Thermal Error Prediction of CNC Machine Tools Based on Regression Support Vector Machine with Variable Sensitivity Screening
With the rapid development of machinery manufacturing industry,the positioning accuracy of CNC machine tools are more and more demanding.In order to improve the positioning accuracy of CNC machine tools,a hybrid model based on variable sensitivity screening and regression support vector machine(SVR)was established to predict the thermal errors of CNC machine tools.This method is based on the sensitivity analysis of variables,and the interference independent variables with low sensitivity are screened out in time.Compared with basic SVR model for predicting the thermal errors of CNC machine tools,the result shows that the basic SVR is affected by the interference independent variables with low sensitivity,and the predicted results devi-ate greatly from the measured thermal error results.After the sensitivity screening of variables,the predicted values of the SVR model have higher accuracy,which verifies the feasibility of this model.
CNC Machine ToolsSupport Vector Machine for RegressionVariable Sensitivity ScreeningTher-mal Error
万方数据
维普
