Acoustic emission cutting tool state distinguishing based on wavelet analysis

CHEN Xiao-zhi; LI Bei-zhi; YANG Jian-guo

doi:10.13873/j.1000-97872006.06.006

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Acoustic emission cutting tool state distinguishing based on wavelet analysis

更新时间：2025-09-11

- Acoustic emission cutting tool state distinguishing based on wavelet analysis
- Issue 6, Pages: 19-21+24(2006)
- 作者机构：
  
  1. 东华大学机械工程学院
  2. 东华大学机械工程学院,上海,200051
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872006.06.006
  CLC： TG71
- Published：2006
- 稿件说明：
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[1]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(06):19-21+24.

CHEN Xiao-zhi, LI Bei-zhi, YANG Jian-guo. Acoustic emission cutting tool state distinguishing based on wavelet analysis[J]. 2006, (6): 19-21+24.
[1]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(06):19-21+24. DOI： 10.13873/j.1000-97872006.06.006.

CHEN Xiao-zhi, LI Bei-zhi, YANG Jian-guo. Acoustic emission cutting tool state distinguishing based on wavelet analysis[J]. 2006, (6): 19-21+24. DOI： 10.13873/j.1000-97872006.06.006.

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。

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

references

声发射信号的参数分析方法 [J]. 沈功田,耿荣生,刘时风. 无损检测 . 2002(02)

子波变换理论及其在信号处理中的应用[M]. 国防工业出版社 , 陈逢时著, 1998

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