GEAR FAULT DIAGNOSIS BASED ON THE FREQUENCY SLICE WAVELET TRANSFORM TIME-FREQUENCY ANALYSIS METHOD

CAI JianHua; HUANG GuoYu; LI XiaoQin

doi:10.16579/j.issn.1001.9669.2017.05.005

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GEAR FAULT DIAGNOSIS BASED ON THE FREQUENCY SLICE WAVELET TRANSFORM TIME-FREQUENCY ANALYSIS METHOD

更新时间：2022-09-22

- GEAR FAULT DIAGNOSIS BASED ON THE FREQUENCY SLICE WAVELET TRANSFORM TIME-FREQUENCY ANALYSIS METHOD
- Journal of Mechanical Strength Vol. 39, Issue 5, Pages: 1026-1030(2017)
- 作者机构：
  
  1. 湖南文理学院信息研究所
  2. 南华大学电气工程学院
- 作者简介：
- 基金信息：
- DOI：10.16579/j.issn.1001.9669.2017.05.005
  CLC：
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CAI JianHua, HUANG GuoYu, LI XiaoQin. GEAR FAULT DIAGNOSIS BASED ON THE FREQUENCY SLICE WAVELET TRANSFORM TIME-FREQUENCY ANALYSIS METHOD. [J]. 39(5):1026-1030(2017)
DOI：

CAI JianHua, HUANG GuoYu, LI XiaoQin. GEAR FAULT DIAGNOSIS BASED ON THE FREQUENCY SLICE WAVELET TRANSFORM TIME-FREQUENCY ANALYSIS METHOD. [J]. 39(5):1026-1030(2017) DOI： 10.16579/j.issn.1001.9669.2017.05.005.

摘要

为了在强噪声中有效提取齿轮的故障特征,提出了一种基于频率切片小波变换时频分析的齿轮故障诊断方法。先对信号进行频率切片小波变换,得到在全频带下的时频分布,然后在此基础上分割出含有故障特征的时频区域,再通过对该区域进行时频阈值滤波和逆变换重构分离出有效的故障特征。仿真实验和实测信号分析表明,这种方法可从噪声信号中分离出有效的特征分量,在齿轮故障诊断方面取得了较好的应用效果。

Abstract

In order to extract the gear fault characteristics under the strong noise condition,a fault feature separation and extraction method was proposed based on a new time-frequency decomposition method,the frequency slice wavelet transform（ FSWT）. Firstly,the signal was processed with the FSWT to get its time-frequency distribution. Then the time and frequency intervals,which contain the fault feature, were chosen to do threshold de-noising in time-frequency domain. Through reconstructing signals from the characteristic frequency slices,separation and extraction of time-frequency features were realized.The proposed method was shown to be efficient by simulations and engineering applications. It has the ability to isolate the desired components from noisy signals. It achieves an ideal effect on feature extraction for gear fault diagnosis.

关键词

频率切片小波变换时频分析齿轮故障诊断

Keywords

Frequency slice wavelet transformTime-frequency analysisGearFault diagnosis

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