Research on electric spindle thermal error prediction model based on DBO-SVM

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Liu K, Sun MJ, Zhu TJ, Wu YL, Liu Y (2016) Modeling and compensation for spindle’s radial thermal drift error on a vertical machining center. Int J Mach Tools Manuf 105:58–67

Deng XL, Lin H, Wang JC, Xie CX, Fu JZ (2018) Review on thermal design of machine tool spindles. Opt Precis Eng 26(6):1415–1429

Yan ZZ, Tao T, Hou RS, Du HY, Mei XS (2019) Convolution modeling for thermal properties of motorized spindle in machine tools. J Xi’an Jiaotong Univ 53(6):1–8

Li TM, Li FC, Jiang Y, Wang HT (2017) Thermal error modeling and compensation of a heavy gantry-type machine tool and its verification in machining. Int J Adv Manuf Technol 92(9):3073–3092

Zhou ZD, Hu JM, Liu Q, Lou P, Yan JM, Hu JW, Gui L (2019) The selection of key temperature measurement points for thermal error modeling of heavy-duty computer numerical control machine tools with density peaks clustering. Adv Mech Eng 11(4)

Abdulshahed AM, Longstaff AP, Fletcher S (2015) The application of ANFIS prediction models for thermal error compensation on CNC machine tools. Appl Soft Comput 27:158–168

Li GL, Tang XD, Li ZY, Xu K, Li CZ (2022) The temperature-sensitive point screening for spindle thermal error modeling based on IBGOA-feature selection. Precis Eng -J Int Soc Precis Eng Nanotechnol 73:140–152

Xu K, Wang WH, Li JY, Li GL, Miao EM (2018) Temperature sensitive point selection method for machine tools based on active construction of temperature difference variables. Chinese J Sci Instrum 44(02):67–74

Cao WJ, Li HL, Li QA (2021) A method of thermal error prediction modeling for CNC machine tool spindle system based on linear correlation. Int J Adv Manuf Technol 118(9–10):3079–3090

Miao EM, Liu Y, Liu H, Gao ZH, Li W (2015) Study on the effects of changes in temperature-sensitive points on thermal error compensation model for CNC machine tool. Int J Mach Tools Manuf 97:50–59

Yang ZQ, Lv SY, Bo JD, Chen YS, Liu LB (2020) GRA-PCA-based optimization of heat-sensitive points in machine tool spindle systems. Mach Tools Hydraulics 48(23):93–98

Tsai PC, Cheng CC, Chen WJ, Su SJ (2020) Sensor placement methodology for spindle thermal compensation of machine tools. Int J Adv Manuf Technol 106(11):5429–5440

Liu H, Miao EM, Wei XY, Zhuang XD (2021) Robust modeling method for thermal error of CNC machine tools based on ridge regression algorithm. Int J Mach Tools Manuf 113:35–48

Liu JL, Ma C, Wang SL, Wang SB, Yang B, Shi H (2019) Thermal-structure interaction characteristics of a high-speed spindle- bearing system. Int J Mach Tools Manuf 137:42–57

Hou RS, Du HY, Yan ZZ, Yu WB, Tao T, Mei XS (2019) The modeling method on thermal expansion of CNC lathe headstock in vertical direction based on MOGA. Int J Adv Manuf Technol 103(9):3629–3641

Lu C, Fei JY, Meng XZ, Li YS, Liu ZB (2022) Thermal error prediction and compensation of digital twin laser cutting based on T-XGBoost. Sensors 22(18):7022

Yuan Q, Ma C, Liu JL, Gui HQ, Li MY, Wang SL (2022) Correlation analysis-based thermal error control with ITSA-GRU-A model and cloud-edge-physical collaboration framework. Adv Eng Inform 54:101759

Li Y, Zhao WH, Wu WW, Lu BH, Chen YB (2014) Thermal error modeling of the spindle based on multiple variables for the precision machine tool. Int J Adv Manuf Technol 72(9):1415–1427

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Abdulshahed AM, Longstaff AP, Fletcher S, Potdar A (2016) Thermal error modelling of a gantry-type 5-axis machine tool using a grey neural network model. J Manuf Syst 41:130–142

Wu CY, Xiang ST, Xiang WS (2021) Spindle thermal error prediction approach based on thermal infrared images: a deep learning method. J Manuf Syst 59:67–80

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