Experimental study on the life prediction of servo motors through model-based system degradation assessment and accelerated degradation testing

Abstract

The advent of smart factories has resulted in the frequent utilization of industrial robots within factories to increase production automation and efficiency. Due to the increase in the number of industrial robots, it has become more important to prevent any unexpected breakdowns of the factory. As a result, the lifespan prediction of machinery has become a crucial factor because such failures can be directly associated with factory productivity resulting in significant losses. Most of the failures occur within one of the core components of the robot arm, the servo motor, and thus we will focus on the analysis of the servo motor in this study. However, sensor attachment to such equipment is considered difficult due to the dynamic movement of the robot arm, meaning that internal instrumentation should be utilized during analysis. In addition, no definite measure to determine the degradation of the motor exists, and thus a new degradation index is proposed in this study. Therefore, in this study, the lifespan of the servo motor will be estimated through accelerated degradation testing methods based on a new system degradation assessment method, which estimates the fault of the system using observer-based residuals with encoder data obtained from internal instrumentation.