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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