[1]李志农,刘立州.分数阶经验模态分解方法在机械故障诊断中应用[J].华侨大学学报(自然科学版),2010,31(4):367-370.[doi:10.11830/ISSN.1000-5013.2010.04.0367]
　LI Zhi-nong,LIU Li-zhou.Application of the Method of Fractional Empirical Mode Decomposition to Machine Fault Diagnosis[J].Journal of Huaqiao University(Natural Science),2010,31(4):367-370.[doi:10.11830/ISSN.1000-5013.2010.04.0367]
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分数阶经验模态分解方法在机械故障诊断中应用()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第31卷
期数:
2010年第4期
页码:
367-370
栏目:
出版日期:
2010-07-20

文章信息/Info

Title:
Application of the Method of Fractional Empirical Mode Decomposition to Machine Fault Diagnosis
文章编号:
1000-5013(2010)04-0367-04
作者:
李志农; 刘立州
南昌航空大学无损检测技术教育部重点实验室; 郑州大学机械工程学院
Author(s):
LI Zhi-nong1; 2;  LIU Li-zhou2
1.Key Laboratory of Nondestructive Testing, Ministry of Education, Nanchang Hangkong University, Nanchang 360063, China; 2.School of Mechanical Engineering, Zhengzhou University, Zhengzhou 450001, China
关键词:
故障诊断;  分数阶Fourier变换;  经验模态分解;  仿真
Keywords:
fault diagnosis;  fractional Fourier transform;  empirical mode decomposition;  simulation
分类号:
TH165.3
DOI:
10.11830/ISSN.1000-5013.2010.04.0367
文献标志码:
A
摘要:
将经验模态分解方法(EMD)和分数阶Fourier变换基本理论相结合,提出一种基于分数阶Fourier变换的经验模态分解的机械故障诊断方法.仿真结果表明,提出的方法是有效的,尤其是对于用EMD分解方法无法进行有效分解的信号.如果时频平面旋转一定的角度,将信号从EMD难以分离的区域变换到可以用EMD分解有效识别的区域,然后经过EMD分解和分数阶Fourier反变换,就可以实现分量的提取.诊断实例进一步验证方法的有效性.
Abstract:
Combining empirical mode decomposition(EMD) and fractional Fourier transform,a new fault diagnosis method based on fractional empirical mode decomposition is proposed.The proposed method is compared with the conventional time-frequency analysis method.The simulation result shows that the proposed method is very effective,especially for signal which can hardly be decomposed by conventional EMD method.The proposed method rotates the signal in the time-frequency plane,and transforms the signal from the hardly decomposable domain to easily decomposable domain,the component of the signal can be effectively extracted by EMD and fractional Fourier reverse transform.The experimental results further have verified the validity of the proposed method.

参考文献/References:

[1] 刘立州. 分数阶非平稳信号处理方法及在机械故障诊断中应用研究 [D]. 郑州:郑州大学, 2009.
[2] 于德介, 程军圣, 杨宇. 机械故障诊断的Hilbert-Huang变换方法 [D]. 北京:科学出版社, 2006.
[3] HUANG N E, SHEN Z, LONG S R. The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis [J]. Proceedings of the Royal Society, 1998, (1971):903-995.doi:10.1098/rspa.1998.0193.
[4] 刘立州, 王穗平, 李志农. 分数倒谱及其在机械故障诊断中应用研究 [J]. 噪声与振动控制, 2009(5):77-79.doi:10.3969/j.issn.1006-1355.2009.05.021.
[5] 吕亚平. 基于时频分析的机械故障源盲分离方法研究 [D]. 郑州:郑州大学, 2009.
[6] LOPARO K A. Bearing data center [EB/OL]. http:∥www.eecs.case.edu/laboratory/bearing/download.html, 2005.

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备注/Memo

备注/Memo:
国家自然科学基金资助项目(50775208); 河南省教育厅自然科学基金资助项目(2006460005,2008C460003)
更新日期/Last Update: 2014-03-23