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| 基于人工神经网络的微钻头破损监测 | |
| 引用本文： | 孙艳红,杨兆军,杨晓东,张立新.基于人工神经网络的微钻头破损监测[J].汽车工艺与材料,2006(11):21-23. |
| 作者姓名： | 孙艳红 杨兆军 杨晓东 张立新 |
| 作者单位： | 1. 吉林工程技术师范学院,吉林,长春,130052;吉林大学,吉林,长春,130025 2. 吉林大学,吉林,长春,130025 3. 吉林工程技术师范学院,吉林,长春,130052 |
| 摘 要： | 采用人工神经网络技术对与微钻头破损有因果关系的轴向力、扭矩和主电机电流等多种物理量进行信息融合,建立了适合于微小孔数控钻床的钻头破损在线监测系统,并验证了该系统对钻头破损的检出率达94.5%以上,证明了该系统在生产上应用的有效性。 |
| 关 键 词： | 微钻头 破损 状态监测 人工神经网络 信息融合 |
| 文章编号： | 1003-8817(2006)11-0021-02 |
| 收稿时间： | 2006-06-22 |
| 修稿时间： | 2006年6月22日 |
A Monitoring Method for Micro-Drill Breakage Based on Artificial Neural Networks |
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| SUN Yan-hong,YANG Zhao-jun,YANG Xiao-dong,ZHANG Li-xin.A Monitoring Method for Micro-Drill Breakage Based on Artificial Neural Networks[J].Automobile Technology & Material,2006(11):21-23. | |
| Authors: | SUN Yan-hong YANG Zhao-jun YANG Xiao-dong ZHANG Li-xin |
| Institution: | 1.Jilin Teachers Institute of Engineering and Technology,Changchun Jilin 130052,China;2.Jilin University, Changchun Jilin 130025,China |
| Abstract: | Multi-information amalgamation is done for axial force,torque and main motor current and so on,which represent the causal relationship to micro-drills breakage,by using artificial neural network technology.An in-process monitoring system for micro-hole numerical control drill press is built up based on artificial neural networks. Experiments demonstrate the rate of checking out micro-drills breakage has reached 94.5% and the system has practicality value very well. |
| Keywords: | micro-drill breakage status monitoring artificial neural networks multi- information amalgamation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |