Remaining useful life prediction of a mechanism considering wear correlation of multiple joints

Abstract

Wear of joints is inevitable and has a significant influence on the performance of a mechanism. Existing researches have extensively studied the wear of a single joint. However, they ignored the wear interaction between joints and its influence on the motion output of a mechanism. In this paper, we propose a method for remaining useful life (RUL) prediction of a mechanism with multiple joints. Wear correlation between joints is taken into account for the first time in the RUL prediction of a mechanism. The relationship between the wear of joints and the motion output of a mechanism is investigated. A wear inference method based on Bayesian posterior information is introduced. Then, the influence of wear on motion accuracy of a mechanism is studied. To verify the feasibility of the proposed method, wear experiments of a crank-slider mechanism are conducted. Our RUL prediction results demonstrate that the proposed method is very accurate. The prediction error is within 4%.