关键词: 温度测点, 模糊聚类分析, 相关性分析, 热误差模型, 热误差补偿

Abstract: Thermal error seriously affects the machining accuracy of the machine,and it is a very effective way to improve the precision of the machine by thermal error compensation.The selection and optimization of temperature measurement points are the difficulties in the study of thermal error compensation technology.In order to reduce the number of temperature measurement points reasonably,the temperature distribution of the parts in the feed system under different working conditions is tested.The fuzzy clustering analysis method is used to classify the temperature variation of the measuring point.Through the analysis of the distribution of the spindle temperature field and the method of correlation analysis,five temperature characteristic points were selected from 24 temperature measuring points to compensate the thermal error of the machining center,which greatly improved the efficiency of the thermal error model.The method optimizes the position of the temperature sensor measuring point,achieves the simplified temperature measuring point and improves the accuracy of the thermal error compensation.

Key words: temperature measuring points, fuzzy clustering analysis, correlation analysis, thermal error model, thermal error compensation