An Improved Particle Filter Method for Accurate Remaining Useful Life Prediction

Abstract

The prognostics method that updates the parameters of degradation model using particle filter to predict the remaining useful life (RUL) of equipment is widely used in recent years. However, most of the traditional methods that use this strategy for prognostics do not establish the state transition equation and measurement equation of particle filter from the aspect of degradation trend, which makes the predicted curve may not conform to the degradation trend of the known data because of the loss of information. This paper proposes a prognostics method based on degeneration trajectory, which updates model parameters using particle filter and makes the predicted curve which depends on the updated parameters conform to the known degradation trend by establishing the measurement equation of particle filter different from the traditional method. The proposed method is verified by using the turbine engine degradation data published by NASA and the experiment shows that this method is superior to the traditional method in prediction accuracy and precision.