基于局部均值分解和峭度图的滚动轴承包络分析方法

张亢; 程军圣

doi:10.13224/j.cnki.jasp.2015.12.030

基于局部均值分解和峭度图的滚动轴承包络分析方法

doi: 10.13224/j.cnki.jasp.2015.12.030

张亢¹,
程军圣²

1. 长沙理工大学能源与动力工程学院, 长沙 410076;
2. 湖南大学机械与运载工程学院, 长沙 410082

基金项目:

国家自然科学基金(51305046)

能源高效清洁利用湖南省高校重点实验室开放基金(2013NGQ007)

详细信息

作者简介:
张亢(1983-),男,湖南长沙人,讲师,博士,主要从事机械故障诊断研究.

中图分类号: V233.4⁺5;TN911.7;TH165.3
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- 文章访问数: 762
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- 被引次数: 0
出版历程
- 收稿日期: 2014-04-28
- 刊出日期: 2015-12-28

Roller bearing envelope analysis method based on local mean decomposition and kurtogram

ZHANG Kang¹,
CHENG Jun-sheng²

1. School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha 410076, China;
2. College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410082, China

摘要

摘要: 提出了基于局部均值分解(local mean decomposition,LMD)和峭度图(kurtogram)的滚动轴承包络分析方法.该方法中,原始滚动轴承故障振动信号通过LMD进行自适应的频率成分分离和初步降噪,包络分析中带通滤波器的参数通过峭度图客观地提供,从而提高滚动轴承包络分析的准确度.通过对滚动轴承仿真信号以及实验信号的分析,结果表明:在低信噪比情况下,LMD可以自适应分离出滚动轴承的固有振动成分,峭度图可以自动确定包络分析中带通滤波器的参数,与传统包络分析比较,所提方法能更加清晰准确地提取滚动轴承的故障特征.
- 故障诊断 /
- 滚动轴承 /
- 局部均值分解 /
- 峭度图 /
- 包络分析 /
- 故障特征
Abstract: Roller bearing envelope analysis method based on local mean decomposition (LMD) and kurtogram was proposed. In this method, the original roller bearing fault vibration signal was decomposed into a set of frequency components and preliminary reduced noises adaptively by LMD, and the parameters of band-pass filter in envelope analysis were provided objectively by kurtogram, thus the envelope analysis accuracy for roller bearing can be enhanced. The analytical results from roller bearing simulation signals and experiment signals indicate that the natural vibration components of roller bearing can be separated by LMD adaptively and the parameters of band-pass filter in envelope analysis can be determined by kurtogram automatically in low signal-to-noise ratio. Compared with traditional envelope analysis, the proposed method can extract the fault features of roller bearing more clearly and accurately.
- fault diagnosis /
- roller bearing /
- local mean decomposition /
- kurtogram /
- envelope analysis /
- fault feature

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参考文献(18)

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