Bearing degradation prediction based on support vector regression

Abstract

Abstract Predicting bearing degradation before reaching the state of risk of accident is one important issues in power generation insurance. This paper proposes a method based on support vector regression to achieve the goal. The method is applied on PRONOSTIA dataset which is an experimental platform dedicated to test methods related to bearing health assessment. The results show that the method can effectively model the evolution of the bearing degradation.