Determination of the fatigue P-S-N curves – A critical review and improved backward statistical inference method

Abstract To increase the prediction accuracy of small-number sample life data, improved backward statistical inference approach (ISIA) was formulated using the modified distribution coefficients while fitting the fatigue probabilistic S-N (P-S-N) curve. Based on the search path searching for fatigue parameters, the novel scheme captures the optimal coefficients that can efficiently correlate the life distribution and stress levels. The equivalent lives can be obtained through the conversion of fatigue life to the highest stress level. To acquire a realistic P-S-N curve of full-scale components, the life distribution effect of small-number samples can be considered when fitting curves. Results show that for a set of data with an accurate standard deviation at the first stress level, the predicted lifetime using the ISIA is approximately 8.7% of the conventional group method and is only 10.5% of the original backwards statistical inference method. Meanwhile, by comparing the predicted results with the fatigue life testing data of full-scale alloy steel EA4T axles, the accuracy of fatigue P-S-N curves by using ISIA is further confirmed. For the modern axle materials and welded structures widely used in railway vehicles, the newly-proposed ISIA can not only achieve a reliable fatigue life, particularly in the high cycle fatigue regime, but also provide a more conservative fatigue P-S-N curve than traditional fitting methods.