Remaining useful life prediction for a nonlinear multi-degradation system with public noise

To predict the remaining useful life (RUL) for a class of nonlinear multi-degradation systems, a method is presented. In the real industrial processes, systems are usually composed by several parts or components, and these parts or components are working in the same environment, thus the degradations of these parts or components will be influenced by common factors. To describe such a phenomenon in degradations, a multi-degradation model with public noise is proposed. To identify the degradation states and the unknown parameters, an iterative estimation method is proposed by using the Kalman filter and the expectation maximization (EM) algorithm. Next, with known thresholds, the RUL of each degradation can be predicted by using the first hitting time (FHT). In addition, the RUL of the whole system can be obtained by a Copula function. Finally, a practical case is used to demonstrate the method proposed.