Online Performance Assessment Method for a Model-Based Prognostic Approach

In this paper, we propose a method for online assessing the performance of a prognostic approach in situations of very poor knowledge on the degradation process. In particular, we deal with cases in which the entire degradation process, from the beginning of the operation until failure, has never been observed and, thus, the traditional offline performance metrics cannot be applied. The proposed method is applied on a prognostic approach based on a particle filter and optimized tuning kernel smoothing (PF-OTKS). Case studies regarding the degradation of turbine blade and aluminum electrolytic capacitor are considered