| 基于切削声音的刀具磨损状态识别研究 |
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| 引用本文： | 刘刚. 基于切削声音的刀具磨损状态识别研究[J]. 机械研究与应用, 2008, 21(6): 51-54 |
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| 作者姓名： | 刘刚 |
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| 作者单位： | 齐齐哈尔矿产勘查开发总院,黑龙江,齐齐哈尔,161006 |
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| 摘 要： | 人工神经网络可以实现多特征信息的融合，将基于BP神经网络，建立各频率段能量百分比与刀具磨损的映射关系，进行刀具磨损状态识别的研究。最后在Labview环境下调用Matlab神经网络程序，初步实现了刀具磨损的识别。
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| 关 键 词： | 刀具磨损 切削声音信号 神经网络 |
Study of tool wear state recognition based on cutting sounds |
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| Liu Gang. Study of tool wear state recognition based on cutting sounds[J]. Mechanical Research & Application, 2008, 21(6): 51-54 |
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| Authors: | Liu Gang |
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| Affiliation: | Liu Gang ( Qiqihaer mineral perambulation general institute, Qiqihaer Heilongjiang 161006, China) |
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| Abstract: | Artificial neural network can fuse excessive trait signals . The author builds the relationship between each frequency stage energy percent and tool wear based on BP neural network to study the tool wear state recognition. At last, by using the Matlab BP neural network procedure in Labview, wear state recognition is accomplished. |
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| Keywords: | tool wear cutting sound signal neural network |
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