基于OE-CM算法的机床主轴热误差建模与补偿分析

摘要/Abstract

摘要：

针对机床热误差建模过程中，误差信息不透明、数据特性不全面等不利因素，根据机床主轴热误差实验数据，分别采用GM(1,n) 模型和最小二乘支持向量机(LS-SVM)模型建立主轴热误差预测模型并进行线性叠加，然后采用预测有效度算法调整模型加权系数，建立了最优有效度复合预测模型（OE-CM）以获取最佳预测效果。在VXC-560型三轴数控机床上进行在线实验建模,实验结果表明：OE-CM具有预测精度高、鲁棒性好等特点,整体预测效果优于灰色GM(1,n)模型和LS-SVM模型，适合在复杂工况条件下对机床主轴热误差进行预测和补偿,为提高机床热误差补偿精度建立了理论模型。为了验证该预测模型的有效性,对所研究的机床主轴进行热误差在线补偿,机床主轴Z向最大误差从23.8μm减小到8μm,减幅达到66.4%,较好地提高了机床精度，具有一定的工程化推广前景。

关键词: 数控机床, 热误差建模, 预测有效度, 误差补偿

Abstract:

According to the disadvantages about the error information opaque and incomplete in the thermal error modeling,a new OE-CM prediction model was proposed herein based on combining the self characteristic of GM(1,n) and LS-SVM algorithm. A online modeling experiment was designed on the three-axis CNC machine tool,and the results show that OE-CM model has the characteristics of high precision forecasting and good robustness.This model is superior to GM(1,n)
model and SVM model,which are recommended to be applied to predict and compensate the spindle thermal errors under different working environments.Firstly,according to the experimental data of the spindle thermal errors,this model used GM(1,n) algorithm to establish the prediction model and linear superposition respectively.Then,the forecasting effectiveness measure was used to adjust the weighting coefficients,and finally the optimal prediction effect was obtained.In order to verify the validity of this model,thermal error online compensation experiments were made on the spindle,and the z-direction maximum error is reduced from 23.8μm to 8μm,which can improve the precision of the machine tool,and have preliminary engineering popularizing prospect.

Key words: CNC , machine , tool;thermal , error , modeling;forecasting effectiveness;error , compensation

中图分类号:

TH161

要小鹏, 殷国富, 李光明. 基于OE-CM算法的机床主轴热误差建模与补偿分析[J]. 中国机械工程, 2015, 26(20): 2757-2762.

Yao Xiaopeng, Yin Guofu, Li Guangming. Thermal Error Modeling and Compensation Analysis Based on OE-CM Algorithm for Machine Tool Spindles[J]. China Mechanical Engineering, 2015, 26(20): 2757-2762.

参考文献

[1]Ramesh R,Mannan M A,Poo A N.Error Compensation in Machine Tools-review Part Ⅱ:Thermal Error[J].International Journal of   Machine   Tools   and   Manufacture,2000,40(9):1257-1284.
[2]傅建中,陈子辰.奇异值分解识别精密机械热动态特性参数的研究[J].浙江大学学报(工学版),2004,38(4):474-477.
Fu Jianzhong,Chen Zichen.Research on Identification of Thermal Dynamics Characteristics Parameter of Precision Machine Based on Singular Value Decomposition[J].Journal of Zhejiang University(Engineering Science),2004,38(4):474-477.
[3]陈泽宇, 龚凌云.基于GA-SVR的数控机床热误差建模[J].组合机床与自动化加工技术,2012,38(2):9-15.
Chen Zeyu,Gong Lingyun.Thermal Error Modeling of Numerical Control Machine Tool Based on GA-SVR[J].Modular   Machine Tool & Automatic Manufacturing Technique,2012,38(2):9-15.
[4]Huang Yanqun,Zhang Jie,Li Xu,et al.Thermal Error Modeling by Integrating GA and BP Algorithms for the High-speed Spindle[J].International Journal Advance Manufacture Technology,2014,71(9/12):1669-1675.
[5]要小鹏,殷国富,方辉,等.五轴数控机床的空间误差建模与解耦补偿分析[J].高技术通讯,2011,21(10):1084-1089.
Yao Xaiopeng,Yin Guofu,Fang Hui,et al.Volumetric Error Modelling and Decoupled Error Compensation Analysis of Five-axis   CNC Machine   Tools[J].Chinese High Technology Letters,2011,21(10):1084-1089.
[6]Ramesh R,Mannan M A,Poo A N,et al.Thermal Error Measurement and Modeling in Machine Tools,Part Ⅱ.Hubrid Bayesian Network-support Vector Machine Model[J].The International Journal of Machine Tools & Manufacture, 2003, 43(7): 405-419.
[7]Zhang Yi,Yang Jianguo,Jiang Hui.Machine Tool Thermal Error Modeling   and Prediction by Grey Neural Network[J]. The International Journal of Advanced Manufacturing Technology,2012,59(9/12):1068-1072.
[8]林伟青,傅建中,陈子辰,等.数控机床热误差的动态自适应加权最小二乘支持向量机建模方法[J].机械工程学报,2009,45(3):178-182.
Li Weiqing,Fu Jianzhong,Chen Zichen,et al.Modeling of NC Machine Tool Thermal Errors Based on Adaptive Best-fitting WLS-SVM[J].Journal of Mechanical Engineering,2009,45(3):178-182.
[9]Chen G J,Li K K,Chung T S,et al.Application of an Innovative Combined Forecasting Method in Power System Load Forecasting[J].Electric Power Systems Research,2001,59(2):131-137.
[10]Mayr J,Jedrzejewski J,Uhlmann E,et al.Thermal Issues in Machine Tools[J].CIRP Annals-Manufacturing Technology, 2012, 61(2):771-791.
[11]Zhang Guoqing, Sue To, Xiao Gaobo.A Novel Spindle Inclination Error Identification and Compensation Method   in Ultra-precision Raster Milling[J].International Journal of Machine Tools and Manufacture,2014,78(3):8-17.
[12]Zhang Jianfu,Feng Pingfa,Chen Chuang,et al.A Method for Thermal Performance Modeling and Simulation of Machine Tools[J].The International Journal of Advanced Manufacturing Technology,2013,68(5/8):1517-1527.
[13]Hsieh Kuen-Hung,Chen Tsair-Rong,Chang Paul,et al.Thermal Growth Measurement and Compensation for Integrated Spindles[J].International Journal of Advanced Manufacturing Technology,2013,64(5/8):889-901.
[14]要小鹏,殷国富,方辉,等.五轴机床误差建模与补偿解析新算法研究[J].四川大学学报(工程科学版),2013,21(5):1084-1089.
Yao Xaiopeng,Yin Guofu,Fang Hui,et al.A New Systhesis Error Modeling and Compensating Algorithm of the Five-axis Machine Tools[J].Journal of Sichuan University(Engineeing Science Edition),2013,21(5):1084-1089.
[15]ISO230-3:Test Code for Machine Tools-Part 3:Determination of   Thermal Effects[S].ISO. Geneva,2007:10-35.