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[1]贺文杰,Bajolet Julien,Yoann Plassard,等.基于EMD和FFT的齿轮箱故障诊断[J].武汉工程大学学报,2011,(01):65-70,95.[doi:10.3969/j.issn.16742869.2011.01.017]
　HE Wen jie,BAJOLET Ju lien,PLASSARD Yoann,et al.Gearbox fault diagnosis based on EMD and FFT[J].Journal of Wuhan Institute of Technology,2011,(01):65-70,95.[doi:10.3969/j.issn.16742869.2011.01.017]
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基于EMD和FFT的齿轮箱故障诊断(/HTML)
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《武汉工程大学学报》[ISSN:1674-2869/CN:42-1779/TQ]

卷:
期数:
2011年01期
页码:
65-70,95
栏目:
机电与信息工程
出版日期:
2011-01-30

文章信息/Info

Title:
Gearbox fault diagnosis based on EMD and FFT
文章编号:
16742869(2011)01006506
作者:
贺文杰1; Bajolet Julien2;  Yoann Plassard2; 陈汉新1; 鲁艳军1
1.武汉工程大学机电工程学院,湖北 武汉 430074;2.法国国立梅斯工程师学院,梅斯 57078
Author(s):
HE Wenjie1;  BAJOLET Julien2;  PLASSARD Yoann2;  CHEN Hanxin1;  LU Yanjun1
1.School of Mechanical and Electrical Engineering, Wuhan Institute of Technology, Wuhan 430074, China;
2.Ecole Nationale d’Ingénieurs de Metz, Metz 57078, France
关键词:
齿轮箱; 经验模态分解; 快速傅里叶变换; 故障诊断
Keywords:
gearbox;  empirical mode decomposition;  fast Fourier transform;  fault diagnosis
分类号:
TH165+.3
DOI:
10.3969/j.issn.16742869.2011.01.017
文献标志码:
A
摘要:
提出了一种基于小波包分析(WPA),经验模态分解(EMD)和快速傅里叶变换(FFT)的齿轮箱故障诊断方法,此方法适合于非线性非稳态信号的自适应分析.首先运用WPA对采集的齿轮箱振动信号进行分解可得到不同频率的子频带;然后对各子频带信号进行EMD,从而得到一定数量的本征模态函数(IMF);最后选取特定的IMF,对其作FFT可得到相应的功率谱,从而提取齿轮箱故障特征频率,进而对齿轮箱故障模式进行识别和诊断.分析结果表明本文所提议的方法能有效地检测出齿轮箱故障特征频率.
Abstract:
Based upon wavelet packet analysis (WPA), empirical mode decomposition (EMD) and fast Fourier transform (FFT), a novel fault diagnosis method of gearbox is proposed in this paper. It is an adaptive signal processing method that is very suitable for nonlinear and nonstationary signals. Firstly, WPA is used to decompose the original vibration signals collected from gearbox in order to obtain different frequency bands with various frequencies. Second, EMD is applied to analyze different frequency bands to acquire a finite number of stationary intrinsic mode function (IMF). Finally, FFT is employed to obtain corresponding power spectrum density through analyzing the special IMF. Fault characteristic frequency can be extracted according to the power spectrum so that we can identify and diagnosis for fault modes of gearbox. The analysis results show that the proposed approach based on EMD and FFT is able to detect gearbox fault characteristic frequency effectively.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期：20101229基金项目：湖北省教育厅科学技术研究重大项目（Z20101501）;武汉市科技局科技攻关项目（201010621237）作者简介：贺文杰（1986）,男,湖北监利人,硕士研究生在读.研究方向：机械系统的故障检测与诊断.指导老师：陈汉新，男，教授，博士.研究方向：机械故障诊断、无损检测和系统状态监测.
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