A New View of Mode Mixing Phenomenon

Yan Rui Du; Li Hui Chen; Jin He

doi:10.4028/www.scientific.net/AMM.532.134

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 532A New View of Mode Mixing Phenomenon

A New View of Mode Mixing Phenomenon

Abstract:

The EMD method is to separate a composite signal into simple oscillatory mode functions called intrinsic mode functions (IMFs) which are generated by a sifting process. IMFs can lose their physical meaning when mode mixing phenomenon occurs. For mode mixing, do not have an exact definition by now, the purpose of this paper is to analysis the mode mixing phenomenon in the EMD method and to advance a new view of mode mixing. By the model and the simulations, we point out that cutoff frequency and the extrema rate of signal is the fundamental reason of mode mixing.

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Periodical:

Applied Mechanics and Materials (Volume 532)

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134-137

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.532.134

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Online since:

February 2014

Authors:

Yan Rui Du, Li Hui Chen*, Jin He

Keywords:

EMD Method, HHT, Mode Mixing, Time Frequency

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References

[1] Huang, N.E., Shen, Z., Long, S. R. et al., The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis, Proc. R. Soc. Lond. A, 1998, 454: 899.

Google Scholar

[2] Huang, N.E., Shen, Z., Long, S. R., A new view of nonlinear water waves: the Hilbert spectrum, Annu. Rev. Fluid Mech., 1999, 31: 417.

DOI: 10.1146/annurev.fluid.31.1.417

Google Scholar

[3] N.E. Huang, Z. Shen, and S.R. Long, A new view of nonlinear water waves: The Hilbert Spectrum, Annu. Rev. Fluid Mech., vol. 31, pp.417-457, (1999).

DOI: 10.1146/annurev.fluid.31.1.417

Google Scholar

[4] Farge, M., Wavelet transforms and their applications to turbulence, Ann. Rev. fluid Mech., 1992, 24: 395.

DOI: 10.1146/annurev.fl.24.010192.002143

Google Scholar

[5] Y.C. Gao, G.T. Ge, Z.Y. Sheng, and E.F. Sang, Analysis and solution to the mode mixing phenomenon in EMD, in Cong. Image Signal Process. 2008, pp.223-227.

DOI: 10.1109/cisp.2008.193

Google Scholar

[6] P. Flandrin, G. Rilling, and P. Goncalves, Empirical mode decomposition as a filter bank, IEEE Signal Process. Lett., vol. 11, no. 2, pt. 1, pp.112-114, Feb. (2004).

DOI: 10.1109/lsp.2003.821662

Google Scholar

[7] Helong Li, Lihua Yang. The study of the intermittency test filtering character of Hilbert-Huang transform. Mathematics and Computers in Simulation. 2005, 70, 22-32.

DOI: 10.1016/j.matcom.2005.03.020

Google Scholar