On-line Estimation of Degradation State Under Random Change of Mode

Due to changes of the surrounding environment, the dynamic of one degradation process may change at random time and it follows different modes before and after the change point. For solving on-line degradation state estimation problems subject to random change of mode, a novel state estimation method is proposed in this paper based on the degradation models and related monitored data. The proposed method employs sequential probability ratio test based on log-likelihood ratio to detect the unknown change time of degradation mode, and particle filtering to estimate the degradation states given observations and also to evaluate the decision functions of the sequential probability ratio test. Two case studies referring to a pneumatic valve considering single and multiple change times of degradation mode are presented to illustrate the accuracy and effectiveness of the proposed method.