关键词: 剩余寿命, 非线性维纳过程, 贝叶斯方法, 退化, 极大似然法

Abstract: To predict available residual life of single service equipment, a prediction method of residual life which combines prior and current degradation data is proposed. The equipment degradation model is constructed, conforming to a nonlinear Wiener process. The unknown parameters are estimated by using the Maximum Likelihood Estimate（MLE） method. Parameters are updated by using the Bayesian method when new degradation data is available. After that, the real-time residual life is further evaluated. Numerical simulation and case study are conducted. Results indicate that the presented method can update the evaluation distribution of residual life by using new degradation data, reflect differences between individual equipment well and significantly reduce uncertainty of the residual life distribution, compared with the fixed parameter method.

Key words: residual life, nonlinear Wiener process, Bayesian method, degradation, Maximum Likelihood Estimate（MLE）