Remaining Useful Life Prediction of Electronic Products Based on Wiener Degradation Process

This paper address the remaining useful life (RUL) prediction of electronic products based on wiener degradation process model and Bayesian posterior estimation.Considering the randomness and individual difference of performance degradation process of electronic products, the degradation process can be modeled and analyzed based on the Wiener process. Combining with the historical degradation data of other similar products as the prior information, posterior parameters can be estimated by using the degradation information of the target product through Bayesian estimation through the RUL distribution of the first hitting time (FHT). It can realize real-time update of parameters. Then the RUL of target electronic product can be estimated. It can improve the accuracy of RUL prediction to a certain extent. The feasibility of the method is verified by a practical example of GaAs lasers.