Zhang Yuepeng, Wu Jun, Gao Bo, Xia Linzhong, Lu Chen, Wang Hui, Cao Guangzhong
School of Sino-German Robotics, Shenzhen Institute of Information Technology, Shenzhen 518172, China.
Inovance Industrial Robot Reliability Technology Research Institute, Shenzhen Institute of Information Technology, Shenzhen 518172, China.
Sensors (Basel). 2025 Mar 10;25(6):1716. doi: 10.3390/s25061716.
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.
操作机器人对智能制造的发展和产业转型具有重要意义。制造商和用户越来越关注操作机器人的故障诊断。操作机器人的电压、电流、速度、扭矩和振动信号常被用于从频率角度探索故障特征，温度和声也被用于从不同角度表征操作机器人的故障信息。从技术层面讲，涉及人工干预的操作机器人故障诊断正逐渐被新技术所取代，如专家经验、人工智能和数字孪生方法。以往的综述往往侧重于单一类型的故障，如减速器或关节轴承的分析，这导致对操作机器人故障诊断的各种方法缺乏全面总结。考虑到未来研究的需求，对操作机器人不同故障类型和诊断方法进行综述，能为读者提供更清晰的阅读体验，并揭示潜在的挑战和机遇。这样的综述有助于新进入该领域的研究人员避免重复过去的工作，并提供全面的概述，指导和鼓励读者致力于提高操作机器人故障诊断技术的有效性和实用性。
