DocumentCode :
1535449
Title :
Signal restoration using dynamic neural network model for eddy current nondestructive testing
Author :
Chady, Tomasz ; Enokizono, Masato ; Sikora, Ryszard
Author_Institution :
Oita Ind. Res. Inst., Japan
Volume :
37
Issue :
5
fYear :
2001
fDate :
9/1/2001 12:00:00 AM
Firstpage :
3737
Lastpage :
3740
Abstract :
In this paper we propose to use a multi-frequency excitation and spectrogram (MFES) eddy current testing method and a neural network model to flaw signal restoration in case of presence of interferences from fasteners and subsurface structures. The extended experiments with various interfering structures were performed in order to verify the usability of the proposed restoration method. The selected results of numerical simulations are presented
Keywords :
eddy current testing; flaw detection; inverse problems; neural nets; signal restoration; dynamic neural network model; eddy current nondestructive testing; fastener; flaw detection; interference; inverse problem; multi-frequency excitation spectrogram; numerical simulation; signal restoration; subsurface structure; Eddy currents; Fasteners; Frequency; Interference; Neural networks; Nondestructive testing; Numerical simulation; Shape; Signal restoration; Spectrogram;
fLanguage :
English
Journal_Title :
Magnetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9464
Type :
jour
DOI :
10.1109/20.952702
Filename :
952702
Link To Document :
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