Reliability prediction of machinery with multiple degradation characteristics using double-Wiener process and Monte Carlo algorithm

Reliability prediction is of great importance to improve the operational safety of machinery and decreasing their maintenance costs. In this paper, a new method combining double-Wiener process model with Monte Carlo algorithm is proposed to solve the problem of degradation modeling and reliability prediction of machinery with multiple degradation characteristics. Unlike other Wiener process-based prediction methods that only the mean is modelled, this method considers the degradation of both mean and variance, making degradation modelling more accurate. Meanwhile, the proposed method estimates reliability level of the machinery based on its entire monitoring information to date through an expectation maximization algorithm and a Monte Carlo algorithm, which does not require historical degradation data of other machines in a population. A numerical degradation case and a bearing degradation case with a set of degradation data are studied to validate the proposed method. The results demonstrate the effectiveness of the proposed method compared with other existing methods. (C) 2019 Elsevier Ltd. All rights reserved.