摘要
运用RBF神经网络理论建立机床主轴热误差数学模型,首次采用API主轴测量系统对150MD24Y16型电主轴进行了热变形实时测量。实验结果表明,所测主轴热变形沿Z轴方向最大,在主轴转速1000r/min的条件下,约为43μm,并依据国际标准对主轴进行了24h测量,为后期有限元分析和实时补偿提供了实测数据和经验保障。
A neural network based on radial basis function（RBF） is used to predict the thermal error of a CNC turning center.At the same time,this paper studies firstly the thermal deformation of 150MD24Y16 motorized spindle using the spindle measurement system of API.The results shows that thermal deformation along the Z axis is maximum,and about 43μm on it continuous operation at 1 000r/min.According to international standards,the spindle continues the measurement for 24 hours.All the above measurements provide the measured data and experience for the future of finite element analysis and real-time compensation.
出处
《制造技术与机床》
CSCD
北大核心
2011年第8期27-30,共4页
Manufacturing Technology & Machine Tool
基金
国家重大专项(2009ZX04014-036)
北京工业大学博士科研启动基金项目资助
关键词
主轴
径向基函数
神经网络
热变形
实时测量
API
Spindle
Radial Basis Function
Neural Network
Thermal Deformation
Real-time Measurement
API
