光学精密工程2023，Vol.31Issue(22)：3289-3304,16.DOI:10.37188/OPE.20233122.3289
基于复合标定和极限学习机的关节臂式坐标测量机残差建模及补偿
Residual modelling and compensation for articulated arm coordinate measuring machines based on compound calibration and extreme learning machine
摘要
Abstract
Kinematic calibration is a common method for enhancing the accuracy of articulated arm coordi-nate measuring machines(AACMMs).However,the residual errors after calibration can affect its mea-surement accuracy and stability.In this study,we propose a residual error compensation method based on a compound calibration and extreme learning machine to improve the measurement accuracy of AAC-MMs.First,we establish the kinematic parameter identification model based on the kinematic modeling of AACMM.Furthermore,we conduct angle parameter identification,length parameter identification,and length parameter scaling to complete the compound kinematic calibration.Subsequently,we construct the measurement configuration with the measurement angle,elevation angle,distance,and rotation angle as variables to analyze the residual error map.The proposed residual error compensation method is based on an extreme learning machine owing to the strong nonlinear relationship between the measurement configu-ration variables and the residual errors.We verify the validity of the proposed method through experi-ments.The results show that the maximum value of the single point measurement error of the AACMM decreases from 0.061 mm to 0.044 mm,the mean value of measurement error decreases from 0.023 mm to 0.017 mm,and the standard deviation of measurement error decreases from 0.011 mm to 0.007 mm af-ter residual correction.Furthermore,the maximum length measurement error decreases from 0.137 mm to 0.074 mm,the mean measurement error decreases from 0.033 mm to 0.021 mm,and the standard de-viation of measurement error decreases from 0.037 mm to 0.019 mm.关键词
关节臂式坐标测量机/残余误差/测量构型/极限学习机/复合标定Key words
Articulated Arm Coordinate Measuring Machines(AACMM)/residual/measuring configura-tion/extreme learning machine/compound calibration分类
计算机与自动化引用本文复制引用
高贯斌,谢佩,刘飞,那靖..基于复合标定和极限学习机的关节臂式坐标测量机残差建模及补偿[J].光学精密工程,2023,31(22):3289-3304,16.基金项目
国家自然科学基金资助项目(No.52265001) （No.52265001）
云南省科技厅基础研究重点项目资助(No.202201AS070033) （No.202201AS070033）
