Abstract
The change of residual stress is complex in the fatigue cycle. The method of evaluating the fatigue state through physical models couldn’t express the possibility of residual stress evolution. The data-driven model doesn’t conform to the physical evolution law in detail and the most model need large-scale data. In this paper, a probabilistic model based on physical model and Gaussian Process Flow is proposed to describe the fatigue life degradation curve of alloy components in practical production. It could get different evolution paths instead of statistical parameters by Gaussian Process Flow. Different evolution paths are calibrated by Kalman filter, and the model is optimized combined with the physical model. Through a fatigue test for nickel alloy, the proposed model could better describe the evolution relationship between fatigue stress and fatigue cycle under small samples.
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