Remaining Useful Life Prediction for Hidden Degradation Process with Multiple Source Uncertainty

A remaining useful life (RUL) prediction algorithm considering temporal uncertainty, individual variability uncertainty, and unmodeled dynamic uncertainty is proposed for hidden degradation process with unmeasurable degradation index. First, the degradation model integrating multiple uncertainties is established. Then, the estimated distribution of degradation index and degradation model parameters are iteratively computed using the nonlinear filter. Finally, based on the real-time multiple uncertainties information, the probability density function (PDF) is adaptively updated, achieving the RUL prediction for hidden degradation process with the influence of multiple uncertainties.