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Location of plural defects in conductive plates via neural networks

Journal Article · · IEEE Transactions on Magnetics
DOI:https://doi.org/10.1109/20.376378· OSTI ID:63112
;  [1]
  1. Univ. of Reggio Calabria (Italy). Dipt. di Ingegneria Elettronica e Matematica Applicata
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 characterizing plural defects. The experimental results show the validity of the proposed processing.
OSTI ID:
63112
Report Number(s):
CONF-9407177--
Journal Information:
IEEE Transactions on Magnetics, Journal Name: IEEE Transactions on Magnetics Journal Issue: 3Pt1 Vol. 31; ISSN IEMGAQ; ISSN 0018-9464
Country of Publication:
United States
Language:
English

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