Remaining Useful Life Prediction for Aircraft Engines Based on Grey Model

Assessing the health status and predicting the remaining useful life (RUL) of system can be carried out effectively by prognostics and health management (PHM). It is a significant guarantee to enhance the security and economy of complex systems such as aircraft engines. A new approach for aircraft engines RUL prediction is proposed to fully assess the health status of the engines. Firstly, the health indicator model is constructed by liner regression. Secondly, the improved grey model GM(1,1) is constructed based on the health indicator (HI). Finally, the system RUL is obtained by the improved GM(1,1) model. A case study is performed on C-MAPSS aircraft engine datasets examining the validity of approach proposed by us. According to the experimental results, a better prediction accuracy is given by the proposed method compared to traditional method.