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Thermal error model for precision machine tools based on digital twin control
Published:2023-05-25 author:SONG Fei-hu, WANG Meng-ke, YIN Jing, et al. Browse: 1318 Check PDF documents
Thermal error model for precision machine tools based 
on digital twin control


SONG Fei-hu, WANG Meng-ke, YIN Jing, LV Chang-fei

(School of Mechanical and Electrical Engineering, Guizhou Normal University, Guiyang 550025, China)


Abstract: The results of studies have shown that the thermal error of the machine tool accounts for about 40% to 70% of its total machining error, and the more precise the machine tool is, the greater the proportion of its thermal error is. Therefore, it is necessary to improve the machining accuracy of the machine by controlling the thermal error.Aiming at the problem that the prediction accuracy and generalization ability of machine tool thermal error model were not strong, a thermal error modeling method which introduced spindle speed and could be embedded in the digital twin control system was presented. Firstly, the fuzzy cluster analysis(FCA), grey correlation analysis(GCA)and principal component regression(PCR) method were theoretically analyzed. Then, a vertical machining center was used as the object, and the temperature data and thermal error data under the rotational speed chart were obtained through the thermal characteristic experiment, fuzzy cluster analysis combined with grey correlation analysis were used to select temperature sensitive points. Finally, the spindle speed and the temperature appreciation of the temperature sensitive points were used as input variables. The thermal error model was established by PCR method, and the effect was compared with multiple linear regression (MLR) model. The results show that the prediction accuracy of the established PCR model is 9.5% higher than that of the MLR model, which proves that the model has higher prediction accuracy and stronger generalization ability. It can be embedded into the digital twin control system to predict thermal error in real time and realize thermal error control.

Key words: processing error of CNC machine tool; control of thermal error; principal component regression(PCR)analysis; multiple linear regression (MLR) model; spindle rotation speed;temperature sensitive points; thermal characteristic experiment
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