DocumentCode
762676
Title
Location of plural defects in conductive plates via neural networks
Author
Morabito, Francesco Carlo ; Campolo, Maurizio
Author_Institution
Dipatimento di Ingegneria Elettronica e Matematica Applicata, Calabria Univ., Italy
Volume
31
Issue
3
fYear
1995
fDate
5/1/1995 12:00:00 AM
Firstpage
1765
Lastpage
1768
Abstract
This paper treats an inverse electrostatic sample problem which is very similar to a real nondestructive testing (NDT) problem. The focus of the paper is on the use of an artificial neural network (ANN) approach. The method here presented aims at detecting and characterising plural defects. The experimental results show the validity of the proposed processing
Keywords
electrical engineering computing; electrostatics; neural nets; nondestructive testing; artificial neural network; conductive plates; inverse electrostatic sample problem; neural networks; nondestructive testing; plural defects; Artificial neural networks; Electromagnetics; Electrostatics; Inspection; Intelligent networks; Inverse problems; Magnetic field measurement; Neural networks; Shape measurement; Testing;
fLanguage
English
Journal_Title
Magnetics, IEEE Transactions on
Publisher
ieee
ISSN
0018-9464
Type
jour
DOI
10.1109/20.376378
Filename
376378
Link To Document