| 基于小波分析的声发射刀具状态判析 |
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| 引用本文： | 陈晓智,李蓓智,杨建国. 基于小波分析的声发射刀具状态判析[J]. 传感器与微系统, 2006, 25(6): 19-21,24 |
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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,上海,200051 |
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| 摘 要： | 提出了一种基于小波分析的声发射刀具状态判析方法,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2——范数表征信号的奇异性,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,并具有较好理论基础与操作性。
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| 关 键 词： | 声发射 刀具磨损检测 小波分析 |
| 文章编号： | 1000-9787（2006）06-0019-03 |
| 收稿时间： | 2005-12-28 |
| 修稿时间： | 2005-12-28 |
Acoustic emission cutting tool state distinguishing based on wavelet analysis |
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| CHEN Xiao-zhi,LI Bei-zhi,YANG Jian-guo. Acoustic emission cutting tool state distinguishing based on wavelet analysis[J]. Transducer and Microsystem Technology, 2006, 25(6): 19-21,24 |
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| Authors: | CHEN Xiao-zhi LI Bei-zhi YANG Jian-guo |
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| Affiliation: | College of Mechanical Engineering, Donghua University, Shanghai 200051, China |
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| Abstract: | A method based on wavelet analysis of acoustic emission(AE) cutting tool state distinguishes and analysis is presented.The local characterize of the frequency band which contains the signal main energy is depicted by the multiplayer wavelet decomposition,and the strangeness of signal is represented by wavelet decomposition coefficient 2—norm.The physical relationship between the statistic and tool state is built up.Its validity is proved by the turning experiments.The nethod can preferably distinguish tool state,and it has a preferable theory foundation and maneuverability. |
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| Keywords: | acoustic emission(AE) tool wear monitoring wavelet analysis |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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