• CN:11-2187/TH
  • ISSN:0577-6686

›› 2002, Vol. 38 ›› Issue (3): 69-73.

• 论文 • 上一篇    下一篇

基于连续小波变换的齿轮故障诊断方法研究

郑海波;李志远;陈心昭   

  1. 合肥工业大学动态测试中心
  • 发布日期:2002-03-15

FAULT DIAGNOSIS FOR GEARBOXGEAR BASED ON CONTINUOUS WAVELET TRANSFORM

Zheng Haibo;Li Zhiyuan;Chen Xinzhao   

  1. Hefei University of Technology
  • Published:2002-03-15

摘要: 根据连续小波变换具有较二进离散小波变换更精细的尺度分辨率的特点,提出了基于Morlet连续小波变换的时间平均小波谱的概念,同时建立了两种基于时间平均小波谱的故障诊断方法:谱形比较法和特征能量法。将这两种方法应用在变速箱齿轮故障诊断中,结果表明,时间平均小波谱可以有效提取齿轮故障特征信息;谱形比较法和特征能量法能够准确诊断齿轮故障程度,且特征能量与齿轮故障程度成二次曲线关系。为齿轮故障诊断提供了一种新途径,对于其他复杂机械设备的故障诊断具有参考价值。

关键词: 变速箱齿轮, 故障程度, 故障诊断, 连续小波变换, 时间平均小波谱

Abstract: Continuous wavelet transform (CWT) has a finer scale resolution than dyadic discrete wavelet transform and wavelet packet transform. The concept of time averaged wavelet spectrum (TAWS) based on Morlet CWT is proposed and two fault diagnosis methods named spectra comparison (SC) and feature energy (FE) based on TAWS are established. The results of the application to gearbox gear fault diagnosis show that TAWS can effectively extract gear fault information, and that SC and FE can accurately detect the gear fault level, and that the feature energy of the TAWS is comic proportional to the gear fault level.

Key words: Continuous wavelet transform, Fault advancement, Fault diagnosis, Gearbox gear, Time averaged wavelet spectrum

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