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天津大学 精密测试技术及仪器国家重点实验室,天津 300072
[ "裘祖荣(1958-),男,上海人,教授,博士生导师,1981年、1995年于太原工业大学分别获得学士、硕士学位,2000年于天津大学获得博士学位,主要从事精密机械设计、精密仪器设计、传感器等方面的教学和科研工作。 E-mail:qzr@tju.edu.cn" ]
[ "周 磊(1998-),男,陕西渭南人,硕士研究生,2019年于天津大学获得学士学位,主要从事光电自准直技术以及精密减速器检测仪器方面的研究。E-mail:zhoulei_@tju.edu.cn" ]
收稿日期:2021-05-25,
修回日期:2021-06-28,
纸质出版日期:2021-11-15
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裘祖荣,周磊,薛洁等.精密减速器检测仪测角误差补偿[J].光学精密工程,2021,29(11):2622-2631.
QIU Zu-rong,ZHOU Lei,XUE Jie,et al.Angle error compensation of precision reducer tester[J].Optics and Precision Engineering,2021,29(11):2622-2631.
裘祖荣,周磊,薛洁等.精密减速器检测仪测角误差补偿[J].光学精密工程,2021,29(11):2622-2631. DOI: 10.37188/OPE.20212911.2622.
QIU Zu-rong,ZHOU Lei,XUE Jie,et al.Angle error compensation of precision reducer tester[J].Optics and Precision Engineering,2021,29(11):2622-2631. DOI: 10.37188/OPE.20212911.2622.
针对圆光栅安装倾斜、光栅变形等因素造成的精密减速器检测仪测角系统精度降低,传统误差补偿方法采样点数受多面棱体工作面限制,导致补偿效果不足的问题,提出一种多数据关联的误差补偿方法。采用自准直仪结合正24面棱体对圆光栅测角误差进行标定,通过改变多面棱体与圆光栅在周向方向上的相对位置,得到多组测角误差标定数据。利用误差谐波法对多组测量数据进行预处理,将不同组数据关联,并代入BP神经网络中训练,得到圆光栅测角误差模型。该方法无需计算补偿式,能够克服误差谐波法在样本点过多时易产生拟合震荡的问题。实验结果表明:本文所提出的补偿方法残差峰峰值在0.94″内,标准差为0.25″,分别减小至误差谐波法修正后的33.3%和37.9%,有效提高了圆光栅测角系统的精度,使减速器检测仪测角精度达到亚角秒级。
This study was aimed at dealing with the reduction in the precision of the angle measurement system in precision reducers due to the installation tilt and the deformation of the circular grating. The traditional error compensation method is limited by the number of working faces of the multi-sided prism, making the compensation effect insufficient. Thus, an error compensation method based on multi-data correlation was proposed. The autocollimator was combined with a regular 24-sided prism and used to calibrate the angle measurement error of the circular grating. By changing the relative position of the polyhedral prism and the circular grating in the circumferential direction, several groups of calibration data for the measurement of the angle error were obtained. The harmonic wave error compensation method was then used to preprocess multiple groups of measurement data; subsequently, the different groups of data were correlated and trained by a back propagation neural network to obtain the angular error model for the circular grating. This method does not need to employ the compensation formula, and it can also overcome the problem of fitting oscillation data when there are several sample points in the harmonic wave error compensation method. The experimental results show that the peak value for the residual error of the proposed compensation method is within 0.94" and the standard deviation is 0.25"; these values are 33.3% and 37.9% less than those of the traditional harmonic wave error compensation method, respectively. The proposed method effectively improves the accuracy of the angle measuring system to a sub-arc second level.
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