The Research to the De-Noising Method for the Vibration Signals Based on EEMD

Wei Chang Xu; Tao Tang; Ji Fang Liu; Wei  Huang

doi:10.4028/www.scientific.net/AMM.687-691.3806

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 687-691The Research to the De-Noising Method for the...

The Research to the De-Noising Method for the Vibration Signals Based on EEMD

Abstract:

Dynamical properties of mechanical systems can be obtained with the vibration signals from the systems. However, for the influence of noises, it is difficult to accurately acquire the features. Therefore, de-noising operation is significant for vibration signal in the practical engineering. In order to resolve this problem, the Ensemble Empirical Mode Decomposition (EEMD) method is introduced to try to eliminate noises from the analyzed signal. At first, the theory of the method is illustrated, which included adding white noises, EMD for the signal and calculating the mean of the intrinsic mode function. On this base, the signal which contains several harmonic components with white noise is processed by EEMD. As the result shown, the random noise can be effectively removed; moreover, the harmonic components can be accurately separated. And these improve that the EEMD is an effective method for the de-noising.

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Periodical:

Applied Mechanics and Materials (Volumes 687-691)

Pages:

3806-3808

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.687-691.3806

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Online since:

November 2014

Authors:

Wei Chang Xu*, Tao Tang, Ji Fang Liu, Wei Huang

Keywords:

De-Noising, EEMD, Random Noise, Vibration Signal

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References

[1] Chun-xiang Shi, Qi-feng Luo. Hilbert-huang transform and wavelet analysis of time history signal[J]. Acta Seismologica Sinica . 2003 (4).

DOI: 10.1007/s11589-003-0075-9

Google Scholar

[2] XIA Chen-xi, YANG Jun, LI Shun-bo, Application of Best Wavelet Packet Basis Algorithm in De-noising of Blasting Vibration Signal[J]. Blasting. 2011(3): 4-7.

Google Scholar

[3] ZHANG Feng; MA Shu-xiao; SHI Xian-feng. Algorithm of Vibration Signal Based on Cricular Wiener Filtering[J]. 2014(24). 6: 49-55.

Google Scholar

[4] Huang, N. E., Z. Shen, S. R. Long, M. C. Wu, E. H. Shih, Q. Zheng, C. C. Tung, and H. H. Liu, 1998: The empirical mode decomposition and the Hilbert spectrum for nonlinear and nonstationary time series analysis. Proceedings of the Royal Society A, London, 454, 903–995.

DOI: 10.1098/rspa.1998.0193

Google Scholar

[5] Wu, Z., and N. E. Huang, 2009: Ensemble Empirical Mode Decomposition: a noise-assisted data analysis method. Advances in Adaptive Data Analysis, 1, 1-41.

DOI: 10.1142/s1793536909000047

Google Scholar