Fatigue Crack Growth Prediction via Artificial Neural Network Technique

Nechval, Konstantin N.; Bausova, Irina; ŠķiItere, Daina; Nechval, Nicholas A.; Strelchonok, Vladimir F.

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Автор

Nechval, Konstantin N.
Bausova, Irina
ŠķiItere, Daina
Nechval, Nicholas A.
Strelchonok, Vladimir F.

Дата издания

2006

Издательство

BrSTU

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Библиографическое описание

Fatigue Crack Growth Prediction via Artificial Neural Network Technique / Konstantin N. Nechval [et al,] // International Conference on Neural Networks and Artificial Intelligence : proceedings, Brest, 31 May – 2 June, 2006 / Edited: V. Golovko [et al.]. – Brest : BSTU, 2006. – P. 124–129 : il. – Bibliogr.: p. 128–129 (26 titles).

Аннотация

The artificial neural network (ANN) technique for the data processing of on-line fatigue crack growth monitoring is proposed after analyzing the general technique for fatigue crack growth data. A model for predicting the fatigue crack growth by ANN is presented, which does not need all kinds of materials and environment parameters, and only needs to measure the relation between a (length of crack) and N (cyclic times of loading) in-service. The feasibility of this model was verified by some examples. It makes up the inadequacy of data processing for current technique and on-line monitoring. Hence it has definite realistic meaning for engineering application.