大连理工大学学报2016，Vol.56Issue(3)：236-243,8.DOI:10.7511/dllgxb201603003
基于 IFCM-GRA 的空间多维热误差温度测点优化
Optimization of temperature measuring points in multi-dimensional space for thermal error based on IFCM-GRA
摘要
Abstract
Thermal error is one of the main error sources for the precision and ultra‐precision machining .Optimizing the temperature measuring points for the thermal error is the key problem for the thermal error compensation .The numerous temperature measuring points arranged in the multi‐dimensional space of machine tool exist multiple correlations . The quality of choice of the feature points from the numerous measuring points directly affects the thermal error compensation effect .By comprehensively analyzing the multiple correlations among the temperature measuring points and the relation between the temperature and the thermal error , an improved fuzzy C‐means (IFCM ) clustering algorithm is adopted to classify the temperature measuring points . It can reduce the correlations of the temperature measuring points for different classes and avoid the shortcoming of the FCM algorithm which is too sensitive for the initial clustering center to get global convergence .The temperature measuring points are sorted by the grey synthetic degree of association in the grey relational analysis (GRA) ,which can comprehensively reflect the relation between the temperature and the thermal error at the perspective of the value of change and the rate of change .Using IFCM‐GRA to optimize the temperature measuring points can improve the robustness and accuracy of the thermal error model and decrease the number of the temperature measuring points greatly . This method was tested on a horizontal precision machining center .The temperature measuring points were reduced to 4 from 17 .At different revolving speeds ,by using the multiple linear regression ,the model for the optimal temperature measuring points and the thermal error is established .It can predict the thermal error change well .The axial thermal error could be reduced from dozens of microns to 5 microns by analyzing the forecasting model .关键词
数控机床/测点优化/FCM 聚类/灰色关联分析/灰色综合关联度Key words
CNC machine tool/measuring points optimization/fuzzy C-means clustering/grey relational analysis/grey synthetic degree of association分类
机械制造引用本文复制引用
马跃,王洪福,孙伟,黄余彬,鞠修勇..基于 IFCM-GRA 的空间多维热误差温度测点优化[J].大连理工大学学报,2016,56(3):236-243,8.基金项目
辽宁省科技创新重大专项（201301002）． （）
