A Review of Robotic Arm Joint Motors and Online Health Monitoring Techniques

Abstract

The employment of robots in numerous emerging applications, e.g., disaster rescue, nuclear waste remediation, and space exploration, is of paramount importance due to their improved safety, flexibility, and productivity. Due to the harsh environmental conditions, the robotic arm joint motors and power electronic drives are vulnerable to electrical faults and mainly contribute to joint failures. To substantially improve the reliability and robustness of the robot arms utilized in remote, hazardous, and safety-critical environments, autonomous fault-tolerant and fail-active operation for these robotic arms experiencing joint failures should be developed. In the literature, many strategies have been proposed for fault prognosis, diagnosis, and health monitoring of electric motors and drives using online data analytics of the fault signature information. Thus, this paper presents an extensive up-to-date review of joint motor types, common fault types, and robot joint fault prognostics, diagnostics, and health management. First, various joint motors are introduced and compared, considering their performance advantages, disadvantages, and wide applications. Furthermore, joint motors for collaborative robotic applications are summarized and compared as illustrative examples. After that, fault types are reviewed with a further classification by fault locations, namely, stator windings, rotors, and bearings. In addition, health monitoring techniques are classified into methods for stator winding, rotor, and bearing faults. These methods are intensively compared with respect to motor and fault types, proposed health monitoring techniques, and control strategies. Finally, conclusions and future research trends are summarized.

Keywords

• Collaborative robots
• joint motors
• fault prognosis
• fault diagnosis
• health monitoring