摘要
在分析某XH718加工中心主轴及主轴箱结构和热源的基础上,在主轴箱上初步选择多个测温点,根据测温点温度和主轴热误差的数据,应用模糊聚类分析和相关性分析对测温点进行了优化,确定最小数量的关键测温点。然后应用多元线性回归理论建立了关键测温点的温升和热误差的数学模型。数学模型在加工中心上补偿后的数据表明,可以在很大程度上改进加工中心的精度,达到了客户需要的精度要求。
After analyzing the structure and thermal source of the spindle and spindle box of XH718 Type machining center, the paper selected numerous temperature measurement points from the spindle box. In light of the temperature and thermal error data of the spindle at the temperature measurement points, it optimized the temperature measurement points using fuzzy set analysis and correlation analysis, thus defining their minimum key points. Then it established the mathematical model of temperature and thermal errors using the polynomial linear regression theory. The compensation for errors on the machining center demonstrates that the mathematical model can enhance its precision to a great degree, meeting its customers' accuracy requirement.
出处
《机械科学与技术》
CSCD
北大核心
2007年第4期511-514,共4页
Mechanical Science and Technology for Aerospace Engineering
基金
成都市科技局支持项目(05HJDZ299)资助
关键词
加工中心
热误差补偿
多元线性回归
模糊聚类
machining center
thermal error compensation
polynomial linear regression
fuzzy group