion by a finite element electromagnetic field simulator. The same pre-calculated reaction data set supports the quick evaluation of sensitivity information, thereby ensuring the efficient implementation of an optimization algorithm. This optimization algorithm combines first-order and stochastic optimization strategies and improves the reliability of the reconstruction significantly if the observed data contain large noise components. Examples with tube specimens are presented for different 3D flaw shapes
Keywords
eddy current testing; finite element analysis; flaw detection; inverse problems; least squares approximations; optimisation; sensitivity analysis; 3D eddy current data; eddy current flaw reconstruction strategy; fast 3D forward solver; finite element EM field simulator; first-order optimization strategy; flaw reconstruction; minimization; nonlinear least-squares error functionals; optimization algorithm; reaction data set; sensitivity information; signal evaluation; stochastic optimization strategy; Coils; Eddy currents; Electromagnetic fields; Finite element methods; Impedance; Nuclear fuels; Performance evaluation; Probes; Shape measurement; Stochastic processes;
fLanguage
English
Journal_Title
Magnetics, IEEE Transactions on
Publisher
ieee
ISSN
0018-9464
Type
jour
DOI
10.1109/20.717657
Filename
717657
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