| 基于人工神经网络的刀具状态监测系统 |
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| 引用本文： | 陈超,徐建林,黄建龙.基于人工神经网络的刀具状态监测系统[J].机械工程学报,2002,38(8):135-138. |
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| 作者姓名： | 陈超 徐建林 黄建龙 |
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| 作者单位： | 甘肃工业大学机电工程学院;甘肃工业大学 |
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| 摘 要： | 在自动化制造业生产中，刀具状态的监测具有十分重要的意义。在充分考虑对刀具状态密切相关的敏感特征参数的基础上，利用人工神经网络模型实现了刀具状态的监测。试验表明，该系统的错报率为6.3%，可有效地应用到工程实际中。最后，对系统的误差进行分析并提出了改进的方向。
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| 关 键 词： | 刀具状态 监测 神经网络 |
| 修稿时间： | 2001年3月9日 |
DETECTION SYSTEM OF TOOL CONDITION BASED ON ARTIFICIAL NEURAL NETWORKS |
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| Chen Chao,Xu Jianlin,Huang Jianlong.DETECTION SYSTEM OF TOOL CONDITION BASED ON ARTIFICIAL NEURAL NETWORKS[J].Chinese Journal of Mechanical Engineering,2002,38(8):135-138. |
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| Authors: | Chen Chao Xu Jianlin Huang Jianlong |
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| Affiliation: | Gansu University of Technology |
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| Abstract: | Detection of tool condition is meaningful in automatic manufacturing process. According to the sensitive feature parameters in close relationship with tool condition, the detection system of tool condition is set up based on artificial neural networks. Experiments show that percentage of erroneous detection is 6.3% and the system is reliable in practical. Finally, the system error is analysed and improvement direction is presented. |
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| Keywords: | Neural network Tool condition Detection |
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