Abstract
The problem of real-time reliability analysis and prediction is considered in this paper based on degradation measurements. Given the nonlinear degradation path model with random parameters, the prior distribution of the random parameters is updated into a posterior distribution according to Bayesian formula based on the measurable degradation information. Then, the reliability during a certain period in the future can be predicted by Monte Carlo integration. An example by use of the fatigue crack growth data is given for illustration.
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