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Survival analysis of fatigue data: Application of generalized linear models and hierarchical Bayesian model

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Abstract The survival analysis is introduced to describe the fatigue failure process in this paper for obtaining a set of flexible and accurate probabilistic stress-life (P-S-N) curves in fatigue reliability… Click to show full abstract

Abstract The survival analysis is introduced to describe the fatigue failure process in this paper for obtaining a set of flexible and accurate probabilistic stress-life (P-S-N) curves in fatigue reliability analysis. The generalized linear models (GLMs) are applied as well for expressing a trend and random errors of the P-S-N curves simultaneously. A GLM, including a linear Basquin relation and a shape-fixed Weibull hazard function, has been established for the P-S-N curves estimation, then a hierarchical Bayesian model is employed to estimate their parameters. The fatigue probability design curves are generated by the survivor function or the resulting predictive distributions. Finally, a comparative example is presented to verify the effectiveness of the method.

Keywords: bayesian model; analysis; generalized linear; hierarchical bayesian; survival analysis; linear models

Journal Title: International Journal of Fatigue
Year Published: 2018

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