Journal Article

Fault Types and Diagnostic Methods of Manipulator Robots: A Review

Wu, Jun, Lu, Chen, Zhang, Yuepeng, Wang, Hui, Gao, Bo, Cao, Guangzhong, Xia, Linzhong

2025

Overview

Manipulator robots hold significant importance for the development of intelligent manufacturing and industrial transformation. Manufacturers and users are increasingly focusing on fault diagnosis for manipulator robots. The voltage, current, speed, torque, and vibration signals of manipulator robots are often used to explore the fault characteristics from a frequency perspective, and temperature and sound are also used to represent the fault information of manipulator robots from different perspectives. Technically, manipulator robot fault diagnosis involving human intervention is gradually being replaced by new technologies, such as expert experience, artificial intelligence, and digital twin methods. Previous reviews have tended to focus on a single type of fault, such as analysis of reducers or joint bearings, which has led to a lack of comprehensive summary of various methods for manipulator robot fault diagnosis. Considering the needs of future research, a review of different fault types and diagnostic methods of manipulator robots provides readers with a clearer reading experience and reveals potential challenges and opportunities. Such a review helps new researchers entering the field avoid duplicating past work and provides a comprehensive overview, guiding and encouraging readers to commit to enhancing the effectiveness and practicality of manipulator robot fault diagnosis technologies.

• Publisher: MDPI AG,MDPI
• Subject: Algorithms / Automation / Comparative analysis / Efficiency / Fault diagnosis / Fault location (Engineering) / Innovations / Lubricating oils / Machine learning / Maintenance and repair / Maintenance costs / manipulator robot / Manipulators / Manufacturers / Manufacturing / Methods / Neural networks / Review / Robots / signal acquisition / Testing / type of fault