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一种基于EMD的振动信号时频分析新方法研究 被引量:20

STUDY ON THE METHOD OF EMD-BASED VIBRATION SIGNAL TIME-FREQUENCY ANALYSIS
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摘要 基于经验模态分解(Empirical Mode Decomposition,EMD)的希尔伯特变换(Hilbert Transformation,HT),是先把一列时间序列数据通过经验模态分解成本征模函数(Intrinsic Mode Function,IMF),然后经过希尔伯特变换获得瞬时频率的信号处理方法。针对HT求瞬时频率的不足,提出了把IMF分解成包络和纯调频信号,然后通过对纯调频信号进行反余弦求瞬时频率的新方法。通过对非线性仿真信号研究表明,该方法是有效的。把该方法应用于转子横向裂纹的时频分析,表明能把横向裂纹转子的扭振所形成的相位调制现象检测出来,获得了良好的效果。仿真和实测信号的分析结果说明,用新方法对振动信号进行时频分析是有效的。该研究成果能广泛地用于信号时频分析领域。 A new method for identifying the instantaneous frequency with empirical mode decomposition (EMD) based Hilbert transformation (HT) was proposed. Through EMD,the time series data are seperated into intrinsic mode functions (IMFs), and then each IMF is decomposed to an envelope signal and a frequency modulated signal. The instantaneous frequency can be derived from the frequency modulated signal using arccosine function. A simulated nonlinear signal was processed using the method and the results show the validity of the technology. A deep crack rotor vibration signal was dealt with as an example and the results show that the method is helpful to detect the phase-modulation caused by torsional vibration of the rotor.
出处 《振动与冲击》 EI CSCD 北大核心 2008年第8期71-73,154,共4页 Journal of Vibration and Shock
基金 国家自然科学基金资助项目(50675194) 宁波市自然科学基金资助项目(2007A610014)
关键词 振动信号 经验模态分解(EMD) 时频分析 vibration signal empirical mode decomposition(EMD) time-frequency analysis
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参考文献8

  • 1Norden E. Huang, Zheng Shen, Steven R. Long, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis [ C ]. Proc. Royal Society. Lond : 1998:903-995.
  • 2Better algorithms for analyzing nonlinear, nonstationary data [ EB/OL]. http://tco, gsfc. nasa. gov, 2005 -07 - 10.
  • 3Loh CH, et al. Application of the empirical mode decomposition-Hilbert spectrum method to identify near-fault ground-motion characteristics and structural responses [ J ]. Bulletin Of The Seismological Society Of America,2001,91 : 1339-1357.
  • 4Vasudevan K, et al. Empirical mode skeletonization of deep crustal seismic data : Theory and applications [ J ]. Journal Of Geophysical Research-Solid Earth ,2000,105:7845-7856.
  • 5Echeverria J C, et al. Application of empirical mode decomposition to heart rate variability analysis [ J ]. Medical & Biological Engineering & Computing,2001,39:471-479.
  • 6杨世锡,胡劲松,吴昭同,严拱标.旋转机械振动信号基于EMD的希尔伯特变换和小波变换时频分析比较[J].中国电机工程学报,2003,23(6):102-107. 被引量:182
  • 7胡劲松,杨世锡,吴昭同,严拱标.基于EMD和HT的旋转机械振动信号时频分析[J].振动.测试与诊断,2004,24(2):106-110. 被引量:48
  • 8Boashiash, B. Estimating and interpreting the instantaneous frequency of a signal-part l[J]. Proc. IEEE,1992(80) :520-538.

二级参考文献12

  • 1Vasudevan K, Cook F A. Empirical mode skeletonization of deep crustal seismic data: theory and applications. Journal of Geophysical Research-Solid Earth,2000, (105):7845~7856
  • 2Echeverria J C, Crowe J A, Woolfson M S, et al. Application of empirical mode decomposition to heart rate variability analysis. Medical & Biological Engineering &Computing, 2001, (39) :471~479
  • 3Norden E, Huang Z S, Steven R L, et al. The empirical mode decomposition and the non-stationary time series analysis. In: Proc. R. Soc. Lond, 1998. 903~995
  • 4Better algorithms for analyzing nonlinear, nonstationary data. http:∥tco. gsfc. nasa. gov
  • 5Loh C H, Wu T C, Huang N E. Application of the empirical mode decomposition-Hilbert spectrum method to identify near-fault ground-motion characteristics and structural responses. Bulletin of the Seismological Society of America, 2001, (91) :1339~1357
  • 6Huang N E, Shen Zheng, Long S R, et ol. The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis[J]. Proc. R. Soc. Lond. 1998, A:903-995.
  • 7Better Algorithms for Analyzing Nonlineat[EB/OL], Nonstationary Data.http://tco.gsfc.nasa.gov,.
  • 8CH Loh, Application of the empirical mode decomposition-Hilbert spectrum method to identify near-fault ground-motion charact-eristics and structural responses[J]. Bulletin of the Seismological Society of America, 2001, 91: 1339-1357.
  • 9Vasudevan K. Empirical mode skeletonization of deep crustal seismic data: Theory and applications[J]. Journal of Geophysical Research-Solid Earth, 2000, 105: 7845-7856.
  • 10Echeverria J C, Application of empirical mode decomposition to heart rate variability analysis[J], Medical & Biological Engneering & Computing, 2001, 39:471-479.

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