[1]KIM B S, SONG Y C, PARK C H. Robust Thermal Error Modeling and Compensation for a Nano Level Thermal Drift in a High Precision Lathe[J]. International Journal of Precision Engineering and Manufacturing, 2011, 12(4): 657-661.
[2]WANG H T, WANG L P, LI T M. Thermal Sensor Selection for the Thermal Error Modeling of Machine Tool Based on the Fuzzy Clustering Method[J]. International Journal of Manufacturing Technology, 2013, 69: 121-126.
[3]HAN J, WANG L P, WANG H T, et al. A New Thermal Error Modeling Method for CNC Machine Tools[J]. International Journal of Manufacturing Technology, 2012, 62: 205-212.
[4]ZHANG T, YE W H, LIANG R J. Temperature Variable Optimization for Precision Machine Tool Thermal Error Compensation on Optimal Threshold[J]. Chinese Journal of Mechanical Engineering, 2013, 26(1): 158-165.
[5]MIAO E M, GONG Y Y, NIU P C, et al. Robustness of Thermal Error Compensation Modeling Models of CNC Machine Tools[J]. International Journal of Manufacturing Technology, 2013, 69: 2593-2603.
[6]ABDULSHAHED A M, LONGSTAFF A P, FLETCHER S, et al. Thermal Error Modeling of Machine Tools Based on ANFIS with Fuzzy C-means Clustering Using a Thermal Imaging Camera[J]. International Journal of Manufacturing Technology, 2015, 39(7): 1837-1852.
[7]YANG L, ZHAO W H, WU W W, et al. Thermal Error Modeling of the Spindle Based on Multiple Variables for the Precision Machine Tool[J]. International Journal of Manufacturing Technology, 2014, 72: 1415-1427.
[8]XIANG S T, LU H X, YANG J. Thermal Error Prediction Method for Spindles in Machine Tools Based on a Hybrid Model[J]. Journal of Engineering Manufacture, 2015, 229(1): 130-140.
[9]LO Chihhao, YUAN Jingxia, NI Jun. Optimal Temperature Variable Selection by Grouping Approach for Thermal Error Modeling and Compesation[J]. International Journal of Machine Tools & Manufacture, 1999, 39(9): 1383-1396.
[10]ABDULSHAHED A M, LONGSTAFF A P, FLETCHER S, et al. The Application of ANFIS Prediction Models for Thermal Error Compensation on CNC Machine Tools[J]. Applied Soft Computing, 2015, 27: 158-168.
[11]苗恩铭,龚亚运,成天驹,等. 支持向量回归机在数控加工中心热误差建模中的应用[J]. 光学精密工程,2013, 21(4): 980-986.
MIAO Enming, GONG Yayun, CHENG Tianju, et al. Application of Support Vector Regression Machine to Thermal Error Modelling of Machine Tools[J]. Opt. Precision Eng., 2013, 21(4): 980-986.
[12]MIAO E M, GONG Y Y, DANG L C, et al. Temperature-sensitive Point Selection of Thermal Errors of Model of CNC Machine Center[J]. International Journal of Advanced Manufacturing Technology, 2014, 74:681-691.
[13]苗恩铭,吕玄玄,苗继超,等. 数控机床热误差补偿最佳转速选择[J]. 光学精密工程,2015, 23(11): 3176-3182.
MIAO Enming, LYU Xuanxuan, MIAO Jichao, et al. Selection of Optimum Spindle Speed to Thermal Error Compensation of Machine Tools[J]. Opt. Precision Eng., 2015, 23(11): 3176-3182.
[14]MIAO E M, LIU H, FAN K C, et al. Analysis of CNC Machining Based on Characteristics of Thermal Errors and Optimal Design of Experimental Programs [J]. International Journal of Advanced Manufacturing Technology, 2017, 88(5): 1363-1371.
[15]张伟,叶文华. 基于灰色关联和模糊聚类的机床温度测点优化[J]. 中国机械工程,2014, 25(4): 456-460.
ZHANG Wei, YE Wenhua. Optimization of Temperature Measuring Points for Machine Tools Based on Grey Correlation and Fuzzy Clustering Analysis[J]. China Mechanical Engineering, 2014, 25(4): 456-460.
[16]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 Yan, LI Yinghao, GAO Feng, et al. Investigation on Optimization of Temperature Measurement Key Points Based on Mutual Information and Improved Fuzzy Clustering Analysis[J]. Chinese Journal of Scientific Instrument, 2015, 36(11): 2466-2472.
[17]International Standards Organization. ISO 230-3:2007. Test Code for Machine Tools—Part 3: Determination of Thermal Effects[S]. Geneva: ISO, 2007.
[18]费业泰. 误差理论与数据处理[M]. 6版. 北京:机械工业出版社,2010.
FEI Yetai. Error Theory and Data Handle [M]. 6th ed. Beijing: China Machine Press, 2010.
[19]L K 蒂莫西, B E 博纳. 状态空间分析导论(下册)[M]. 胡钦训,刘颖,译. 北京:高等教育出版社,1986.
TIMOTHY L K, BONA B E. State Space Analysis: an Introduction(Volume Ⅱ)[M]. HU Qinxun, LIU Ying, Trans. Beijing: Higher Education Press, 1986.
[20]HU H, DING F. An iterative Least Squares Estimation Algorithm for Controlled Moving Average Systems Based on Matrix Decomposition [J]. Applied Mathematics Letters, 2012, 25: 2332-2338. |