A Summary of Health Prognostics Methods for Industrial Robots

Abstract

With the rise of intelligent manufacturing, the requirements for precision and reliability of industrial robots are increasing. Through the industrial robot system status monitoring and health prognostics, when maintenance is needed, this strategy of condition-based maintenance (CBM) can reduce unnecessary maintenance operations effectively, and reduce the overall maintenance cost. The health prognostics usually consists of data acquisition and processing, health indicator (HI) construction and remaining useful life (RUL) prediction. Industrial robots are complex systems composed of sensors, reducers, motors, servo drivers and controllers. In this paper, the methods of health prognostics are summarized from two aspects: component level and system level. Finally, the health prognostics methods for industrial robots are prospected and summarized combined with literature.