摘要
针对车床实际加工中主轴与进给轴的热误差相互耦合共同影响工件精度的问题,建立了综合热误差模型并进行了有效补偿。以海德曼HTC500/500精密车床为研究对象,对车床主轴与进给轴热误差的耦合关系进行了解耦;利用模糊聚类理论实现了车床测温点的优化分组,建立了主轴与进给轴的耦合热误差多元线性回归模型,并在精密车床上得到实际应用。结果表明:车床耦合热误差模型符合实际工况,模糊聚类有效降低了温度变量之间的多重共线性,提高了模型的预测精度;主轴x/z方向的预测精度达88.4%、90.7%,进给轴x/z方向的预测精度达82.9%、71.3%;补偿后车床x/z方向精度分别提高了60.3%、56.6%,证明了耦合热误差模型的准确性。
The mutually coupled thermal error of spindle and feed shafts for a lathe strongly affects precision of workpieces. A coupled thermal error model is proposed and implemented for machine tools. For a Headman HTC550/500 precision lathe, the coupled thermal error of spindle and feed shafts is decoupled, and fuzzy clustering is used to optimize the temperature measuring points. Subsequently, a multi-variable linear regression model for coupled thermal error is established and applied. The results show that the coupled thermal error model coincides with the lathe＇ s actual situation; the fuzzy clustering effectively lowers the multicollinearity among temperature variables to improve the prediction accuracy; the prediction accuracy in x and z directions reaches 88.4% and 90.7% for spindle, and 82.9% and 71.3% for feed shafts, so the accuracy of the lathe is improved by 60. 3% in x direction and by 56.6% in z direction after com- pensation.
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2015年第7期105-112,共8页
Journal of Xi'an Jiaotong University
基金
国家高技术研究发展计划资助项目(2012AA040701)
关键词
热误差解耦
热误差建模
模糊聚类分析
误差补偿
thermal error decoupling
thermal error modeling
fuzzy clustering
thermal errorcompensation
