摘要：The focus of this study is development of an intelligent fault detection, diagnosis and health evaluation system for real industrial robots. The system uses principalcomponent analysis based statistical process control withNelson rules for online fault detection. Several suitable Nelson rules are chosen for sensitive detection. When a variation is detected, the system performs a diagnostic operationto acquire features of the time domain and the frequency domain from the motor encoder, motor current sensor and external accelerometer for fault diagnosis with a multi-classsupport vector machine. Additionally, a fuzzy logic basedrobot health index generator is proposed for evaluating thehealth of the robot, and the generator is an original design toreflect the health status of the robot. Finally, several real aging-related faults are implemented on a six-axis industrialrobot, DRV90L7A6213N by Delta Electronics, and the proposed system is validated effectively by the experimentalresults.
关键词：fault detection and diagnosis;industrial robot;Nelson rules;robot health index;statistical process control
