Residual modelling and compensation for articulated arm coordinate measuring machines based on compound calibration and extreme learning machine

GAO Guanbin; XIE Pei; LIU Fei; NA Jing

doi:10.37188/OPE.20233122.3289

您当前的位置：

首页 >

文章列表页 >

Residual modelling and compensation for articulated arm coordinate measuring machines based on compound calibration and extreme learning machine

Micro/Nano Technology and Fine Mechanics | 更新时间：2023-11-28

- Residual modelling and compensation for articulated arm coordinate measuring machines based on compound calibration and extreme learning machine
- Optics and Precision Engineering Vol. 31, Issue 22, Pages: 3289-3304(2023)
- 作者机构：
  
  1.昆明理工大学机电工程学院，云南昆明 650500
- 作者简介：
- 基金信息：
- DOI：10.37188/OPE.20233122.3289
  CLC：
扫描看全文
高贯斌,谢佩,刘飞等.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.

GAO Guanbin,XIE Pei,LIU Fei,et al.Residual modelling and compensation for articulated arm coordinate measuring machines based on compound calibration and extreme learning machine[J].Optics and Precision Engineering,2023,31(22):3289-3304.
高贯斌,谢佩,刘飞等.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. DOI： 10.37188/OPE.20233122.3289.

GAO Guanbin,XIE Pei,LIU Fei,et al.Residual modelling and compensation for articulated arm coordinate measuring machines based on compound calibration and extreme learning machine[J].Optics and Precision Engineering,2023,31(22):3289-3304. DOI： 10.37188/OPE.20233122.3289.

摘要

运动学标定是提高关节臂式坐标测量机精度的主要方法，但运动学标定后的残余误差对其测量精度和稳定性仍有很大影响。本文提出一种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方法，以提高关节臂式坐标测量机的测量精度。首先，在关节臂式坐标测量机运动学建模和误差建模的基础上，建立了运动学参数辨识模型，并依次进行角度参数辨识、长度参数辨识和长度参数等比例缩放的复合辨识，完成了七自由度关节臂式坐标测量机的运动学标定。其次，通过对标定后残余误差图谱的分析，发现残余误差与测量构型有关联，进而构建了以测量摆角、仰角、距离和转角为变量的测量构型。由于测量构型变量与残余误差存在强非线性关系，提出一种基于极限学习机的残余误差预测和补偿方法。通过实验对本文所提模型及方法的有效性进行验证，结果表明：进行残差修正后关节臂式坐标测量机的单点测量误差最大值由0.061 mm下降到0.044 mm，误差均值由0.023 mm下降到0.017 mm，误差标准差由0.011 mm下降到0.007 mm；长度测量误差最大值由0.137 mm下降到0.074 mm，误差均值由0.033 mm下降到0.021 mm、误差标准差由0.037 mm下降到0.019 mm。

Abstract

Kinematic calibration is a common method for enhancing the accuracy of articulated arm coordinate measuring machines （AACMMs）. However， the residual errors after calibration can affect its measurement 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 AACMMs. 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 configuration variables and the residual errors. We verify the validity of the proposed method through experiments. 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 after 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 deviation 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

Keywords

Articulated Arm Coordinate Measuring Machines（AACMM)residualmeasuring configurationextreme learning machinecompound calibration

references

于连栋，赵会宁. 关节类坐标测量机关键技术及进展［J］. 仪器仪表学报， 2017， 38（8）： 1879-1888. doi: 10.3969/j.issn.0254-3087.2017.08.006http://dx.doi.org/10.3969/j.issn.0254-3087.2017.08.006

YU L D， ZHAO H N. Key technologies and advances of articulated coordinate measuring machines［J］. Chinese Journal of Scientific Instrument， 2017， 38（8）： 1879-1888.（in Chinese）. doi: 10.3969/j.issn.0254-3087.2017.08.006http://dx.doi.org/10.3969/j.issn.0254-3087.2017.08.006

余越，胡毅，胡鹏浩，等. 自驱动关节臂坐标测量机臂杆变形静态误差预测模型［J］. 仪器仪表学报， 2020， 41（8）： 37-46.

YU Y， HU Y， HU P H， et al. Static error prediction model of linkage deformation of self-driven articulated arm coordinate measuring machine［J］. Chinese Journal of Scientific Instrument， 2020， 41（8）： 37-46.（in Chinese）

KOVAC I， KLEIN A. Apparatus and a procedu-re to calibrate coordinate measuring arms［J］. Strojniški vestnik-Journal of Mechanical Engineering， 2002， 48（1）：17-32.

SHIMOJIMA K， FURUTANI R， TAKAMASU K， et al. The estimation method of uncertainty of articulated coordinate measuring machine［C］. 2002 IEEE International Conference on Industrial Technology， 2002. IEEE ICIT '02.11-14，2002， Bankok， Thailand. IEEE， 2003： 411-415.

YE D， CHE R， HUANG Q. Calibration for Kinematics Parameters of Articulated CMM［C］. Proceedings of the Second International Symp-osium on Instrumentation Science and Technology， 2002：3-145.

RIM C， RIM C H， CHEN G， et al. A kinematic calibration method of the articulated arm coordinate measuring machine using niching chaos optimization algorithm［J］. Journal of Testing and Evaluation， 2020， 48（4）： 20180174. doi: 10.1520/jte20180174http://dx.doi.org/10.1520/jte20180174

CHEN X Z， ZHAN Q. The kinematic calibration of an industrial robot with an improved beetle swarm optimization algorithm［J］. IEEE Robotics and Automation Letters， 2022， 7（2）： 4694-4701. doi: 10.1109/lra.2022.3151610http://dx.doi.org/10.1109/lra.2022.3151610

潘志康，祝连庆，郭阳宽. 基于内点法实现关节式坐标测量机参数标定［J］. 仪器仪表学报， 2018， 39（3）： 117-123.

PAN Z K， ZHU L Q， GUO Y K. Parameter calibration for articulated arm coordinate measuring machine based on interior point algorithm［J］. Chinese Journal of Scientific Instrument， 2018， 39（3）： 117-123.（in Chinese）

Parameter calibration for articulated arm coordinate measuring machine based on interior point algorithm

于连栋，曹家铭，赵会宁，等. 关节臂式坐标测量机的运动学建模［J］. 光学精密工程， 2021， 29（11）： 2603-2612. doi: 10.37188/OPE.20212911.2603http://dx.doi.org/10.37188/OPE.20212911.2603

YU L D， CAO J M， ZHAO H N， et al. Kinematics model of articulated arm measuring machine［J］. Opt. Precision Eng.， 2021， 29（11）： 2603-2612.（in Chinese）. doi: 10.37188/OPE.20212911.2603http://dx.doi.org/10.37188/OPE.20212911.2603

夏军勇，刘科进，钟飞，等. 运用改进的教学-模拟退火算法辨识关节臂式三坐标测量机的结构参数［J］. 中国机械工程， 2023， 34（3）314-323. doi: 10.3969/j.issn.1004-132X.2023.03.008http://dx.doi.org/10.3969/j.issn.1004-132X.2023.03.008

XIA J Y， LIU K J， ZHONG F， et al. Structural parameter identification for articulated arm coordinate measuring machines using modified teaching-learning-based optimization optimized by simulated annealing algorithm［J］. China Mechanical Engineering， 2023， 34（3）314-323（in Chinese）. doi: 10.3969/j.issn.1004-132X.2023.03.008http://dx.doi.org/10.3969/j.issn.1004-132X.2023.03.008

LUO G， ZOU L， WANG Z， et al. A novel kinematic parameters calibration method for industrial robot based on Levenberg-Marquardt and Differential Evolution hybrid algorithm［J］. Robotics and Computer-Integrated Manufacturing， 2021， 71： 102165. doi: 10.1016/j.rcim.2021.102165http://dx.doi.org/10.1016/j.rcim.2021.102165

BENCIOLINI B， VITTI A. A new quaternion based kinematic model for the operation and the identification of an articulated arm coordinate measuring machine inspired by the geodetic methodology［J］. Mechanism and Machine Theory， 2017， 112： 192-204. doi: 10.1016/j.mechmachtheory.2017.02.008http://dx.doi.org/10.1016/j.mechmachtheory.2017.02.008

冯旭刚，朱嘉齐，章家岩. 关节臂式坐标测量机的数学建模及参数标定［J］. 仪器仪表学报， 2019， 40（2）： 190-197.

FENG X G， ZHU J Q， ZHANG J Y. Mathematical model and parameter calibration of articulated arm coordinate measuring machine［J］. Chinese Journal of Scientific Instrument， 2019， 40（2）： 190-197.（in Chinese）

LU J， GAO G B. Kinematic modeling and simulation of articulated arm coordinate measuring machines based on MCPC method［C］. SPIE Proceedings， Sixth International Symposium on Precision Mechanical Measurements. Guiyang， China. SPIE， 2013： 932-937. doi: 10.1117/12.2035857http://dx.doi.org/10.1117/12.2035857

HUANG K， MO J， FU Z， et al. Screw theory-based mathematical model and parameter calibration for articulated arm coordinate measuring machine［J］. Journal of Huazhong University of Science and Technology. 2010， 38 （4）： 94-97.

RAMU P， YAGÜE JA， HOCKEN RJ， et al. Development of a parametric model and virtual machine to estimate task specific measurement uncertainty for a five-axis multi-sensor coordinate measuring machine［J］. Precision Engineering， 2011， 35（3）： 431-439. doi: 10.1016/j.precisioneng.2011.01.003http://dx.doi.org/10.1016/j.precisioneng.2011.01.003

LI C， WU Y Q， LÖWE H， et al. POE-based robot kinematic calibration using axis configuration space and the adjoint error model［J］. IEEE Transactions on Robotics， 2016， 32（5）： 1264-1279. doi: 10.1109/tro.2016.2593042http://dx.doi.org/10.1109/tro.2016.2593042

BOBY R A. Kinematic identification of industrial robot using end-effector mounted monocular camera bypassing measurement of 3-D pose［J］. IEEE/ASME Transactions on Mechatronics， 2022， 27（1）： 383-394. doi: 10.1109/tmech.2021.3064916http://dx.doi.org/10.1109/tmech.2021.3064916

HAMANA H， TOMINAGA M， OZAKI M， et al. Calibration of articulated arm coordinate measuring machine considering measuring posture［J］. International Journal of Automation Technology， 2011， 5（2）： 109-114. doi: 10.20965/ijat.2011.p0109http://dx.doi.org/10.20965/ijat.2011.p0109

许铀，熊会元，宗志坚，等. 基于测量臂构型的单点残差修正方法［J］. 仪器仪表学报， 2011， 32（4）775-780

XU Y， XIONG H Y， ZONG Z J， et al. Single-point residual correction method for multi-joint arm based on pose configuration［J］. Chinese Journal of Scientific Instrument， 2011， 32（4）775-780（in Chinese）

高群，许铀，于丽敏，等. 基于测量构型周期性特性的多关节测量系统残差修正方法［J］. 仪器仪表学报， 2018， 39（5）： 24-32. doi: 10.19650/j.cnki.cjsi.J1803078http://dx.doi.org/10.19650/j.cnki.cjsi.J1803078

GAO Q， XU Y， YU L M， et al. Residual correction method for articulated arm coordinate measuring machine based on configuration periodicity［J］. Chinese Journal of Scientific Instrument， 2018， 39（5）： 24-32.（in Chinese）. doi: 10.19650/j.cnki.cjsi.J1803078http://dx.doi.org/10.19650/j.cnki.cjsi.J1803078

ZHAO H N， YU L D， CAO J M， et al. Improving the measuring length accuracy of articulated arm coordinate measuring machine using artificial neural network［J］. Review of Scientific Instruments， 2020， 91（12）. doi: 10.1063/5.0028365http://dx.doi.org/10.1063/5.0028365

ZHAO G， ZHANG P， MA G， et al. System identification of the nonlinear residual errors of an industrial robot using massive measurements［J］. Robotics and Computer-Integrated Manufacturing， 2019， 59： 104-114. doi: 10.1016/j.rcim.2019.03.007http://dx.doi.org/10.1016/j.rcim.2019.03.007

NGUYEN HN， ZHOU J， KANG HJ. A calibration method for enhancing robot accuracy through integration of an extended Kalman filter algorithm and an artificial neural network［J］. Neurocomputing， 2015， 151： 996-1005. doi: 10.1016/j.neucom.2014.03.085http://dx.doi.org/10.1016/j.neucom.2014.03.085

DENAVIT J， HARTENBERG R S. A kinematic notation for lower-pair mechanisms based on matrices［J］. Journal of Applied Mechanics， 1955， 22（2）： 215-221. doi: 10.1115/1.4011045http://dx.doi.org/10.1115/1.4011045

高贯斌，王文，林铿，等. 应用改进模拟退火算法实现关节臂式坐标测量机的参数辨识［J］. 光学精密工程， 2009， 17（10）： 2499-2505. doi: 10.3321/j.issn:1004-924X.2009.10.023http://dx.doi.org/10.3321/j.issn:1004-924X.2009.10.023

GAO G B， WANG W， LIN K， et al. Parameter identification based on modified annealing algorithm for articulated arm CMMs［J］. Opt. Precision Eng.， 2009， 17（10）： 2499-2505.（in Chinese）. doi: 10.3321/j.issn:1004-924X.2009.10.023http://dx.doi.org/10.3321/j.issn:1004-924X.2009.10.023

CHENG L， WANG W， WENG Y X， et al. A novel kinematic parameters identification method for articulated arm coordinate measuring machines using repeatability and scaling factor［J］. Mathematical Problems in Engineering， 2018， 2018： 1-10. doi: 10.1155/2018/1760190http://dx.doi.org/10.1155/2018/1760190

许铀，高群. 基于光栅编码器的柔性测量臂位置精度研究［J］. 仪器仪表学报， 2017， 38（2）336-342. doi: 10.3969/j.issn.0254-3087.2017.02.010http://dx.doi.org/10.3969/j.issn.0254-3087.2017.02.010

XU Y， GAO Q. AACMM Position accuracy distribution research based on the accuracy of grating encoder［J］. Chinese Journal of Scientific Instrument， 2017， 38（2）336-342（in Chinese）. doi: 10.3969/j.issn.0254-3087.2017.02.010http://dx.doi.org/10.3969/j.issn.0254-3087.2017.02.010

HUANG G B， ZHU Q Y， SIEW C K. Extreme Learning Machine： A New Learning Scheme of Feedforward Neural Networks［C］. 2004 IEEE International Joint Conference on Neural Networks （IEEE Cat. No.04CH37541）.25-29， 2004， Budapest， Hungary. IEEE， 2005： 985-990. doi: 10.1109/ijcnn.2004.1380068http://dx.doi.org/10.1109/ijcnn.2004.1380068

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

FBG sensor of double-layer cross beam structure based on SSA-ELM three-dimensional force decoupling

Complex signal filter method for position sensitive devices application using a feedback stacking model based on extreme learning machine

Rapid identification of coffee bean variety by near infrared hyperspectral imaging technology

Identification of bruised kiwifruits during storage by near infrared spectroscopy and extreme learning machine

Related Author

No data

Related Institution

School of Mechatronics and Vehicle Engineering， Chongqing Jiaotong University

School of Intelligent Engineering， Chongqing College of Mobile Communication

Intelligent Detection and Equipment Department, ShenyangInstitute of Automation, Chinese Academy of Sciences

Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences

University of Chinese Academy of Sciences

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰