为降低机床加工过程中温度场变化对机床加工精度的影响，分析了数控机床生产过程中热源组成及热误差产生机理，根据灰色关联度理论从原设定的8个温度测量点中计算选定4个机床温度关键测量点，建立了灰色GM（1，4）预测模型。该模型搭建了4个关键测温点的温度变化情况与机床热误差值之间的映射关系，能在生产过程通过获取关键点温度实时预测机床热误差值，再通过数控系统将预测值补偿到刀具进给位置，以此形成机床热误差补偿机制。最后，以精密卧式加工中心THM6380为实验对象，检验GM（1，4）模型预测结果与实际热误差值间的差距，拟合残差在±1 μm以内，拟合效果良好。

To reduce the influence of temperature field on the machining accuracy of machine tools, we analyze the heat source composition and the thermal error mechanism in the production process of CNC machine tools, select 4 key points for temperature-measuring from the original 8 temperature-measuring points according to the theory of grey relational degree, and establish a grey (4,1) prediction model. The model builds the mapping relationship between the changes of the 4 key points and the thermal error of machine tools. It can predict the thermal error of machine tools in real time by acquiring the temperature of the key points and then compensate the predicted thermal error to the tool feed position, and thus a machine thermal error compensation mechanism is formed. The precision horizontal machining center experiment THM6380 is taken as the experimental object, the gap between the test results of GM(4,1) model and the actual thermal error value is calculated, and the fitting residual error is within ±1 μm, which shows the fitting effect is good.

国家自然科学基金（51575070）和国家"高档数控机床与基础制造装备"科技重大专项（2013ZX04011-013，2013ZX04012-041，2014ZX04001-031，2016ZX04004005）资助项目。