绝对式光栅尺测量精度补偿方法研究
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摘要
文章研究绝对式光栅尺测量精度的影响因素,探索提高绝对式光栅尺测量精度的补偿算法。通过分析绝对式光栅尺测量精度的影响因素设计出绝对式光栅尺测量精度检测平台,在该平台上进行多次精度测量,得到误差曲线;根据误差曲线的特性,依次采用一次线性补偿,分段线性补偿和基于径向函数的神经网络补偿算法进行修正,并写入到绝对式光栅尺读数头内。从实验结果显示,绝对式光栅尺经过一次线性算法补偿后,精度提高到2.8μm,经过分段线性算法补偿后精度提高到1.08μm,经过基于径向函数的神经网络算法补偿后精度可提到0.65μm。表明以上三种算法都能达到对绝对式光栅尺测量精度进行补偿目的,对绝对式光栅尺精度的提高具有较大意义。
This paper studies the influencing factors of the accuracy of absolute linear encoder measurement,and explores the compensation algorithm to improve the accuracy of absolute linear encoder measurement. Through the analysis of the influence factors,the measurement platform is designed,and the error curve is obtained on this platform by performing multiple precision measurements. Based on the characteristics of the error curve,the linear compensation,the piecewise linear compensation and the neural network compensation algorithm based on the radial function are used to correct the error curve and write to the absolute linear encoder's reading head. The experimental results showthat the precision of the absolute linear encoder is improved to ± 2. 8μm after a linear algorithm compensation,and the precision is improved to ± 1. 08μm after the compensation of the piecewise linear algorithm.,and after the compensation of the neural network algorithm based on the radial function Mention,the precision improved to ± 0. 65μm. It is shown that the above three algorithms can achieve the purpose of compensating the accuracy of absolute linear encoder,and it is of great significance to improve the accuracy of absolute linear encoder.
This paper studies the influencing factors of the accuracy of absolute linear encoder measurement,and explores the compensation algorithm to improve the accuracy of absolute linear encoder measurement. Through the analysis of the influence factors,the measurement platform is designed,and the error curve is obtained on this platform by performing multiple precision measurements. Based on the characteristics of the error curve,the linear compensation,the piecewise linear compensation and the neural network compensation algorithm based on the radial function are used to correct the error curve and write to the absolute linear encoder's reading head. The experimental results showthat the precision of the absolute linear encoder is improved to ± 2. 8μm after a linear algorithm compensation,and the precision is improved to ± 1. 08μm after the compensation of the piecewise linear algorithm.,and after the compensation of the neural network algorithm based on the radial function Mention,the precision improved to ± 0. 65μm. It is shown that the above three algorithms can achieve the purpose of compensating the accuracy of absolute linear encoder,and it is of great significance to improve the accuracy of absolute linear encoder.
引文
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[2]吴宏圣.应用于数控机床的绝对式光栅尺[J].世界制造技术与装备市场,2013(3):74-77.
[3]范朝龙,王晗,刘强,等.精密宏微复合绝对式光栅尺设计与研究[J].应用光学,2015,36(20):287-292.
[4]乔栋,续志军,吴宏圣,等.绝对式光栅尺细分误差补偿方法[J].光学学报,2015,35(1):69-73.
[5]许志涛,刘金国,龙科慧,等.高分辨率空间相机调焦机构精度分析[[J].光学学报,2013,33(7):276-281.
[6]吕孟军.光栅莫尔条纹电子学细分技术研究[D].南京:南京航空航天大学,2008.
[7]Yu Honglin,Huang Liangming,Wang Yuangan.Study on DSP filter and subdivision of moire fringes signal[J].Opto-Electronic Engineering,2004,31(9):61-65.
[8]常丽,许会,修国一.基于相关和最小二乘原理的光栅栅距动态测量[[J].仪器仪表学报,2013,34(5):1001-1007.
[9]冯英翘,万秋华,孙英,等.近似三角波莫尔条纹光电信号的细分误差修正[[J].光学学报,2013,33(8):106-110.
[10]吴宏圣,曾琪峰,乔栋,等.提高光栅莫尔条纹信号质量的滤波方法[[J].光学精密工程,2011,19(8):1944-1949.
[11]楚兴春,吕海宝,赵尚弘.基于傅里叶变换的高精度条纹细分方法[J].光学学报,2007,27(12):2179-2183.
[12]张勇,王选择,郭桂珍.一种提高光栅尺测量精度的有效方法[J].湖北工学院学报,2002,17(4):99-101.
[13]乔栋,续志军,吴宏圣,等.基于回归分析的绝对式光栅尺精度提高方法[J].华中科技大学学报(自然科学版),2015,43(1):71-74.
[14]乔栋.高精度绝对式光栅尺测量技术研究[D].北京:中国科学院研究生院,2015.
[15]孙强.高精度绝对式光栅尺研究进展及技术难点[J].世界制造技术与装各市场,2012(5):72-73.
[16]郑黎明.绝对式光栅尺产品的精度检测设备与精度修正方法[J].机电产品开发与创新,2015(4):92-93.
[17]于海,梁立辉,王树洁,等.基于径向基函数神经网络的高精度基准编码器误差补偿[J].红外与激光工程,2014,43(12):4123-4127.