| 基于小波神经网络的高速铣削刀具磨损识别 |
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| 引用本文： | 陈维金,李迎,朱红雨. 基于小波神经网络的高速铣削刀具磨损识别[J]. 组合机床与自动化加工技术, 2005, 0(10): 86-88 |
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| 作者姓名： | 陈维金 李迎 朱红雨 |
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| 作者单位： | 南京理工大学,机械工程学院,南京,210094 |
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| 摘 要： | 刀具磨损一直是制造技术中引人注目的重要问题,对于高速切削来说由于加工成本较高而且刀具价格比较昂贵,因此对高速切削中的刀具状态进行识别和监控具有非常重要的意义.文章通过建立小波神经网络来实现对高速加工中刀具状态的识别,结果与实际情况基本一致,从而表明通过此方法是可以较好的对高速加工刀具状态进行识别的.
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| 关 键 词： | 高速铣削 刀具磨损 小波变换 神经网络 |
| 文章编号： | 1001-2265(2005)10-0086-03 |
| 收稿时间： | 2005-03-17 |
| 修稿时间： | 2005-03-17 |
Tool Wear Identification based on Wavelet Neural Network in High-Speed Milling |
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| CHEN Wei-jin,LI Ying,ZHU Hong-yu. Tool Wear Identification based on Wavelet Neural Network in High-Speed Milling[J]. Modular Machine Tool & Automatic Manufacturing Technique, 2005, 0(10): 86-88 |
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| Authors: | CHEN Wei-jin LI Ying ZHU Hong-yu |
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| Abstract: | The tool wear is a conspicuous problem in manufacture.Because of the high of produce cost and the tool's price,the tool condition identification and monitoring are very significant in high-speed milling.In this paper,a tool wear identification method used a wavelet neural network is introduced.Accorded with the actual states,the experimental results show it is effective to identify the tool wear in high-speed milling. |
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| Keywords: | high-speed milling tool wear wavelet transform neural network |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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