工业机器人的自主模式分析方法,考虑动态空间灵敏度和激发随机性
Yongkang Jiao1, Xubing Chen1,2, Yili Peng3,4
1School of mechanical and electrical engineering, Wuhan Institute of Technology, Wuhan, 430205, China.
本研究介绍了工业机器人的自主模式分析方法,可以在操作过程中准确识别动态参数. 该方法通过解决姿势变化和随机激发力来提高削精度和效率.
科学领域:
- 机械工程 机械工程
- 机器人技术 机器人技术 机器人技术
- 振动分析 振动分析
背景情况:
- 工业机器人对于加工复杂的表面至关重要,但它们的动态特性会影响加工性能.
- 在操作过程中准确识别动态参数对于抑制振动和提高效率至关重要.
- 现有的运行模态分析 (OMA) 方法不适合机器人,原因是非白噪声激发和改变姿势.
研究的目的:
- 为工业机器人提出一种自主模式分析方法,该方法可以考虑动态空间灵敏度和随机激发.
- 为了能够在运行条件下准确识别动态参数,尽管存在变化.
主要方法:
- 基于模态形状预测自然频率灵敏度的方法,以限制自我激发的运动范围.
- 使用全级扭矩投影矩阵确定随机激发力方向的条件.
- 通过多关节随机加速/减速生成宽带随机信号,以激发白噪声.
主要成果:
- 提出的方法有效地减轻了对模态参数识别的姿势变化的影响.
- 成功生成了符合白噪声要求的宽带随机激发信号.
- 实验验证证了自主模式分析方法的有效性.
结论:
- 开发的自主模式分析方法提高了工业机器人削操作的准确性和效率.
- 这种方法为在现实的操作条件下识别机器人动态参数提供了可靠的解决方案.
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