基于逐步线性回归的温度测点优化

Optimization of the Temperature Measuring Points Based on Linear Stepwise Regression

在数控机床热误差补偿技术中,温度测点的选择与优化是一个难点。文章采用逐步线性回归方法对核电轮槽铣床主轴箱的温度测点进行优化与建模。首先利用瞬态热-结构耦合分析了主轴箱在粗加工时的温升和热变形,再通过逐步线性回归方法对温度测点进行优化,利用优化后的温度测点建立了主轴X,Y,Z三个方向的热误差模型,最后对主轴箱在精加工运行时对所建立的模型进行了验证,结果表明:该方法不仅可以有效减小温度测点数目,还能保证模型的预测精度,三个方向的热误差均减小到5μm以下。

The optimization and selection of temperature measuring points is a difficulty in the error compensation technology for NC machine tool. In this paper,using stepwise linear regression method,the temperature measuring point＇s optimization and thermal error model were obtained for nuclear power wheel groove milling machine spindle box. Firstly,the temperature rise and thermal deformation of the spindle box was obtained through transient thermal-structure coupling analysis during rough machining,then temperature measuring points were optimized by stepwise linear regression method,and the X,Y,Z directions of thermal error model was established based on the optimized temperature measuring points. Finally,the thermal error model was verified in the fine processing operation,the results shown that： this method can not only effectively reduce the number of temperature measuring points,also can ensure the accuracy of the model prediction,three directions of thermal error are reduced to below 5μm.