| 基于FCM聚类和RBF神经网络的机床热误差补偿建模 |
| |
| 引用本文： | 苏铁明,叶三排,孙伟.基于FCM聚类和RBF神经网络的机床热误差补偿建模[J].组合机床与自动化加工技术,2011(10). |
| |
| 作者姓名： | 苏铁明 叶三排 孙伟 |
| |
| 作者单位： | 大连理工大学机械工程学院,辽宁,大连,116023 |
| |
| 基金项目： | “高档数控机床与基础制造装备”科技重大专项(2009ZX04001-021-02) |
| |
| 摘 要： | 热关健点的选择和热误差建模技术是决定热误差补偿是否有效的关键,对提高数控机床的加工精度至关重要.为了实现对数控机床热误差的补偿控制,文章利用模糊C均值(FCM)聚类方法,对机床上布置的温度测点进行优化筛选,将温度变量从20个减少到4个,然后给出了基于RBF热误差补偿建模方法.通过建模实例表明,文章提出的建模方法,在保证补偿模型精度的同时有效减少了温度测点,降低了变量耦合影响,并提高了补偿模型的鲁棒性.
|
| 关 键 词： | 数控机床 热误差补偿 模糊C均值聚类 RBF神经网络 |
Thermal Error Compensation Modeling Based on Fuzzy C-means Clustering Algorithm and RBF Neural Network Modeling |
| |
| SU Tie-ming,YE San-pai,SUN Wei.Thermal Error Compensation Modeling Based on Fuzzy C-means Clustering Algorithm and RBF Neural Network Modeling[J].Modular Machine Tool & Automatic Manufacturing Technique,2011(10). |
| |
| Authors: | SU Tie-ming YE San-pai SUN Wei |
| |
| Affiliation: | SU Tie-ming,YE San-pai,SUN Wei(School of Mechanical Engineering,Dalian University of Technology,Dalian Liaoning 116023,China) |
| |
| Abstract: | The selection of thermal critical points and thermal error compensation modeling technique are crucial in deciding the effectiveness of thermal error compensation and important for improving machining accuracy of numerical control(NC) machine.In order to realize the compensation of the thermal error of NC machine,the temperature measurement points are optimized based on the fuzzy C-means(FCM) clustering algorithm and the number of temperature measurement points is cut down from 20 to 4,then the thermal erro... |
| |
| Keywords: | NC machine tools thermal error compensation fuzzy C-means clustering RBF neural network |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
