| 引用本文: | 杨林,李圣怡,梁建成,等.基于特征融合的刀具磨损监测方法.[J].国防科技大学学报,1996,18(4):49-53.[点击复制] |
| Yang Lin,Li Shengyi,Liang Jiancheng,et al.A Tool Wear Monitoring Method Based on Feature Fusion[J].Journal of National University of Defense Technology,1996,18(4):49-53[点击复制] |
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| 基于特征融合的刀具磨损监测方法 |
| 杨林, 李圣怡, 梁建成, 吴学忠 |
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(国防科技大学 机械电子工程与仪器系 湖南 长沙 410073)
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| 摘要: |
| 提出了-种基于特征融合的刀具磨损监测方法，将该方法应用于铣刀磨损监测取得了较好的效果，文中论述了特征融合方法的基本思想，多传感器信号的特征关联、抽取及正规化处理，作为融合中心的神经网络的构造及训练等内容。实验分析表明，该方法实现刀具磨损监测是行之有效的。 |
| 关键词: 刀具磨损，特征融合，神经网络，监测 |
| DOI： |
| 投稿日期：1996-03-25 |
| 基金项目:国家自然科学基金资助项目 |
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| A Tool Wear Monitoring Method Based on Feature Fusion |
| Yang Lin, Li Shengyi, Liang Jiancheng, Wu Xuezhong |
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(Department of Electromechanics and lnstrumentation，NUDT，Changsha，410073)
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| Abstract: |
| This paper presents a tool wear monitoring method based on feature fusion via neural networks. The basic principle of this method，feature association，feature extraction，data normalization and neural networks construction of the method are discussed. The experimintal results show that the proposed method for tool wear monitoring is reliable and effective. |
| Keywords: tool wear,feature fusion,neural networks, Monitoring |
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