Fatigue life analysis based on six sigma robust optimization for pantograph collector head support

Abstract

In this article, a new fatigue life analysis method based on six sigma robust optimization is proposed, which considers the random effects of material properties, external loads, and dimensions on the fatigue life of a pantograph collector head support. Some main random factors are identified through fatigue reliability sensitivity analysis, which are used as input variables during fatigue life analysis. The six sigma optimization model is derived using the second-order response surface method. The response surface is fitted by the Monte Carlo method, the samples are obtained by the Latin hypercube sampling technique, and the proposed model is optimized using the interior point algorithm. Through the optimization, the collector head support weight is reduced, the mean and the standard deviation of fatigue life have been decreased, and the effect of design parameter variation on the fatigue life is reduced greatly. The robustness of fatigue life prediction of collector head support is improved. The proposed method may be extended to fatigue life analysis of other components of electric multiple units.