Thermal Error Modeling and Compensating of Motorized Spindle Based on Improved Neural Network

摘要：

In a lot of factors, thermal deformation of motorized high-speed spindle is a key factor affecting the manufacturing accuracy of machine tool. In order to reduce the thermal errors, the reasons and influence factors are analyzed. A thermal error model, that considers the effect of thermodynamics and speed on the thermal deformation, is proposed by using genetic algorithm-based radial basis function neural network. The improved neural network has been trained and tested, then a thermal error compensation system based on this model is established to compensate thermal deformation. The experiment results show that there is a 79％ decrease in motorized spindle errors and this model has high accuracy.

关键词： motorized spindle thermal error genetic algorithm neural network

作者: Chunli Lei Zhiyuan Rui

作者单位: Key Laboratory of Digital Manufacturing Technology and Application,The Ministry of Education,Lanzhou University of Technology,Lanzhou,China,730050 School of Mechanical and Electronic Engineering,Lanzhou University of Technology,Lanzhou,China,730050

会议类型: 国际会议

会议名称: 2010 International Conference on Material and Manufacturing Technology(2010材料与制造技术国际会议 ICMMT2010)

会议地点: 重庆

会议语种:英文

页码: 556-560

在线出版日期: 2010-09-17（万方平台首次上网日期，不代表论文的发表时间）