龙门机床进给系统热误差模型关键点优化
|
摘要
为了解决温度测点数量和测点间复共线性对龙门机床热误差模型精度和鲁棒性的影响,提出了一种测点综合优化方法。首先,采用模糊聚类法和相关性分析筛选出对热误差影响较大的关键点,达到优化测点数量的目的;然后采用特征提取法得到预测模型的自变量,特征提取消除了复共线性对预测模型精度和鲁棒性的影响。在一台龙门精密镗铣加工中心上实验验证,结果表明:所提出的测点综合优化法优于自适应模糊聚类热关键点优化,采用该方法进行误差预测模型关键点优化可有效提高模型精度和鲁棒性。
In order to deal with the effect of the number of temperature test points and multi-collinearity among the test points on the thermal error model accuracy and robustness of gantry machine tool,a test point synthesis optimization method is proposed. First of all,the fuzzy clustering and correlation analysis methods are adopted to screen out the critical points that have great effect on the thermal error and the purpose of optimizing the number of the test points is achieved. Then,the feature extraction method is used to obtain the independent variables of the prediction model,which eliminates the effect of multi-collinearity on the model accuracy and robustness. An experiment was conducted on a gantry type precision boring milling machining center,and experiment result indicates that the proposed test point synthesis optimization method is superior to the thermal critical point optimization method based on adaptive fuzzy clustering.Adopting this model to carry out the critical point optimization of the error prediction model can effectively improve the robustness and accuracy of the model.
In order to deal with the effect of the number of temperature test points and multi-collinearity among the test points on the thermal error model accuracy and robustness of gantry machine tool,a test point synthesis optimization method is proposed. First of all,the fuzzy clustering and correlation analysis methods are adopted to screen out the critical points that have great effect on the thermal error and the purpose of optimizing the number of the test points is achieved. Then,the feature extraction method is used to obtain the independent variables of the prediction model,which eliminates the effect of multi-collinearity on the model accuracy and robustness. An experiment was conducted on a gantry type precision boring milling machining center,and experiment result indicates that the proposed test point synthesis optimization method is superior to the thermal critical point optimization method based on adaptive fuzzy clustering.Adopting this model to carry out the critical point optimization of the error prediction model can effectively improve the robustness and accuracy of the model.
引文
[1]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.
[2]刘宝俊.龙门加工中心进给系统温度场与热变形研究[D].南京:南京航空航天大学,2013.LIU B J.Temperature field and thermal deformation of feed system on gantry machining center[D].Nanjing:Nanjing University of Aeronautics and Astronautics,2013.
[3]高峰,刘江,李艳,等.基于Kohonen自组织竞争网络的机床温度测点辨识研究[J].中国机械工程,2014,25(7):862-866.GAO F,LIU J,LI Y,et al.Identification of temperature measuring points for machine tools with kohonen selforganizing competitive network[J].China Mechanical Engineering,2014,25(7):862-866.
[4]高峰,刘江,杨新刚,等.基于Fisher最优分割法的机床热关键点优化研究[J].仪器仪表学报,2013,34(5):1070-1075.GAO F,LIU J,YANG X G,et al.Study on optimization of thermal key points for machine tools based on Fisher optimal segmentation method[J].Chinese Journal of Scientific Instrument,2013,34(5):1070-1075.
[5]周杰,李小汝,罗范杰.基于FCM自适应模糊聚类的温度测点优化[J].制造技术与机床,2015(2):39-42.ZHOU J,LI X R,LUO F J.Optimization of the temperature measuring points based on self-adaptive FCM fuzzy clustering[J].Manufacturing Technology and Machine Tools,2015(2):39-42.
[6]ABDLSHAHED A M,LONGSTAFF A P,FLETCHER S.The application of ANFIS prediction models for thermal error compensation on CNC machine tools[J].Applied Soft Computing,2015,27:158-168.
[7]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[J].西安交通大学学报,2015,49(7):105-112.SUN ZH CH,TAO T,HUANG X Y,et al.The study for modeling and compensation of coupled thermal error between spindle and feed shaft[J].Journal of Xi'an Jiaotong University,2015,49(7),105-112.
[8]赵瑞月,梁睿君,叶文华.基于模糊聚类与偏相关分析的机床温度测点优化[J].机械科学与技术,2012,31(11):1767-1771.ZHAO R Y,LIANG R J,YE W H.Optimization of temperature measuring points for machine tool based on fuzzy clustering and partial correlation analysis[J].Mechanical Science and Technology for Aerospace Engineering,2012,31(11):1767-1771.
[9]李艳,李英浩,高峰,等.基于互信息法和改进模糊聚类的温度测点优化[J].仪器仪表学报,2015,36(11):2466-2472.LI Y,LI Y H,GAO F,et al.Study on optimization of temperature measurement points based on mutual information and improved fuzzy clustering analysis[J].Chinese Journal of Scientific Instrument,2015,36(11):2466-2472.
[10]ZHANG C,GAO F,MENG Z,et al.A novel linear virtual temperature constructing method for thermal error modeling of machine tools[J].The International Journal of Advanced Manufacturing Technology,2015,80(9-12):1965-1973.
[11]范金梅,徐黎明,赵晓明,等.机床热误差补偿中温度传感器布置策略的研究[J].仪器仪表学报,2005,26(8):963-964.FAN J M,XU L M,ZHAO X M,et al.Sensor placement strategy for thermal error compensation on machine tools[J].Chinese Journal of Scientific Instrument,2005,26(8):963-964.
[12]仇健,刘春时,刘启伟,等.龙门数控机床主轴热误差及其改善措施[J].机械工程学报,2012,48(21):149-157.QIU J,LIU CH SH,LIU Q W,et al.Thermal errors of planer type nc machine tools and its improvement measures[J].Journal of Mechanical Engineering,2012,48(21):149-157.
[13]HUANG J,ZHOU Z,LIU M,et al.Real-time measurement of temperature field in heavy-duty machine tools using fiber Bragg grating sensors and analysis of thermal shift errors[J].Mechatronics,2015,31:16-21.
[14]BEZDEK J C,EHRLICH R,FULL W.FCM:The fuzzy c-means clustering algorithm[J].Computers&Geosciences,1984,10(2):191-203.
[15]宫改云,高新波,伍忠东.FCM聚类算法中模糊加权指数m的优选方法[J].模糊系统与数学,2005,19(1):143-148.GONG G Y,GAO X B,WU ZH D.An optimal choice method of parameter m in FCM clustering algorithm[J].Fuzzy Systems and Mathematics,2005,19(1):143-148.
[16]BEZDEK J C.Numerical taxonomy with fuzzy sets[J].Journal of Mathematical Biology,1974,1(1):57-71.
[17]BEZDEK J C.Cluster validity with fuzzy sets[J].Journal of Cybernetics,1973,3(3):58-73.
[18]王维,杨建国,姚晓栋,等.数控机床几何误差与热误差综合建模及其实时补偿[J].机械工程学报.2012,48(7):165-170.WANG W,YANG J G,YAO X D,et al.Synthesis modeling and real-time compensation of geometric error and thermal error for CNC machine tools[J].Journal of Mechanical Engineering.2012,48(7):165-170.
[2]刘宝俊.龙门加工中心进给系统温度场与热变形研究[D].南京:南京航空航天大学,2013.LIU B J.Temperature field and thermal deformation of feed system on gantry machining center[D].Nanjing:Nanjing University of Aeronautics and Astronautics,2013.
[3]高峰,刘江,李艳,等.基于Kohonen自组织竞争网络的机床温度测点辨识研究[J].中国机械工程,2014,25(7):862-866.GAO F,LIU J,LI Y,et al.Identification of temperature measuring points for machine tools with kohonen selforganizing competitive network[J].China Mechanical Engineering,2014,25(7):862-866.
[4]高峰,刘江,杨新刚,等.基于Fisher最优分割法的机床热关键点优化研究[J].仪器仪表学报,2013,34(5):1070-1075.GAO F,LIU J,YANG X G,et al.Study on optimization of thermal key points for machine tools based on Fisher optimal segmentation method[J].Chinese Journal of Scientific Instrument,2013,34(5):1070-1075.
[5]周杰,李小汝,罗范杰.基于FCM自适应模糊聚类的温度测点优化[J].制造技术与机床,2015(2):39-42.ZHOU J,LI X R,LUO F J.Optimization of the temperature measuring points based on self-adaptive FCM fuzzy clustering[J].Manufacturing Technology and Machine Tools,2015(2):39-42.
[6]ABDLSHAHED A M,LONGSTAFF A P,FLETCHER S.The application of ANFIS prediction models for thermal error compensation on CNC machine tools[J].Applied Soft Computing,2015,27:158-168.
[7]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[J].西安交通大学学报,2015,49(7):105-112.SUN ZH CH,TAO T,HUANG X Y,et al.The study for modeling and compensation of coupled thermal error between spindle and feed shaft[J].Journal of Xi'an Jiaotong University,2015,49(7),105-112.
[8]赵瑞月,梁睿君,叶文华.基于模糊聚类与偏相关分析的机床温度测点优化[J].机械科学与技术,2012,31(11):1767-1771.ZHAO R Y,LIANG R J,YE W H.Optimization of temperature measuring points for machine tool based on fuzzy clustering and partial correlation analysis[J].Mechanical Science and Technology for Aerospace Engineering,2012,31(11):1767-1771.
[9]李艳,李英浩,高峰,等.基于互信息法和改进模糊聚类的温度测点优化[J].仪器仪表学报,2015,36(11):2466-2472.LI Y,LI Y H,GAO F,et al.Study on optimization of temperature measurement points based on mutual information and improved fuzzy clustering analysis[J].Chinese Journal of Scientific Instrument,2015,36(11):2466-2472.
[10]ZHANG C,GAO F,MENG Z,et al.A novel linear virtual temperature constructing method for thermal error modeling of machine tools[J].The International Journal of Advanced Manufacturing Technology,2015,80(9-12):1965-1973.
[11]范金梅,徐黎明,赵晓明,等.机床热误差补偿中温度传感器布置策略的研究[J].仪器仪表学报,2005,26(8):963-964.FAN J M,XU L M,ZHAO X M,et al.Sensor placement strategy for thermal error compensation on machine tools[J].Chinese Journal of Scientific Instrument,2005,26(8):963-964.
[12]仇健,刘春时,刘启伟,等.龙门数控机床主轴热误差及其改善措施[J].机械工程学报,2012,48(21):149-157.QIU J,LIU CH SH,LIU Q W,et al.Thermal errors of planer type nc machine tools and its improvement measures[J].Journal of Mechanical Engineering,2012,48(21):149-157.
[13]HUANG J,ZHOU Z,LIU M,et al.Real-time measurement of temperature field in heavy-duty machine tools using fiber Bragg grating sensors and analysis of thermal shift errors[J].Mechatronics,2015,31:16-21.
[14]BEZDEK J C,EHRLICH R,FULL W.FCM:The fuzzy c-means clustering algorithm[J].Computers&Geosciences,1984,10(2):191-203.
[15]宫改云,高新波,伍忠东.FCM聚类算法中模糊加权指数m的优选方法[J].模糊系统与数学,2005,19(1):143-148.GONG G Y,GAO X B,WU ZH D.An optimal choice method of parameter m in FCM clustering algorithm[J].Fuzzy Systems and Mathematics,2005,19(1):143-148.
[16]BEZDEK J C.Numerical taxonomy with fuzzy sets[J].Journal of Mathematical Biology,1974,1(1):57-71.
[17]BEZDEK J C.Cluster validity with fuzzy sets[J].Journal of Cybernetics,1973,3(3):58-73.
[18]王维,杨建国,姚晓栋,等.数控机床几何误差与热误差综合建模及其实时补偿[J].机械工程学报.2012,48(7):165-170.WANG W,YANG J G,YAO X D,et al.Synthesis modeling and real-time compensation of geometric error and thermal error for CNC machine tools[J].Journal of Mechanical Engineering.2012,48(7):165-170.