摘要
为提高机床加工精度,研究并选择最佳模型对立式加工中心主轴热误差进行补偿。以KVC650E立式加工中心为实验对象,根据秋季数据对主轴热误差建立了多元线性回归、神经网络和支持向量机模型;将同一台机床和另一台同类型机床所测得的冬季数据分别代入3种模型计算各模型补偿精度;根据3种模型的精度变化规律比较三者的精确性、鲁棒性和通用性。实验结果表明:3种模型都有各自的优势,但支持向量机模型能在不同的环境温度和机床条件下保证较高的精度,综合性能最好。
In order to improve the machining precision of machine tools,an optimal model to compensate the thermal error of the spindle was explored and selected,In experinments the KVC650 E vertical machining center was taken as a research object,and Multiple Linear Regression( MLR) model,Neural Network( NN) model and Support Vector Machine( SVM) model were established according to the first batch of data of the CNC center gained in autumn. By substituting the second batch of data measured in winter on the same machine and the third batch of data measured in winter on another similar machine into three kinds of models respectively,the compensation accurary of each model was calculated. The accuracy,robustness and versatility between three models was compared according to the precision variation regulation. The experiment shows that the three models have their own advantages,but SVM model ensure high precision in different environmental temperature and machine conditions,which has the best comprehensive properities.
出处
《机床与液压》
北大核心
2015年第5期82-85,共4页
Machine Tool & Hydraulics
关键词
热误差
多元线性回归
神经网络
支持向量机
立式加工中心
Thermal error
Multiple linear regression
Neural network
Support vector machine
Vertical machining center
