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Published on: December 14, 2011
工业机器人减速器测试仪器动态扭矩测量误差校准,基于Bisquare曲线拟合-改进的贝叶斯粒子群优化-非线性回声状态网络 (BCF-IBPSO-NESN) 方法
Zhen Yu1, Yuan Zhang2, Xiaomin Liu3
1Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences), Qingdao 266061, China.
这项研究引入了一种新方法,用于校准工业机器人减速器的动态扭矩测量误差. 改进的贝叶斯粒子群优化-非线性回声状态网络 (BCF-IBPSO-NESN) 算法显著提高了机器人减速器测试仪器的测量精度.
科学领域:
- 机器人和自动化 机器人和自动化
- 计量学和测量科学 计量学和测量科学
- 机械工程 机械工程
背景情况:
- 工业机器人在制造业中至关重要,减速器显著影响其性能.
- 准确的测试仪器对于高质量的工业机器人减速机至关重要.
- 校准动态扭矩测量误差对于减速器测试仪器精度至关重要.
研究的目的:
- 分析工业机器人减速器测试仪器中动态扭矩测量误差的特征.
- 为实时动态扭矩测量误差提出和验证一种新的校准方法.
- 提高工业机器人减速器性能评估的准确性和可靠性.
主要方法:
- 动态扭矩测量误差的特征分析.
- 开发Bisquare曲线拟合-改进贝叶斯粒子群优化-非线性回声状态网络 (BCF-IBPSO-NESN) 算法进行校准.
- 在各种负载条件下实时校准动态扭矩测量误差.
主要成果:
- 拟议的BCF-IBPSO-NESN方法有效校准了动态扭矩测量误差.
- 实现了将测量误差降低到输入侧±0.05 Nm,输出侧±1 Nm.
- 证明了该方法在任何负载条件下对错误校准的能力.
结论:
- 开发的BCF-IBPSO-NESN方法为校准动态扭矩测量误差提供了有效的解决方案.
- 这项研究为校准工业机器人减速器测试仪器提供了有价值的指南.
- 这些发现有助于通过精确的减速器测量来提高工业机器人的整体质量和性能.
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