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作 者:李金和[1] Li Jinhe(The Ministry of Education Key Laboratory of Mechanism Theory and Equipment Design,Tianjin University,Tianjin 300354,China)
机构地区:[1]天津大学机构理论与装备设计教育部重点实验室,天津300354
出 处:《机械科学与技术》2019年第3期472-479,共8页Mechanical Science and Technology for Aerospace Engineering
基 金:国家自然科学基金面上项目(30553);国家科技重大专项(子课题)(33558)资助
摘 要:并联机器人运动学误差的标定是并联机器人工程应用的主要问题之一,测量位形的选择和辨识算法对参数辨识结果和误差补偿效果有重要影响。工程实践中,为了提高测量效率或者受到测量环境的限制,往往利用布置简单和数量较少的位形获取测量数据,这可能导致所构造的线性回归模型出现强复共线性,为此提出了一种残差比例指标的测量位形优选方法和一种主元分析的几何误差源辨识算法来实现变量空间的降维操作,二者可有效地提高测量效率,改善辨识算法的鲁棒性和抗差能力。通过计算机仿真验证了所提方法正确可行。The calibration of kinematic error of parallel robot is one of the main problems in the application of parallel robot.The selection and identification algorithm of measuring positions has important influence on the result of parameter identification and the effect of error compensation.In engineering practice,in order to improve the efficiency of measurement or to be restricted by the measurement environment,measurement data are often obtained with simple position and less number of positions,which may lead to the strong complex collinearity in the linear regression model.Using the means of residual proportion index and the principal component analysis(PCA),the algorithms for optimal measurement configuration selection and robust source error identification are investigated to realize the dimensionality reduction of the variable space,two important issues for improving the measurement efficiency as well as identification accuracy.Computer simulation shows that the proposed method is correct and feasible.
分 类 号:TG80[金属学及工艺—公差测量技术] TB92[一般工业技术—计量学]
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