Improved backward fatigue statistical inference to the high-speed railway vehicle components

Abstract

Original backward statistical inference method (BSIM) was improved (here further termed as ISIA) to fit the fatigue probabilistic S-N (P-S-N) curve with finite life data or small sample problem. Based on the search path, the novel scheme captures the optimal parameters that can efficiently establish the quantitative relationship between the life distribution and stress levels. Meanwhile, the equivalent lives at different stress levels can be obtained through the conversion of fatigue life. To formulate the more realistic P-S-N curve of full-size components, the life distribution effect of small-size specimens can be considered when fitting curves. Results show that the slope and intercept of newly-proposed fatigue P-S-N curve by using the ISIA for (X-x-x-x) type life data exhibit a relative error less than 3%, and the predicted fatigue life is approximately 5% of the group method (TGM). On the other hand, the predicted life is only 0.1% of (x-x-x-x) type life data by the classical method (TCM). For the welded structures widely used in high-speed railway vehicles, the present ISIA can achieve more conservative and reliable life predictions. It is thus concluded that the newly-proposed ISIA can not only ensure the accuracy of life distribution particularly during high cycle fatigue regime but also acquire more conservative P-S-N curve as opposed to standard methods such as TGM and TCM.