基于BP神经网络的数控机床综合误差补偿方法

王洪乐 1; 王家序 1; 2; 周青华 1; 熊青春 1; 3; 魏子淇 1

doi:10.7652/xjtuxb201706022

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基于BP神经网络的数控机床综合误差补偿方法

更新时间：2025-07-09

- 基于BP神经网络的数控机床综合误差补偿方法
- Comprehensive Error Compensation of Machine Tools Based on BP-Neural Network Algorithm
- 西安交通大学学报 2017年51卷第6期页码：138-146
- 作者机构：
  
  四川大学空天科学与工程学院,成都,610065
- 作者简介：
- 基金信息：
  
  : 2016-11-21。作者简介: 王洪乐(1988—),男,硕士生;周青华(通信作者),男,讲师。基金项目: 国家自然科学基金资助项目(51435001,51405316);中航工业产学研专项资助项目(cxy2013CD36);中央高校基本科研业务费专项资金资助项目(2014SCU11062)
- DOI：10.7652/xjtuxb201706022
  中图分类号： TH161
- 网络首发：2017-06-10，
  
  纸质出版：2017
- 稿件说明：
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王洪乐 1, 王家序 1, 2, 等. 基于BP神经网络的数控机床综合误差补偿方法[J]. 西安交通大学学报, 2017,51(6):138-146.

Comprehensive Error Compensation of Machine Tools Based on BP-Neural Network Algorithm[J]. 2017, 51(6): 138-146.
王洪乐 1, 王家序 1, 2, 等. 基于BP神经网络的数控机床综合误差补偿方法[J]. 西安交通大学学报, 2017,51(6):138-146. DOI： 10.7652/xjtuxb201706022.

Comprehensive Error Compensation of Machine Tools Based on BP-Neural Network Algorithm[J]. 2017, 51(6): 138-146. DOI： 10.7652/xjtuxb201706022.

摘要

针对多轴数控机床热影响导致的加工精度衰减问题

结合神经网络自学习与数据拟合能力

提出基于优化BP神经网络的多轴数控机床综合误差补偿方法。针对BP神经网络神经元误差曲面下降缓慢影响收敛效率的问题

引入陡度因子和放大因子

并基于此对数控机床运动轴加工精度进行预测和补偿。将大型A/B双摆角龙门数控铣床各关键发热源的温度检测数据和运动轴误差检测数据作为精度预测模型的输入量和输出量

采用改进后的BP神经网络进行训练

获得温度变化与位移误差量之间的非线性映射关系

并据此修改被加工工件的刀位数据文件

实现数控机床加工精度的提高。模拟算例和实验结果表明

该方法降低了传统BP神经网络的预测误差和运算时间

对机床平均误差补偿率达到50%以上。开发的数控机床误差补偿系统无须对现有机床进行大规模硬件改造

应用简便易于推广。

Abstract

Machining precision is attenuated by thermal factors. Making use of neural network's strong self-learning and data fitting ability

a novel method based on improved BP-neural network algorithm is proposed for comprehensive error compensation of multi-axis machine tools. An improved algorithm introducing steepness factor and amplification factor is presented to improve the convergence efficiency affected by slow decline of neurons error surface

and to predict and compensate machining precision of motion axes. The measured data of the temperature of each key heat source and displacement errors of motion axis of the large A/B double-pendulum angle gantry milling machine are respectively regarded as input and output. A machining precision error prediction model of machine tool is established and trained by the improved BP-neural network. The nonlinear relationship between temperature and displacement errors is obtained. Cutter location data file of workpiece is modified accordingly and machining precision is improved. Simulation and experiments indicate that this method reduces the prediction errors and computing period compared with the conventional BP-neural network. It is unnecessary to greatly reform the existing machine tools for application of the comprehensive error compensation system.

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references

周志雄, 周秦源, 任莹辉. 复杂曲面加工技术的研究现状与发展趋势 [J]. 机械工程学报, 2010, 46(17): 105-113.

ZHOU Zhixiong, ZHOU Qinyuan, REN Yinghui. Current research and development trends of complex surface machining technology [J]. Chinese Journal of Mechanical Engineering, 2010, 46(17): 105-113.

王海同, 李铁民, 王立平, 等. 机床热误差建模研究综述 [J]. 机械工程学报, 2015, 51(9): 119-128.

WANG Haitong, LI Tiemin, WANG Liping, et al. Review on thermal error modeling of machine tools [J]. Journal of Mechanical Engineering, 2015, 51(9): 119-128.

刘明, 章青. 运用多体理论和神经网络的机床热误差补偿 [J]. 振动、测试与诊断, 2010, 30(6): 657-661.

LIU Ming, ZHANG Qing. Thermal error model and compensation of machining tool using multibody system theory and neural network [J]. Journal of Vibration, Measurement Diagnosis, 2010, 30(6): 657-661.

YANG S, YUAN J, NI J. The improvement of thermal error modeling and compensation on machine tools by CMAC neural network [J]. International Journal of Machine Tools and Manufacture, 1996, 36(4): 527-537.

YANG H, NI J. Dynamic neural network modeling for nonlinear, nonstationary machine tool thermally induced error [J]. International Journal of Machine Tools and Manufacture, 2005, 45(4/5): 455-465.

张毅, 杨建国. 基于灰色神经网络的机床热误差建模 [J]. 上海交通大学学报, 2011, 45(11): 1581-1586.

ZHANG Yi, YANG Jianguo. Grey neural network modeling for machine tool thermal error [J]. Journal of Shanghai Jiaotong University, 2011, 45(11): 1581-1586.

郭前建, 杨建国. 基于蚁群算法的机床热误差建模技术 [J]. 上海交通大学学报, 2009, 45(3): 803-806.

GUO Qianjian, YANG Jianguo. Thermal error modeling on machine tools based on ant colony algorithm [J]. Journal of Shanghai Jiaotong University, 2009, 45(3): 803-806.

张秋菊, 赵一丁, 毛军红, 等. 模糊自学习误差补偿方法及其在位置误差补偿中的应用 [J]. 西安交通大学学报, 1995, 29(2): 67-72.

ZHANG Qiuju, ZHAO Yiding, MAO Junhong, et al. A method of fuzzy self-learning error compensation and its application in positional error compensation [J]. Journal of Xi'an Jiaotong University, 1995, 29(2): 67-72.

HSU Y Y, WANG S S. A new compensation method for geometry errors of five-axis machine tools [J]. International Journal of Machine Tools and Manufacture, 2007, 47(2): 352-360.

张宏韬, 杨建国, 姜辉, 等. 双转台五轴数控机床误差实时补偿 [J]. 机械工程学报, 2010, 46(21): 143-148.

ZHANG Hongtao, YANG Jianguo, JIANG Hui, et al. Real-time error compensation for the two turntable five-axis NC machine tools [J]. Chinese Journal of Mechanical Engineering, 2010, 46(21): 143-148.

何春燕, 李为民, 张建军, 等. 三轴立式加工中心几何误差补偿方法的研究 [J]. 兵工学报, 2012, 33(12): 1516-1520.

HE Chunyan, LI Weimin, ZHANG Jianjun, et al. Study on compensation method of geometric error for three-axis machining center [J]. Acta Armamentarii, 2012, 33(12): 1516-1520.

LEI W T, HSU Y Y. Accuracy test of five-axis CNC machine tool with 3D probe-ball: part I Design and modeling [J]. International Journal of Machine Tools and Manufacture, 2002, 42(10): 1153-1162.

LEI W T, HSU Y Y. Accuracy test of five-axis CNC machine tool with 3D probe-ball: part II Errors estimation [J]. International Journal of Machine Tools and Manufacture, 2002, 42(10): 1163-1170.

LEI W T, HSU Y Y. Accuracy enhancement of five-axis CNC machines through real-time error compensation [J]. International Journal of Machine Tools and Manufacture, 2003, 43(9): 871-877.

王维, 杨建国. 基于插值算法的数控机床复合误差补偿技术 [J]. 上海交通大学学报, 2014, 48(1): 12-15.

WANG Wei, YANG Jianguo. Compound error compensation technique for CNC machine tools based on interpolation method [J]. Journal of Shanghai Jiaotong University, 2014, 48(1): 12-15.

张成新, 高峰, 李艳, 等. 基于分段拟合的机床大尺寸工作台热误差补偿模型 [J]. 机械工程学报, 2015, 51(3): 146-152.

ZHANG Chengxin, GAO Feng, LI Yan, et al. Model of thermal error compensation of large size worktable for machine tools based on piecewise fitting [J]. Chinese Journal of Mechanical Engineering, 2015, 51(3): 146-152.

朱小龙, 杨建国, 代贵松. 基于AVQ聚类和OIF-Elman神经网络的机床热误差建模 [J]. 上海交通大学学报, 2014, 48(1): 16-21.

ZHU Xiaolong, YANG Jianguo, DAI Guisong. AVQ clustering algorithm and OIF-Elman neural network for machine tool thermal error [J]. Journal of Shanghai Jiaotong University, 2014, 48(1): 16-21.

RAMESH R, MANNAN M A, POO A N. Error compensation in machine tools—a review: part II Thermal errors [J]. International Journal of Machine Tools and Manufacture, 2000, 40(9): 1257-1284.

WU Hao, ZHANG Hongtao, GUO Qianjian, et al. Thermal error optimization modeling and real-time compensation on a CNC turning center [J]. Journal of Material Processing Technology, 2008, 207(1/2/3): 172-179.

WU Bing, HAN Shaojun, XIAO Jin. et al. Error compensation based on BP neural network for airborne laser ranging [J]. International Journal for Light and Electron Optics, 2016, 127(8): 4083-4088.

MIZE C D, ZIEGERT J C. Neural network thermal error compensation of a machining center [J]. Journal of the International Societies for Precision Engineering and Nanotechnology, 2000, 24(4): 338-346.

孙志超,陶涛,黄晓勇,等.车床主轴与进给轴耦合热误差建模及补偿研究.2015,49(7):105-112.[doi:10.7652/xjtuxb 201507018]

牟恩旭,马振群,冯斌,等.利用数控机床换向特性分析的摩擦误差补偿方法.2014,48(8):47-53.[doi:10.7652/xjtuxb 201408009]

冯斌,梅雪松,杨军,等.数控机床摩擦误差自适应补偿方法研究.2013,47(11):65-69.[doi:10.7652/xjtuxb201311012]

李学伟,赵万华,卢秉恒.轨迹误差建模的多轴联动机床轮廓误差补偿技术.2012,46(3):47-52.[doi:10.7652/xjtuxb 201203009]

陈光胜,梅雪松,陶涛.X-Y工作台摩擦误差补偿方法的研究.2011,45(1):69-73.[doi:10.7652/xjtuxb201101014]

周玉清,陶涛,梅雪松,等.旋转轴与平移轴联动误差的快速测量及溯源.2010,44(5):80-84.[doi:10.7652/xjtuxb201005 017]

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