机器人操纵器的故障类型和诊断方法:一篇评论
Yuepeng Zhang1,2, Jun Wu1,2, Bo Gao1,2
1School of Sino-German Robotics, Shenzhen Institute of Information Technology, Shenzhen 518172, China.
Sensors (Basel, Switzerland)
|April 28, 2025
概括
本综述全面总结了操纵机器人的故障诊断方法,超越了单个故障分析. 它强调了人工智能和数字双胞胎等进步,这对智能制造至关重要.
科学领域:
- 机器人和自动化 机器人和自动化
- 智能制造系统是一个智能制造系统.
- 错误诊断和预测 错误诊断和预测
背景情况:
- 操纵机器人对于智能制造和工业转型至关重要.
- 有效的故障诊断对于制造商和用户来说越来越重要.
- 现有的审查往往缺乏对各种故障诊断方法的全面概述.
研究的目的:
- 为操纵机器人提供各种故障类型和诊断方法的全面审查.
- 为新研究人员提供更清晰的理解,避免重复努力.
- 确定机器人操纵器故障诊断的未来研究机会和挑战.
主要方法:
- 分析传感器数据,包括电压,电流,转速,扭矩,振动,温度和声音.
- 从频率角度探讨故障特征的探索.
- 审查新兴技术,如专家系统,人工智能和数字双胞胎.
主要成果:
- 确定了对操纵机器人多种故障类型的全面审查中的差距.
- 详细介绍了各种信号处理技术和先进的诊断方法.
- 突出了从人类介入诊断向自动化和智能化方法的转变.
结论:
- 对操纵机器人故障诊断的整体审查对于推进该领域至关重要.
- 新兴技术为提高诊断效率和实用性提供了巨大的潜力.
- 本综述是研究人员专注于关键挑战和机会的指南.
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