Remaining useful life prediction of nonlinear degradation process based on EKF

Remaining useful life prediction has always been the core issue of prediction and health management (PHM), and has become a research hotspot in the field of health management. Aiming at the problem of engine life prediction, based on the data set provided by NASA to simulate the degradation process of aircraft turbofan engine, the Extended Kalman Filter (EKF) algorithm is applied to the engine life prediction process, combined with condition monitoring The remaining life of the engine is predicted by fitting the model. The experimental results show that the proposed prediction method can be effectively used in engine life prediction, and has good prediction effect.