Prediction of Remaining Useful Life of Aero-engine Based on Network and Similarity

Aeroengine is a complex system consisting of various components, which has high economic benefits and research value. Accurately evaluating the performance status of aero-engines has become a hot issue in current aero-engine research, and it plays an important role in the maintenance and storage of aero-engines. In this paper, a network model is constructed based on the aero-engine sensors data and the correlation coefficient of sensors. A method for predicting the remaining useful life (RUL) of aero-engines based on the change data of average network node strength and similarity is proposed. Through the node strength to analyze the change of the network node correlation, and the change law of the sensors network overall correlation. The RUL of aero-engines can be predicted accurately. It is found that the correlation between sensors generally increases uniformly at the end of the engine life.