An HHT-based method to eliminate short-time strong disturbance from measured signals of bridge

Xue-min Wang , Fang-lin Huang , Guang Ma , Jian-jun Liu

Journal of Central South University ›› 2007, Vol. 14 ›› Issue (6) : 848 -852.

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Journal of Central South University ›› 2007, Vol. 14 ›› Issue (6) : 848 -852. DOI: 10.1007/s11771-007-0161-6
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An HHT-based method to eliminate short-time strong disturbance from measured signals of bridge

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Abstract

According to the characteristic that Hilbert-Huang transform (HHT) can detect abnormity in signals, an HHT-based method to eliminate short-time strong disturbance was proposed. The signal with short-time strong disturbance was decomposed into a series of intrinsic mode functions (IMFs) and a residue by the empirical mode decomposition (EMD). The instantaneous amplitudes and frequencies of each IMF were calculated. And at abnormal section, instantaneous amplitudes and frequencies were fitted according to the data at normal section, replacing the fitted data for the original ones. A new set of IMFs was reconstructed by using the processed instantaneous amplitudes and frequencies. For the residue, abnormal fluctuations could be directly eliminated. And a new signal with the short-time strong disturbance eliminated was reconstructed by superposing all the new IMFs and the residue. The numerical simulation shows that there is a good correlation between the reconstructed signal and the undisturbed signal. The correlation coefficient is equal to 0.999 1. The processing results of the measured strain signal of a bridge with short-time strong disturbance verify the practicability of the method.

Keywords

short-time strong disturbance / Hilbert-Huang transform / empirical mode decomposition / instantaneous amplitude / instantaneous frequency

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Xue-min Wang, Fang-lin Huang, Guang Ma, Jian-jun Liu. An HHT-based method to eliminate short-time strong disturbance from measured signals of bridge. Journal of Central South University, 2007, 14(6): 848-852 DOI:10.1007/s11771-007-0161-6

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References

[1]

HuG.-shu.Digital Signal Processing[M], 1997, Beijing, Tsinghua University Press

[2]

ZhangX.-da.Modern Signal Processing[M], 2002, Beijing, Tsinghua University Press

[3]

DonohoD. L.. De-noising by soft thresholding[J]. IEEE Trans on Information Theory, 1995, 41(3): 613-627

[4]

YangF.-sheng.The Engineering Analysis and Application of Wavelet Transform[M], 1999, Beijing, Science Press

[5]

ZhaoY.-t., WangY., GuoX.-peng.. Wavelet transform based-analysis for coulostatically induced transients denoising[J]. Acta Physico-chimica Sinica, 2005, 21(9): 1017-1021

[6]

HuangN. E., ShenZ., LongS. R., et al.. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proc Royal Society of London Series, 1998, 454: 903-995

[7]

MontesinosM. E., Muñoz-coboJ. L., PérezC.. Hilbert-Huang analysis of BWR neutron detector signals: application to DR calculation and to corrupted signal analysis[J]. Annals of Nuclear Energy, 2003, 30: 715-727

[8]

DingK., ChenJ.-l., SuX.-rong.. Development in vibration signal analysis and processing methods[J]. Journal of Vibration Engineering, 2003, 16(1): 1-10

[9]

HuangN. E., WuM. L., LongS. R., et al.. A confidence limit for the empirical mode decomposition and Hilbert spectral analysis[J]. Proc Royal Society of London Series, 2003, 459: 2317-2345

[10]

ZhongY.-m., QinS.-r., TangB.-ping.. Study on a new transform method for vibration signal[J]. Journal of Vibration Engineering, 2002, 15(2): 233-238

[11]

HuangD.-j., ZhaoJ.-p., SuJ.-lan.. Practical implementation of the Hilbert-Huang transform algorithm[J]. Acta Oceanologica Sinica, 2003, 25(1): 1-11

[12]

HuangN. E., ShenZ., LongS. R.. A new view of nonlinear water waves: the Hilbert spectrum[J]. Annual Review of Fluid Mechanics, 1999, 31: 417-457

[13]

ZhaoJ.-ping.. Study on the effects of abnormal events to empirical mode decomposition method and the removal method for abnormal signal[J]. Journal of Ocean University of Qingdao, 2001, 31(6): 805-814

[14]

HuangF.-l., HeX.-h., ChenZ.-qing.. Structural safety monitoring for Nanjing Yangtze River Bridge[J]. Journal of Central South University of Technology, 2004, 11(3): 332-335

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