USING OF NEURAL NETWORKS FOR CLASSIFICATION AND DATA ANALYSIS IN EDDY-CURRENT TESTING
Ján Grman - Rudolf Ravas - Lívia Syrová
At present a very prospective solution of indications classification in defectoscopy is neural network application. One
of the fields is classification of indications into classes that are characterized by the signal shape or by the
signatures related to the signal shape. Nondestructive defectoscopy of steam generator tubes of nuclear power plants by
multifrequency eddy current method is the field in which the use of classifiers based on neural network is very
prospective. The contribution concentrates on the choice of suitable neural network structures and of a suitable
representation of indications. Selected structures are compared using real records of steam generator tubes and also
using artificial defects and imitations of construction elements.
Keywords: defectoscopy, eddy-currents, neural network, steam generator, cluster analysis
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