Determination method of optimal measurement area of CNC machine tool on-machine measurement system

ZHANG Shuangshuang; YANG Hongtao; MA Qun; LI Li

doi:10.37188/OPE.20233104.0491

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Determination method of optimal measurement area of CNC machine tool on-machine measurement system

Micro/Nano Technology and Fine Mechanics | 更新时间：2023-02-28

- Determination method of optimal measurement area of CNC machine tool on-machine measurement system
- Optics and Precision Engineering Vol. 31, Issue 4, Pages: 491-502(2023)
- 作者机构：
  
  1.安徽理工大学机械工程学院，安徽淮南 232001
  2.安徽理工大学安徽省矿山智能装备与技术重点实验室，安徽淮南 232001
- 作者简介：
- 基金信息：
- DOI：10.37188/OPE.20233104.0491
  CLC： TH721
- Received：11 August 2022，
  
  Revised：30 August 2022，
  
  Published：25 February 2023
- 稿件说明：
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张双双,杨洪涛,马群等.数控机床在机测量系统最佳测量区确定方法[J].光学精密工程,2023,31(04):491-502.

ZHANG Shuangshuang,YANG Hongtao,MA Qun,et al.Determination method of optimal measurement area of CNC machine tool on-machine measurement system[J].Optics and Precision Engineering,2023,31(04):491-502.
张双双,杨洪涛,马群等.数控机床在机测量系统最佳测量区确定方法[J].光学精密工程,2023,31(04):491-502. DOI： 10.37188/OPE.20233104.0491.

ZHANG Shuangshuang,YANG Hongtao,MA Qun,et al.Determination method of optimal measurement area of CNC machine tool on-machine measurement system[J].Optics and Precision Engineering,2023,31(04):491-502. DOI： 10.37188/OPE.20233104.0491.

摘要

为研究面向不同测量对象且具有普适性的数控机床在机测量系统最佳测量区确定方法，选择球作为测量对象，分析了在机测量系统的工作原理及误差来源，利用BAS-BP神经网络建立了单项几何误差白化模型，同时建立了测量系统综合误差模型和球测量误差模型。研究了用于确定最佳测量区搜索寻优的差分优化布谷鸟（DE-CS）算法，进行了不同算法搜索性能对比，确定了算法最优性能参数。搭建了确定球最佳测量区的实验装置，进行了相应实验，对比了利用算法确定和实际测量得到的最佳测量位置的一致性。实验结果表明，利用上述方法搜索计算确定的面向球最佳测量区位置与实验测量确定的最佳测量区位置一致，最佳测量区为：

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38.35400009

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，实测最大误差最小值为3.1 μm，算法求解的误差也为整个测量空间的最小值0.710 7 μm，且可用于面向点、面等其他测量对象的最佳测量区确定，具有普适性，可用于确定在机测量系统的最佳测量区。

Abstract

To better understand the method for determining the optimal measurement area of a computerized numerical control （CNC） machine tool in-machine measurement system with different measurement objects and universal application， a ball is selected as the measurement object， and the working principle and error sources of the in-machine measurement system are analyzed. A single error-whitening model is established using a dual-frequency laser interferometer and a beetle antenna search algorithm backpropagation （BAS-BP） neural network measurement. Simultaneously， the comprehensive error model of the measurement system and the spherical measurement error model are established. The differential evolution cuckoo search （DE-CS） algorithm for determining the optimal measurement area search is studied. The search performances of different algorithms are compared， and the optimal performance parameters of the algorithm are determined. An experimental device is set up to determine the optimal measurement area of the sphere， and the corresponding experiments are carried out. Finally， the consistency of the optimal measurement position determined by the algorithm and the actual measurement is compared. The experimental results show that the spherical optimal measurement area obtained by the aforementioned method is consistent with that obtained experimentally， and can be used to determine the optimal measurement area of other measurement objects， such as points， planes， and so on. The proposed system is demonstrated to be universally applicable and capable of determining the optimal measurement area of machine measurement systems.

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