Robust modeling method for thermal error of CNC machine tools based on ridge regression algorithm
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- 作者：Hui Liu ; En Ming Miao ; miaoem@163.com ; Xin Yuan Wei ; Xin Dong Zhuang
- 关键词：CNC machine tools ; Thermal error ; Collinearity ; Predicted accuracy and robustness ; Ridge regression
- 刊名：International Journal of Machine Tools and Manufacture
- 出版年：2017
- 出版时间：February 2017
- 年：2017
- 卷：113
- 期：Complete
- 页码：35-48
- 全文大小：1743 K
- 卷排序：113
文摘
The long-term prediction performance of commonly used traditional machine tool thermal error modeling methods is deeply studied. Although the traditional methods can significantly reduce the collinearity between temperature sensitive points (Input variables of thermal error model), the correlation between some points and thermal error is weak. The temperature sensitive points which have strong correlation with thermal error also have high collinearity between them. The ridge regression algorithm is used to inhibit the bad influence of collinearity on the thermal error predicted robustness. The thermal error predicted effect of proposed method is verified by 18 thermal error experiments done in different seasons.