摘要
为了提高精密数控机床的加工精度,减少精密机床的热误差,文章提出了模糊神经网络径向热误差的建模方法。以数控加工中心关键点的温度和主轴径向的热变形量的关系为基础,应用模糊神经网络建模法,采用精密卧式加工中心主轴径向热误差的数据,对机床主轴热误差进行建模与预报。从数控机床主轴建模试验结果分析表明,模糊神经网络预测模型能够较为精准的对机床主轴径向热误差的做出预测,在实际应用中有利于提高机床的补偿精度,对数控机床热误差补偿提供参照。
In order to improve the machining accuracy of precision CNC machine tools and reduce the ther- mal error of precision machine tool, the method of fuzzy neural network radial thermal error modeling is proposed. Based on the relationship between the temperature at the key point of the NC machining center and the thermal deformation in the radial direction of the spindle. The thermal error of the machine tool is modeled and predicted by using the data of a precision horizontal machining center radial thermal error and the learning performance of the fuzzy neural network. The experimental results show that the accuracy of fuzzy neural network model prediction is exactly accurate, which will improve the compensation accuracy and applicate in practical engineering, and provide a practical reference for thermal error compensation of CNC machine tools.
出处
《组合机床与自动化加工技术》
北大核心
2017年第8期51-54,共4页
Modular Machine Tool & Automatic Manufacturing Technique
关键词
模糊数学
T-S神经网络
主轴热误差
T-S模型预测
the fuzzy mathematics theory
T-S neural network
the spindle thermal error
T-S model predic- tion
