摘要
通过模糊聚类分析方法将不同位置测点的温度按特征进行归类,用热误差敏感度分析方法从每一类别中选出一个最优测点组成最优测点组合,实现数控机床温度测点优化,并利用最小二乘法进行多元线性回归分析对机床热误差进行建模,与实验对比,验证了此温度测点优化选择方法的有效性。
The paper classed the temperature measuring points at different positions according to characteristic based on fuzzy cluster theory,and thermal error sensitivity analytical method was adapted to determine optimum measuring point in every class,to make temperature measuring points optimization come true.Thermal error model is proposed with the least square method and contrasted with the experiments to validate the temperature measuring points optimization methods.
出处
《制造技术与机床》
北大核心
2013年第11期31-36,共6页
Manufacturing Technology & Machine Tool
关键词
温度测点优化
数控机床
模糊聚类
热误差敏感度
Temperature Measuring Points Optimization
CNC Machine Tool
Fuzzy Clustering
Thermal Error Sensitivity
