| 一种新的声发射刀具磨损小波分析方法 |
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| 引用本文： | 陈晓智,李蓓智,杨建国.一种新的声发射刀具磨损小波分析方法[J].无损检测,2007,29(1):12-15,35. |
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| 作者姓名： | 陈晓智 李蓓智 杨建国 |
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| 作者单位： | 东华大学,机械工程学院,先进制造技术研究中心,上海,200051 |
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| 摘 要： | 提出了一种新的声发射刀具磨损小波判析方法，该方法通过多层小波分解对信号主能量所处频段进行局部特性刻画，利用小波分解系数特征统计值在统计量与刀具状态间建立物理联系。实例表明，该方法能有效地判断刀具状态，比常用的利用神经网络进行状态分析的方法更具有理论直观性与操作的时效性。
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| 关 键 词： | 声发射 刀具磨损检测 小波分析 |
| 文章编号： | 1000-6656（2007）01-0012-03 |
| 收稿时间： | 2006-04-12 |
| 修稿时间： | 2006-04-12 |
A New Wavelet Analysis Method for Acoustic Emission Tool Wear |
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| CHEN Xiao-zhi,LI Bei-zhi,YANG Jian-guo.A New Wavelet Analysis Method for Acoustic Emission Tool Wear[J].Nondestructive Testing,2007,29(1):12-15,35. |
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| Authors: | CHEN Xiao-zhi LI Bei-zhi YANG Jian-guo |
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| Affiliation: | Advanced Manufacture Technology Research Center, Donghua University, Shanghai 200051, China |
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| Abstract: | A new wavelet analysis method for acoustic emission tool wear distinguish is presented.The local characterize of the frequency band which contains the signal main energy is depicted by the multiplayer wavelet decomposition.Since then,the physical relationship between the wavelet decomposition coefficients' statistical value and tool state can be built up.Its validity is proved by the turning experiments.It has much more theory visualizability and maneuverability than the usual prediction method which based on artificial nerve network(ANN). |
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| Keywords: | Acoustic Emission Tool wear monitoring Wavelet analysis |
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