• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2023, Vol. 59 ›› Issue (11): 147-158.doi: 10.3901/JME.2023.11.147

• 机器人及机构学 • 上一篇    下一篇

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工业机器人参数容差稳健性设计

吴锦辉1,2, 张德权1,3, 韩旭1,2,3   

  1. 1. 河北工业大学省部共建电工装备可靠性与智能化国家重点实验室 天津 300401;
    2. 河北工业大学电气工程学院 天津 300401;
    3. 河北工业大学机械工程学院 天津 300401
  • 收稿日期:2022-06-21 修回日期:2022-12-26 出版日期:2023-06-05 发布日期:2023-07-19
  • 通讯作者: 韩旭(通信作者),男,1968年出生,博士,教授,博士研究生导师。主要研究方向为基于数值模拟的设计理论与方法、反问题理论与方法、不确定分析和可靠性设计。E-mail:xhan@hebut.edu.cn
  • 作者简介:吴锦辉,男,1991年出生,博士,讲师。主要研究方向为工业机器人可靠性分析与设计。E-mail:wujinhui@hebut.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(52105249)

Robust Design of Parameter Tolerance to Industrial Robot

WU Jinhui1,2, ZHANG Dequan1,3, HAN Xu1,2,3   

  1. 1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300401;
    2. School of Electrical Engineering, Hebei University of Technology, Tianjin 300401;
    3. School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401
  • Received:2022-06-21 Revised:2022-12-26 Online:2023-06-05 Published:2023-07-19

摘要: 为降低工业机器人定位精度可靠性对运动学和动力学不确定参数的敏感性,基于工业机器人定位误差信噪比,提出了工业机器人运动学和动力学不确定参数容差稳健性优化设计方法。针对工业机器人动力学方程求解耗时问题,基于径向基函数神经网络建立了工业机器人动力学方程求解过程的代理模型,有效提高了工业机器人定位误差仿真效率。采用遗传算法求解所建立的稳健性优化设计模型,同时还分别以工业机器人定位误差平均值和定位误差信噪比并考虑加工成本为目标函数,对工业机器人不确定参数容差进行了优化设计。最后,以各优化结果作为不确定参数标准差,比较分析了工业机器人定位精度可靠性及定位精度可靠性敏感性,验证了所建立的工业机器人运动学和动力学参数容差稳健性设计方法的有效性。

关键词: 工业机器人, 可靠性分析, 稳健性设计, 定位误差, 可靠性敏感性

Abstract: To reduce the sensitivity of positional accuracy reliability to kinematic and dynamic uncertain parameters of industrial robots, a robust optimization design method for kinematic and dynamic uncertain parameter tolerance is established based on the signal-to-noise ratio (SNR) of positional error. Aiming at the time-consuming problem of solving the dynamic equations to industrial robots, an efficient radial basis function neural network surrogate model for solving the dynamic equations of industrial robots is established, which effectively improved the efficiency of positional error simulation of industrial robots. The robust optimization design model is solved by genetic algorithm. Besides, the kinematic and dynamic uncertain parameter tolerance of industrial robots is optimized by taking the mean value of positional error and the SNR and the processing cost as the objective functions. Finally, the optimization results of the above three optimization objective function are treated as standard deviation of uncertain parameters, the positional accuracy reliability and positional accuracy reliability sensitivity of industrial robots are comparative analyzed. The effectiveness of the proposed robust design method of the kinematic and dynamic parameters tolerances for industrial robots is demonstrated.

Key words: industrial robot, reliability analysis, robust design, positional error, reliability sensitivity

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