Abstract
This paper proposes a novel, wavelet-based algorithm, which by extracting the low-frequency fling makes it possible to automatically correct for baseline shift and re-integrate down to displacement. The algorithm applies a stationary-wavelet transform at a suitable level of decomposition to extract the low frequency fling model in the acceleration time histories. The low frequency, acceleration fling should be as close as possible to the theoretical type A model, which after correction leads to a pulse-type velocity and ramp-like displacement after first and second integration. The wavelet transform essentially decomposes the seismic record using maximally flat filters and these together with a de-noising scheme form the core of this approach, which is to extract the lower and higher frequency sub-band acceleration, velocity and displacement profiles and correct for baseline shift. The correction automatically selects one time point from the low-frequency sub-band and then zeros the acceleration baseline after the fling. This implies pure, translation without any instrument tilts. Estimates of instrument tilt angles are also obtainable from the wavelet transformed time history as well as estimates of signal-to-noise ratios. The acceleration data used in this study is from station TCU068 in the near-fault region of the Chi-Chi, Taiwan, earthquake of 20th September 1999.
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References
Abry P (1997) Ondelettes et turbulence, Multirésolutions, algorithmes de décomposition, invariance d’échelles. Diderot Editeur, Paris
Alexander NA, Chanerley AA, Goorvadoo N (2001) A review of procedures used for the correction of seismic data. In: Proceedings of the eight international conference on civil and structural engineering computing, Vienna, Austria, pp 101–102
Bertero VV, Herrera RA, Mahin SA (1976) Establishment of design earthquakes—evaluation of present methods. ASHRAE Trans 1: 551–580
Bertero VV, Mahin SA, Herrera RA (1978) Aseismic design implications of near-fault San Fernando earthquake records. Earthq Eng Struc Dyn 6: 31–42
Bolt BA (1971) The San Fernando Valley, California, earthquake of February 9 1971: Data on seismic hazards. Bull Seismol Soc Am 61: 501–510
Bolt BA (1975) The San Fernando earthquake, 1971. Magnitudes, aftershocks, and fault dynamics, vol 196, Chap. 21, Calif. Div. of Mines and Geol., Sacramento
Boore DM (2001) Effect of baseline corrections on displacements and response spectra for several recordings of the 1999 Chi-Chi, Taiwan, earthquake. Bull Seismol Soc Am 91: 1199–1211
Boore DM, Bommer JJ (2005) Processing of strong-motion accelerograms: needs, options and consequences. Soil Dyn Earthq Eng 25: 93–115
Chanerley AA, Alexander NA (2002) An approach to seismic correction which includes wavelet de-noising. In: Proceedings of the tenth international conference on civil, structural and environmental engineering computing, Prague, Czech Republic, pp 107–108
Chanerley AA, Alexander NA (2007) Correcting data from an unknown accelerometer using recursive least squares and wavelet de-noising. Comput Struct 85: 1679–1692
Chanerley AA, Alexander NA (2008) Using the total least squares method for seismic correction of recordings from unknown instruments. Adv Eng Softw 39: 849–860
Chen S-M, Loh C-H (2006) Estimates of permanent ground displacements from near-fault, strong-motion acelerograms. In 1st European conference of earthquake engineering & seismology, Geneva
Coifman R, Donoho DL (1995) Translation invariant de-noising, wavelets and statistics, Lecture Notes in statistics, vol 103. Springer, New York, pp 125–150
Debauchies I (1992) Ten lectures on wavelets. SIAM, Philadelphia
Donoho DL (1995) De-noising by soft-thresholding. IEEE Trans Inf Theory 41: 613–627
Freund JE (2003) Mathematical statistics with applications. 7th edn. Prentice Hall, Englewood Cliffs
Graizer VM (2005) Effect of tilt on strong motion data processing. Soil Dyn Earthq Eng 25: 197–204
Halldorsson B, Mavroeidis GP, Papageorgiou AS (2009) Near-fault and far-field strong ground motion simulation for earthquake engineering applications using the specific barrier model. J Struct Eng, ASCE (in press)
Iwan WD, Moser MA, Peng CY (1985) Some observations on strong-motion earthquake measurement using a digital accelerograph. Bull Seismol Soc Am 75: 1225–1246
Lee WHK, Shin TC, Kuo KC, Wu CF (2001) CWB free strong-motion data from the 21st Sept Chi-Chi, Taiwan, Earthquake. BSSA 91:1370–1376. CD ROM
Makris N (1997) Rigidity-plasticity-viscosity: can electrorheological dampers protect base-isolated structures from near-source ground motions?. Earthq Eng Struct Dyn 26: 571–591
Makris N, Black C (2003) Dimensional analysis of inelastic structures subjected to near fault ground motions. Earthquake Engineering Research Center, University of California Report No 2003-05
Trifunac MD (1971) Zero baseline correction of strong-motion accelerograms. Bull Seismol Soc Am 61(5): 1201–1211
Trifunac M, Lee V, Todorovska M (1999) Common problems in automatic digitization of strong motion accelerograms. Soil Dyn Earthq Eng 18: 519–530
Veletsos AS, Newmark NM, Chelepati CV (1965) Deformation spectra for elastic and elastoplastic systems subjected to ground shock and earthquake motions. In: Proceedings of 3rd World conference on earthquake engineering, Wellington, New Zealand, pp 663–682
Wu Y-M, Wu C-F (2007) Approximate recovery of coseismic deformation from Taiwan strong-motion records. J Seismol 11: 159–170
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Chanerley, A.A., Alexander, N.A. Obtaining estimates of the low-frequency ‘fling’, instrument tilts and displacement timeseries using wavelet decomposition. Bull Earthquake Eng 8, 231–255 (2010). https://doi.org/10.1007/s10518-009-9150-5
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DOI: https://doi.org/10.1007/s10518-009-9150-5