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基于EMD降噪和谱峭度的轴承故障诊断方法

张超 陈建军

张超, 陈建军. 基于EMD降噪和谱峭度的轴承故障诊断方法[J]. 机械科学与技术, 2015, 34(2): 252-256. doi: 10.13433/j.cnki.1003-8728.2015.0220
引用本文: 张超, 陈建军. 基于EMD降噪和谱峭度的轴承故障诊断方法[J]. 机械科学与技术, 2015, 34(2): 252-256. doi: 10.13433/j.cnki.1003-8728.2015.0220
Zhang Chao, Chen Jianjun. A Fault Diagnosis Method of Roller Bearing Based on EMD De-noising and Spectral Kurtosis[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(2): 252-256. doi: 10.13433/j.cnki.1003-8728.2015.0220
Citation: Zhang Chao, Chen Jianjun. A Fault Diagnosis Method of Roller Bearing Based on EMD De-noising and Spectral Kurtosis[J]. Mechanical Science and Technology for Aerospace Engineering, 2015, 34(2): 252-256. doi: 10.13433/j.cnki.1003-8728.2015.0220

基于EMD降噪和谱峭度的轴承故障诊断方法

doi: 10.13433/j.cnki.1003-8728.2015.0220
基金项目: 

内蒙古自治区自然科学基金项目(2013MS0907)资助

详细信息
    作者简介:

    张超(1978-),讲师,博士,研究方向为振动信号处理,旋转机械故障诊断,zhanghero123@163.com

A Fault Diagnosis Method of Roller Bearing Based on EMD De-noising and Spectral Kurtosis

  • 摘要: 能否减小噪声干扰,提高信噪比,有效地提取故障信息是进行滚动轴承早期故障诊断的前提和关键。提出一种基于经验模态分解(empirical mode decomposition,EMD)和谱峭度(spectral kurtosis,SK)的滚动轴承故障诊断方法。首先对所提取的故障信号运用EMD分解,得到多个基本模式分量(intrinsic mode function,IMF),然后根据互相关系数去除伪分量,选取合适的IMF分量进行信号重构以达到降噪目的,突出高频共振成分,再应用谱峭度法确定带通滤波器的参数,最后对重构信号进行包络分析完成故障诊断。
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    [3] 丁康,陈健林,苏向荣.平稳和非平稳振动信号的若干处理方法及发展[J].振动工程学报,2003,16(1):1-10 Ding K, Chen J L, Su X R. Development in vibration analysis and processing methods[J]. Journal of Vibration Engineering,2003,16(1):1-10 (in Chinese)
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    [7] 张超,陈建军,郭迅.基于EMD能量熵和支持向量机的齿轮故障诊断方法[J].振动与冲击,2010,29(10):216-220 Zhang C, Chen J J, Guo X. A gear fault diagnosis method based on EMD energy entropy and SVM[J]. Journal of Vibration and Shock,2010,29(10):216-220 (in Chinese)
    [8] 祝志慧,孙云.基于EMD近似熵和SVM的电力线路故障类型识别[J].电力自动化设备,2008,28(7): 81-84 Zhu Z H, Sun Y. Fault classification for power transmission line using EMD-approximate entropy and SVM[J]. Electric Power Automation Equipment,2008,28(7):81-84 (in Chinese)
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出版历程
  • 收稿日期:  2013-07-31
  • 刊出日期:  2015-02-05

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