数控机床热误差建模及预测方法分析

热误差作为制约数控机床加工精度的关键因素,在重型数控机床上表现得尤为明显。以重型落地镗铣床为例,根据热误差测量试验数据,分析重型数控机床温度场特性,并基于兼顾相关系数和欧式距离的系统聚类准则,对温度测点系统进行优化,以减小温度测点间共线性。通过优化温度测点,采用多元线性回归分析,建立重型数控机床热误差预测模型。由现场试验可知,建立的热误差预测模型可将均方根误差控制在10μm以内,有效地提高了热误差预测精度。

Thermal Error Modeling and Prediction Method Analysis of CNC Machine Tools

As a key factor restricting the machining accuracy of computer numerical control (CNC) machine tools, thermal error is especially obvious in heavy CNC machine tools. Taking heavy duty floor boring and milling machine as an example, the temperature field characteristics of heavy-duty CNC machine tools are analyzed according to the thermal error measurement data.The temperature measurement point system was optimized based on the system clustering criterion considering both the correlation coefficient and Euclidean distance to reduce the collinearity between temperature measurement points. According to the optimized temperature measurement point, the thermal error prediction model of heavy CNC machine tool was established by multiple linear regression analysis. The field test shows that the thermal error prediction model can control the root mean square error within 10 micron and improve the thermal error prediction accuracy effectively.