[1]贾民平,许飞云.基于小波分析的进化谱及在故障诊断中的应用[J].东南大学学报(自然科学版),2002,32(6):925-928.[doi:10.3969/j.issn.1001-0505.2002.06.022]
 Jia Minping,Xu Feiyun.Evolutionary spectrum estimation based on the wavelet analysis and its application in fault diagnosis[J].Journal of Southeast University (Natural Science Edition),2002,32(6):925-928.[doi:10.3969/j.issn.1001-0505.2002.06.022]
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基于小波分析的进化谱及在故障诊断中的应用()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
32
期数:
2002年第6期
页码:
925-928
栏目:
机械工程
出版日期:
2002-11-20

文章信息/Info

Title:
Evolutionary spectrum estimation based on the wavelet analysis and its application in fault diagnosis
作者:
贾民平 许飞云
东南大学机械工程系,南京 210096
Author(s):
Jia Minping Xu Feiyun
Department of Mechanical Engineering, Southeast University, Nanjing 210096, China
关键词:
小波分析 进化谱 权函数 分辨率 谱泄漏
Keywords:
wavelet evolutionary spectrum weight function resolution energy leakage
分类号:
TH165.3;TP260.3
DOI:
10.3969/j.issn.1001-0505.2002.06.022
摘要:
在Priestley提出的基于小波分析进化谱理论基础上,对改进进化谱估计的性能进行了研究.首先,重点分析了小波分解的尺度与信号时变趋势和分辨率之间的关系,并指出了根据信号时变特征和分辨率要求确定合理的小波分解尺度.其次,讨论了权函数对进化谱估计能量泄漏现象的影响,指出了选用Hanning窗等作为权函数可以有效地抑制谱泄漏现象.仿真及在故障诊断中的应用与理论分析的结论一致.根据本文所提出的方法来估计非平稳信号的进化谱可以得到更高精度的结果.
Abstract:
The improvement of the accuracy of the wavelet-based evolutionary spectrum estimation is discussed, which is based on the original work of Priestley. Firstly, the relation between wavelet decomposition level, the time-dependent feature of signal and resolution requirement is analyzed for determining the best depth of wavelet decomposition in order to get an evolutionary spectrum with clear time-dependent trend and high resolution. Secondly, the role of weight function in the estimation of evolutionary spectrum is presented, which shows that Hanning window is more effective than rectangle window in reducing the energy leakage in spectrum analysis. Finally, a series of simulation and application results are given and these results show that the method proposed in this paper is feasible, which can offer a more accurate evolutionary spectrum.

参考文献/References:

[1] Yaffee Robert A,McGee Monnie.Introduction to time series analysis and forecasting[M].New York:Academic Press,2000.101-190.
[2] Carmona Rene,Hwang Wenliang,Torresani Bruno. Practical time-frequency analysis[M].New York:Academic Press,1998.99-218.
[3] Priestley M B.Evolutionary spectrum and non-stationary processes[J].J Roy Statist Soc,Series B,1965,27(2):205-237.
[4] Hammond J K.Evolutionary spectrum in random vibrations[J].J Roy Statist Soc,Series B,1973,35(2):167-188.
[5] Priestley M B.Wavelets and time-dependent spectral analysis[J]. J Time Series Analysis,1996,17(1):85-103.
[6] Jia Minping,Du Ruxu.Evolutionary spectrum based on wavelet transform and application in fault diagnosis[A].In:Proceeding’s of the 11th International Conf on Condition Monitoring and Diagnosis Eng 8-11[C].Australia:Monash University Press,1998(I).463-476.
[7] 朱利民.旋转机械工况监视与故障诊断中若干信号处理方法的研究[D].南京:东南大学机械工程系,1999.

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备注/Memo

备注/Memo:
基金项目: 国家高技术研究发展计划(863计划)资助项目(2001AA423240)、国家自然科学基金资助项目(59875013).
作者简介: 贾民平(1960—),男,博士,教授,博士生导师,mpjia@seu.edu.cn.
更新日期/Last Update: 2002-11-20