MIAO En-Ming CHENG Tian-ju GONG Ya-yun CHEN Hai-dong. Application of support vector regression machine to thermal error modelling of machine tools[J]. Editorial Office of Optics and Precision Engineering, 2013,21(4): 980-986
MIAO En-Ming CHENG Tian-ju GONG Ya-yun CHEN Hai-dong. Application of support vector regression machine to thermal error modelling of machine tools[J]. Editorial Office of Optics and Precision Engineering, 2013,21(4): 980-986 DOI: 10.3788/OPE.20132104.0980.
This paper explored and selected an optimal thermal error model of the Computer Numberical Control(CNC) machining center to compensate the main error source
the thermal error of spindle
in the machine processing and to improve the machining accuracy. In experiments
the leaderway-V450 machining center was taken as a compensation object
and the Support Vector Regression (SVR)model and Multiple Regression(MLR) model were analyzed and compared. Firstly
the MLR model and the SVR model were established according to the first batch of data of the CNC center gained in summer. Then
by substituting the second batch of data measured in summer into two kinds of models respectively
the compensation accuracy of each model was calculated. Furthermore,by substituting the third batch of data measured in autumn into two kinds of models respectively,the compensation accuracy of each model was calculated again. Finally
the robustness between both models was compared according to the precision variation regulation. The experiment shows that the compensation standard deviations of SVR model both in summer and autumn are less than 2 m
and that of MLR model in summer is less than 2 m
while less than 8 m in autumn. These data show that the SVR model not only has high accuracy
but also has higher robustness for the thermal error modeling of CNC center.
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references
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