...
首页> 外文期刊>Robotics and Computer-Integrated Manufacturing >Kinematic calibration of a 5-DOF hybrid kinematic machine tool by considering the ill-posed identification problem using regularisation method
【24h】

Kinematic calibration of a 5-DOF hybrid kinematic machine tool by considering the ill-posed identification problem using regularisation method

机译:考虑正则化方法的不适定识别问题的五自由度混合运动机床运动学标定

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Geometric accuracy is one of bottleneck problems restricting the extension of application of the hybrid kinematic machine (HKM). On the premise of having a certain basic manufacturing accuracy, kinematic calibration is an effective means of improving the geometric accuracy of HKMs. In the study, the kinematic calibration technology of a new-type 5-degree of freedom (DOF) HKM was investigated. Moreover, by applying regularisation method, the problem whereby the identification algorithm shows poor robustness due to the presence of an ill-posed identification matrix during error identification was solved. At first, a geometric error model for the HKM satisfying completeness and minimality was established based on screw theory. Then, when identifying error parameters, two indices for evaluating the effectiveness of identification algorithms were proposed: on this basis, the stabilities of solutions obtained through four regularisation identification algorithms and the predictive capability of solutions for the model was analysed and compared by simulated experiment. Additionally, the influence of measurement noises at different levels on five identification algorithms was explored. Finally, an error compensation strategy was proposed and a kinematic calibration experiment was conducted. The test results showed that, after kinematic calibration, the position and orientation errors of the HKM within the whole workspace separately reduced to less than 0.054 mm and less than 0.041(Q), thus validating the effectiveness of the proposed method.
机译:几何精度是制约混合运动学机器(HKM)应用范围扩展的瓶颈问题之一。在具有一定基本制造精度的前提下,运动学标定是提高HKM几何精度的有效手段。在研究中,研究了新型5自由度(DOF)HKM的运动学校准技术。此外,通过应用正则化方法,解决了由于错误识别期间存在不适的识别矩阵而导致识别算法显示出较差的鲁棒性的问题。首先,基于螺旋理论建立了HKM满足完整性和最小性的几何误差模型。然后,在识别误差参数时,提出了两种评价识别算法有效性的指标:在此基础上,通过四种正则化识别算法获得的解的稳定性,并通过仿真实验对模型的解的预测能力进行了比较和比较。另外,探讨了不同级别的测量噪声对五种识别算法的影响。最后提出了误差补偿策略,并进行了运动学标定实验。测试结果表明,运动学校正后,HKM在整个工作空间内的位置和方向误差分别减小至小于0.054 mm和小于0.041(Q),从而验证了该方法的有效性。

著录项

  • 来源
  • 作者单位

    Tianjin Univ, Sch Marine Sci & Technol, Tianjin 300072, Peoples R China|Tianjin Univ, Key Lab Mech Theory & Equipment Design, Minist Educ, Tianjin 300072, Peoples R China|Univ Warwick, Sch Engn, Coventry CV4 7AL, W Midlands, England;

    Tianjin Univ, Sch Marine Sci & Technol, Tianjin 300072, Peoples R China;

    Tianjin Univ, Key Lab Mech Theory & Equipment Design, Minist Educ, Tianjin 300072, Peoples R China;

    Tianjin Univ, Key Lab Mech Theory & Equipment Design, Minist Educ, Tianjin 300072, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Hybrid kinematic machine; Error identification; Ill-posed problem; Regularisation method;

    机译:混合运动机;错误识别;令人虐待问题;正规化方法;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号