Integrate Uncertainty in the Process of Prognostics for Electronics

Elements of uncertainty in the electronics Prognostics process were studied. A method for electronics Dynamic Damage Optimal Estimation and prognostics based on Particle Filtering were proposed. Under the effect of time stress, the electronics cumulative damage is the result of the continuous effect of the stress, as a result, a HMM based electronics dynamic damage model was built at first place, analytical results of uncertainties in the process of prognostics were given and thus a Bayesian based filter system was built. Bayesian Filter change the problem of uncertainty into an optimal estimation processes as a result, the optimal estimation was fetched by applying the particle filtering into the estimation. The experiment case study proved that the proposed method can eliminate the uncertainties caused by measurement and the system effectively and improve the RUL prediction accuracy.