Research on the P-S-N Curve Fitting Method of Notched Specimens Considering Small Sample Properties

Abstract

Aiming at the issue of fatigue test data for large-scale mechanical components of building steel are very limited, a method for fitting P-S-N curves under small sample data of notched specimens is proposed to predict fatigue life. First, a fatigue life subsample augmented and its reliability assessment method are established, based on Bayesian hierarchical modeling and modified Monte Carlo method. Second, a clustering combination weighting method is proposed, to define weights of hidden variables of the binomial mixture Weibull distribution, and the expectation–maximization algorithm is used to determine probability density function of the distribution. Finally, the P-S-N curves under various failure probabilities are fitted with Weibull distributed life models, and the convergence and prediction accuracy of the different models are compared. The results show that the fatigue data of small samples can be predicted better by using mixed Weibull distribution, and the fitting P-S-N curve is more reliable and accurate.