A neural network approach to fatigue life prediction

In this work a novel approach to fatigue life prediction under step-stress conditions is introduced where the cumulative distribution function for the failure of components was Implemented by means of a neural network The model was fit to experimental data on the fatigue life of steel under step-stress conditions For comparison a standard approach based on the lognormal distribution function was also implemented and fit to the same experimental data Both models were optimized by evolutionary computation using a maximum likelihood estimator The Kolmogorov-Smirnov test was applied to compare the results of the new approach to those obtained with the lognormal distribution function (C) 2010 Elsevier Ltd All rights reserved