Extraction method for acoustic emission characteristic signal of grinding machine based on wavelet decomposition

MA Hao; YIN Jian-long; LI Dong-sheng

doi:10.13873/J.1000-9787(2016)07-0013-03

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Extraction method for acoustic emission characteristic signal of grinding machine based on wavelet decomposition

更新时间：2025-09-11

- Extraction method for acoustic emission characteristic signal of grinding machine based on wavelet decomposition
- Vol. 35, Issue 7, Pages: 13-15(2016)
- 作者机构：
  
  中国计量学院计量与测试工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2016)07-0013-03
  CLC： TG580.6
- Published：2016
- 稿件说明：
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[1]马豪,尹健龙,李东升.基于小波分解的磨床声发射特征信号提取方法[J].传感器与微系统,2016,35(07):13-15.

MA Hao, YIN Jian-long, LI Dong-sheng. Extraction method for acoustic emission characteristic signal of grinding machine based on wavelet decomposition[J]. 2016, 35(7): 13-15.
[1]马豪,尹健龙,李东升.基于小波分解的磨床声发射特征信号提取方法[J].传感器与微系统,2016,35(07):13-15. DOI： 10.13873/J.1000-9787(2016)07-0013-03.

MA Hao, YIN Jian-long, LI Dong-sheng. Extraction method for acoustic emission characteristic signal of grinding machine based on wavelet decomposition[J]. 2016, 35(7): 13-15. DOI： 10.13873/J.1000-9787(2016)07-0013-03.

摘要

磨床磨削加工环境复杂

传统的信号分析方法难以对其进行有效的特征信号提取

提出了一种基于小波分解与能量谱相结合的特征信号提取方法。利用小波多尺度、多分辨率的特性

对磨床磨削的声发射信号进行多尺度分解;根据金属磨削的声发射信号的特性

选取最优频率段进行频谱分析

再结合能量谱提取特征信号。通过对自行研发的磨削监测系统工程试验分析表明:该方法能够有效、准确地诊断出磨削的每个状态

误判率为0.02%

相比单一的频谱分析诊断

精度更高、可靠性更好

具有一定的工程实用价值。

Abstract

The complex environment of grinding makes it difficult for traditional method of signal analysis to extract feature signal

therefore

a feature extraction method based on wavelet decomposition and energy spectrum is proposed. Using wavelet multi-scale and multi-resolution characteristics

the acoustic emission signal is decomposed by multi-scale decomposition; according to characteristics of acoustic emission signal of metal grinding

optimal frequency band is selected to carry out spectrum analysis

and combined with energy spectrum characteristic signal is extracted. The experimental analysis on self-developed grinding monitoring system shows that this method can effectively and accurately diagnose various state of the grinding

and the false positive rate is0. 02 %. Compared with the single spectrum analysis

the precision is higher and the reliability is better

and it has certain engineering practical value.

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Keywords

references

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缺陷试板拉伸过程声发射信号特性的相关性分析 [J]. 孙国豪,柏明清,王希,李建宏,潘家祯. 无损检测 . 2010(08)

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Wavelet transform of acoustic emission signals in failure of model composites [J] . Qing-Qing Ni,Masaharu Iwamoto. Engineering Fracture Mechanics . 2002 (6)

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