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Tytuł artykułu

Method for Identifying Micro-seismic P-Arrival by Time-frequency Analysis Using Intrinsic Time-Scale Decomposition

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Języki publikacji
EN
Abstrakty
EN
A method to identify the P-arrival of microseismic signals is proposed in this work, based on the algorithm of intrinsic timescale decomposition (ITD). Using the results of ITD decomposition of observed data, information of instantaneous amplitude and frequency can be determined. The improved ratio function of short-time average over long-time average and the information of instantaneous frequency are applied to the time-frequency-energy denoised signal for picking the P-arrival of the microseismic signal. We compared the proposed method with the wavelet transform method based on the denoised signal resulting from the best basis wavelet packet transform and the single-scale reconstruction of the wavelet transform. The comparison results showed that the new method is more effective and reliable for identifying P-arrivals of microseismic signals.
Czasopismo
Rocznik
Strony
468--485
Opis fizyczny
Bibliogr. 17 poz., rys., tab., wykr.
Twórcy
autor
  • Department of Civil Engineering, North China Institute of Science and Technology, Sanhe-Hebei, China
autor
  • Department of Civil Engineering, North China Institute of Science and Technology, Sanhe-Hebei, China
Bibliografia
  • [1] Allen, R. (1978), Automatic earthquake recognition and timing from single traces, Bull. Seismol. Soc. Am. 68, 5, 1521-1532.
  • [3] Allen, R. (1982), Automatic phase pickers: Their present use and future prospects, Bull. Seismol. Soc. Am. 72, 6B, 225-242.
  • [4] Baer, M., and U. Kradolfer (1987), An automatic phase picker for local and teleseismic events, Bull. Seismol. Soc. Am. 77, 4, 1437-1445.
  • [5] Bai, C., and B.L.N. Kennett (2000), Automatic phase-detection and identification by full use of a single three-component broadband seismogram, Bull. Seismol. Soc. Am. 90, 1, 187-198, DOI: 10.1785/0119990070.
  • [6] Dai, H., and C. MacBeth (1995), Automatic picking of seismic arrivals in local earthquake data using artificial neural network, Geophys. J. Int. 120, 3, 758-774, DOI:10.1111/j.1365-246X.1995.tb01851.x.
  • [7] Daubechies, I. (1992), Ten Lectures on Wavelets, SIAM, Philadelphia, 357 pp. Earle, P.S., and P.M. Shearer (1994), Characterization of global seismograms using an automatic-picking algorithm, Bull. Seismol. Soc. Am. 84, 2, 366-376.
  • [8] Frei, M.G., and I. Osorio (2007), Intrinsic time-scale decomposition: timefrequency energy analysis and real-time filtering of non-stationary signals, Proc. R. Soc. A 463, 321-342, DOI: 10.1098/rspa.2006.1761.
  • [9] Galiana-Merino, J.J., J. Rosa-Herranz, J. Giner, S. Molina, and F. Botella (2003), De-noising of short-period seismograms by wavelet packet transform, Bull. Seismol. Soc. Am. 93, 6, 2554-2562, DOI: 10.1785/0120010133.
  • [10] Galiana-Merino, J.J., J. Rosa-Herranz, P. Jáuregui, S. Molina, and J. Giner (2007), Wavelet transform methods for azimuth estimation in local threecomponent seismograms, Bull. Seismol. Soc. Am. 97, 3, 793-803, DOI:10.1785/0120050225.
  • [11] Liu, J.S., Y. Wang, and Z.X. Yao (2013), On micro-seismic first arrival identification: A case study, Chin. J. Geophys. 56, 5, 1660-1666, DOI: 10.6038/cjg20130523.
  • [12] Ma, Q. (2008), Study and application on earthquake early warning, Ph.D. Thesis, Institute of Engineering Mechanics, China Earthquake Administration, Harbin, China (in Chinese).
  • [13] McEvilly, T.V., and E.L. Majer (1982), ASP: An Automated Seismic Processor for microearthquake networks, Bull. Seismol. Soc. Am. 72, 1, 303-325.
  • [14] Ye, G.X., F.X. Jiang, and S.H. Yang (2008), Possibility of automatically pickingn first arrival of microseismic wave by energy eigenvalue method, Chin. J. Geophys. 51, 5, 1574-1581.
  • [15] Zhang, H., C. Thurber, and C. Rowe (2003), Automatic P-wave arrival detection and picking with multiscale wavelet analysis for single-component recordings, Bull. Seismol. Soc. Am. 93, 5, 1904-1912, DOI: 10.1785/0120020241.
  • [16] Zhang, R.H., D.C. Lin, and L. Qiao (2011), Application of the optimum wavelet packet transform in de-noising seism signals, J. Seismol. Res. 34, 3, 358-364.
  • [17] Zhang, R.H., H.W. Qi, D.C. Lin, and L. Qiao (2012), Micro-seismic signal denoising based on intrinsic time-scale decomposition algorithm, Safety Coal Min. 43, 3, 164-168.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-63a62915-3c61-41c4-b03b-76a4e4b2145c
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