Review on Remaining Useful Life Prediction Methods of Bearing

Abstract

As the foundation and kernel point of prognostics and health management (PHM) technique, the prediction of remaining useful life (RUL) raises numerous concerns. Bearing is one of the momentous parts that determine the state of health and life of the wind turbines, high-speed trains, and rotating machines. With increasing application of bearing in the equipment, the research on RUL prediction of bearing has gradually become one of the issues concerned by people, the research on the RUL prediction methods has made some progress at home and abroad. This paper aims to summarize the research status of RUL prediction methods of the bearings in recently years. Furthermore, the RUL prediction methods of bearings are introduced, which includes RUL prediction methods based on statistical data-driven and RUL prediction methods based on machine learning (ML), and summarizes the research results of RUL prediction. Finally, the research on the RUL prediction method of bearing was prospected.