Mechanism-driven Method for Time-varying Error Modeling and Compensation of CNC Machine Tool's Feed Axes

doi:10.3901/JME.2022.03.251

Abstract

Abstract: At present, the data-driven model used for real-time time-varying error compensation of CNC machine tool has some problems, such as poor robustness of the model, a large number of sensors required and limited practical application in engineering. For this reason, a time-varying error prediction model for feed axes of CNC machine tool was established based on mechanism-driven modeling method. The real-time temperature field of screw in any motion is predicted by this model. Only one temperature sensor is placed on the body near the screw to acquire the initial temperature of screw and the real-time environmental temperature in machining. The compensator communicates with CNC system based on TCP/IP protocol, which can read the coordinates of the machine tool from CNC system and write the value of compensation into CNC system in real time. The test and real-time compensation of time-varying was realized for feed axes of a vertical machining center (HAAS VF-2), which has been used for more than 10 years, based on "Brain Replacement Engineering" of National Science and Technology Major Projects. The results show that the time-varying error compensation model proposed in this paper still acquired good results when the screw was worn and aging with thermal error, and the accuracy and stability of the machine tool had been significantly improved.

Key words: mechanism-driven model, feed axis, time-varying error, compensation, brain replacement engineering

CLC Number:

TG659

LIU Kuo, SONG Lei, CHEN Hu, HAN Wei, CUI Yiming, WANG Yongqing. Mechanism-driven Method for Time-varying Error Modeling and Compensation of CNC Machine Tool's Feed Axes[J]. Journal of Mechanical Engineering, 2022, 58(3): 251-258.

References

[1] 杨建国,范开国,杜正春,等. 数控机床误差补偿技术[M]. 北京:机械工业出版社,2013. YANG Jianguo,FAN Kaiguo,DU Zhengchun,et al. The error compensation technology of CNC machine tool[M]. Beijing:China Machine Press,2013.
[2] ZHANG Jianfu,FENG Pingfa,WU Zuojun,et al. Thermal structure design and analysis of a machine tool headstock[J]. Mechanika,2013,19(4):478-485.
[3] TAMAI A,KURITA T,MATSUE T,et al. Machine tool slide protection-uses thermal insulation or shrouding to equalise thermal distortion through ambient or operating conditions:German,DE3527491-A[P]. 1986-02-13.
[4] 傅建中,陈子辰. 精密机械热误差校正机理及参数遗传优化[J]. 浙江大学学报,2003(6):91-95. FU Jianzhong,CHEN Zichen. Thermal error calibration principle of precision machine and parameter genetic optimization algorithms[J]. Journal of Zhejiang University,2003(6):91-95.
[5] XU Zhezhu,LIU X,KIM H,et al. Thermal error forecast and performance evaluation for an air-cooling ball screw system[J]. International Journal of Machine Tools & Manufacture,2011,51(7-8):605-611.
[6] 张琨,张毅,侯广锋,等. 基于热模态分析的热误差温度测点优化选择[J]. 机床与液压,2012,40(7):1-3. ZHANG Kun,ZHANG Yi,HOU Guangfeng,et al. Selection of sensor placement for thermal error compensation based on thermal mode analysis[J]. Machine Tool & Hydraulics,2012,40(7):1-3.
[7] LIU Jialian,MA Chi,WANG Shilong. Data-driven thermally-induced error compensation method of high-speed and precision five-axis machine tools[J]. Mechanical Systems and Signal Processing,2020,138:106538.
[8] ZHANG Jun,LI Bo,ZHOU Changxing,et al. Positioning error prediction and compensation of ball screw feed drive system with different mounting conditions[J]. Proceedings of the Institution of Mechanical Engineers Part B-Journal of Engineering Manufacture,2016,230(12):2307-2311.
[9] SHI Hu,MA Chi,YANG Jun,et al. Investigation into effect of thermal expansion on thermally induced error of ball screw feed drive system of precision machine tools[J]. International Journal of Machine Tools & Manufacture,2015,97:60-71.
[10] 要小鹏,殷国富,李光明. 数控机床进给轴综合误差解耦建模与补偿研究[J]. 机械工程学报,2016,52(1):184-192. YAO Xiaopeng,YIN Guofu,LI Guangming. Positioning error of feed axis decouple-separating modeling and compensating research for CNC machine tools[J]. Journal of Mechanical Engineering,2016,52(1):184-192.
[11] JIN Chao,WU Bo,HU Youmin. Wavelet neural network based on NARMA-L2 model for prediction of thermal characteristics in a feed system[J]. Chinese Journal of Mechanical Engineering,2011,24(1):33-41.
[12] YAO Xinhua,FU Jianzhong,XU Yuetong,et al. Synthetic error modeling for NC machine tools based on intelligent technology[C]//Procedia CIRP. Huddersfield,United kingdom:Elsevier B.V.,2013,10:91-97.
[13] 张毅,杨建国. 基于灰色理论预处理的神经网络机床热误差建模[J]. 机械工程学报,2011,47(7):134-139. ZHANG Yi,YANG Jianguo. Modeling for machine tool thermal error based on grey model preprocessing neural network[J]. Journal of Mechanical Engineering,2011,47(7):134-139.
[14] JIANG Hui,YANG Jianguo. Application of an optimized grey system model on 5-Axis CNC machine tool thermal error modeling[C]//2010 International Conference on E-Product E-Service and E-Entertainment,ICEEE2010:IEEE Computer Society,2010.
[15] 黄智,刘永超,邓涛,等. 一种五轴数控机床热误差建模方法[J]. 中国机械工程,2020,31(13):1529-1538. HUANG Zhi,LIU Yongchao,DENG Tao,et al. A method for thermal error modeling of FAMT[J]. Chinese Journal of Mechanical Engineering,2020,31(13):1529-1538.
[16] 王新孟,杨军,梅雪松,等. 精密坐标镗床进给系统热误差分析与预测[J].西安交通大学学报,2015,49(10):22-28. WANG Xinmeng,YANG Jun,MEI Xuesong,et al. Analysis and prediction for thermal error of precision coordinate boring machine[J]. Journal of Xi'an Jiaotong University,2015,49(10):22-28.
[17] 陈诚,裘祖荣,李醒飞,等. 伺服系统中滚珠丝杠的温度场模型[J]. 光学精密工程,2011,19(5):1151-1158. CHEN Cheng,QIU Zurong,LI Xingfei,et al. Temperature field model of ball screws used in servo systems[J]. Optics and Precision Engineering,2011,19(5):1151-1158.
[18] LIU Kuo,LIU Yu,SU Mingjia,et al. Comprehensive thermal compensation of the servo axes of CNC machine tools[J]. The Intemational Journal of Advanced Manufacturing Technology,2016,85:2715-2728.