应用变量优选的PLSR分析直线进给轴热扭曲行为
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摘要
为了探索直线电机驱动的高速直线进给轴热扭曲变形的影响因素,在试验的基础上,给出应用向前变量智能自筛选的偏最小二乘线性回归模型(Partial least squares regression,PLSR)分析影响进给轴热扭曲行为关联因素的分析方法。通过在自构建的进给轴试验平台,建立进给轴扭曲变形的测试系统,给出直线进给轴在发热过程和强冷却作用过程的热扭曲变形采样与进给轴温度动态采集方案。应用周期大变异的遗传算法为偏最小二乘回归参数的自检验方法,给出分析方法的具体实现步骤。通过实验和回归识别计算,分析了进给轴的温度分布及其对热扭曲行为的影响规律。结果表明,给出的变量自筛选偏最小二乘线性回归分析方法,可有效的筛选复相关的温度测点变量,并保持较高的回归识别精度,给出的方法与全变量PLSR和向后变量筛选的Bootstrap方法进行了比较,进一步表明了给出的回归分析方法的优越性。
In order to explore the thermal effects of thermal distortion of high speed linear feed axis driven by linear motor,on the basis of experiment,an analytical method by a partial least squares linear regression model( PLSR)with forward variable intelligent self selection was proposed and the impact of the effect factors of thermal distortion behavior on linear feed drive axis was analyzed. According to the established feed axis distortion measurement system on the feed axis test platform,it gives the acquisition scheme of the heat distortion of the linear axis and dynamic temperature in heating process and cooling process. Using the cycle mutation genetic algorithm,the paper provides a self inspection method for acquiring the partial least squares regression parameter and gives the specific steps of the analysis method. With the experiments and regression recognition calculation,the feed axis temperature distribution and the rule of the thermal distortion behavior were analyzed. The results show that,the analysis method with variable self screening partial least squares linear,which can effectively filter the multiple correlation of the variables of temperature measurement points and maintains high regression identification accuracy. Compared with all variable PLSR and backward variables screening Bootstrap method,the regression analysis method can further demonstrates the superiority.
In order to explore the thermal effects of thermal distortion of high speed linear feed axis driven by linear motor,on the basis of experiment,an analytical method by a partial least squares linear regression model( PLSR)with forward variable intelligent self selection was proposed and the impact of the effect factors of thermal distortion behavior on linear feed drive axis was analyzed. According to the established feed axis distortion measurement system on the feed axis test platform,it gives the acquisition scheme of the heat distortion of the linear axis and dynamic temperature in heating process and cooling process. Using the cycle mutation genetic algorithm,the paper provides a self inspection method for acquiring the partial least squares regression parameter and gives the specific steps of the analysis method. With the experiments and regression recognition calculation,the feed axis temperature distribution and the rule of the thermal distortion behavior were analyzed. The results show that,the analysis method with variable self screening partial least squares linear,which can effectively filter the multiple correlation of the variables of temperature measurement points and maintains high regression identification accuracy. Compared with all variable PLSR and backward variables screening Bootstrap method,the regression analysis method can further demonstrates the superiority.
引文
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[3]Jang C,Kim J,Kim Y.Thermal resistance modeling of linear motor driven stages for chip mounter applications[C]//Proceedings of the ITherm 2002.Eighth Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems.San Diego,CA,USA:IEEE,2002:77-84
[4]Kim J J,Jeong Y H,Cho D W.Thermal behavior of a machine tool equipped with linear motors[J].International Journal of Machine Tools and Manufacture,2004,44(7-8):749-758
[5]Eun I U.Comparison between asynchronous and synchronous linear motors as to thermal behavior[J].International Journal of Precision Engineering and Manufacturing,2001,2(3):61-68
[6]Chow J H,Zhong Z W,Lin W,et al.Investigation of thermal effect in permanent magnet linear motor stage[C]//Proceedings of 2010 International Conference on Control Automation Robotics&Vision.Singapore,Singapore:IEEE,2010:258-262
[7]林献坤,李燕军,吴倩倩.高速直线电动机驱动进给轴热行为测试研究[J].制造技术与机床,2012,(11):25-29Lin X K,Li Y J,Wu Q Q.Test of thermal behavior of high speed feed drive system equipped with linear motor[J].Manufacturing Technology&Machine Tool,2012,(11):25-29(in Chinese)
[8]顾平灿,徐月同.扁平型永磁直线同步电机热学模型及实验研究[J].组合机床与自动化加工技术,2015,(11):37-40Gu P C,Xu Y T.Thermal model and experiment study on a flat permanent-magnet linear synchronous motor[J].Modular Machine Tool&&utomatic Manufacturing Technique,2015,(11):37-40(in Chinese)
[9]Xu Z Z,Liu X J,Kim H K,et al.Thermal error forecast and performance evaluation for an air-cooling ball screw system[J].International Journal of Machine Tools and Manufacture,2011,51(7-8):605-611
[10]Alejandre I,Artes M.Thermal non-linear behaviour in optical linear encoders[J].International Journal of Machine Tools and Manufacture,2006,46(12-13):1319-1325
[11]Boulesteix A L,Strimmer K.Partial least squares:a versatile tool for the analysis of high-dimensional genomic data[J].Briefings in Bioinformatics,2007,8(1):32-44
[12]常英杰,陆宪忠,王世龙,等.基于偏最小二乘回归的发动机排气分析仪线性化研究[J].机械工程学报,2011,47(10):76-81Chang Y J,Lu X Z,Wang S L,et al.Study on the linearization of analyzer for engine exhaust based on partial least squares[J].Journal of Mechanical Engineering,2011,47(10):76-81(in Chinese)
[13]王惠文,吴载斌,孟洁.偏最小二乘回归的线性与非线性方法[M].北京:国防工业出版社,2006Wang H W,Wu Z B,Meng J.Partial least-squares regression:linear and nonlinear methods[M].Beijing:National Defense Industry Press,2006(in Chinese)
[14]玄光男,程润伟.遗传算法与工程优化[M].于歆杰,周根贵,译.北京:清华大学出版社,2004Xuan G N,Cheng R W.Genetic algorithms and engineering optimization[M].Yu X J,Zhou G G,trans.Beijing:Tsinghua University Press,2004(in Chinese)
[15]Sarabiaa L A,Ortizb M C,Sanchez M S,et al.Partial least squares fine-tuning by a bootstrap estimated signalnoise relation to weight the loadings[J].Chemometrics and Intelligent Laboratory Systems,2003,68(1-2):83-96