A New Method for Calculating Earthquake Characteristics and Nonlinear Spectra Using Wavelet Theory

Document Type: Regular Paper

Authors

Department of Civil Engineering, Shahrekord University, Shahrekord, Iran

Abstract

In the present study using the wavelet theory (WT) and later the nonlinear spectrum response of the acceleration (NSRA) resulted in estimating a strong earthquake record for the structure to a degree of freedom. WT was used in order to estimate the acceleration of earthquake mapping with equal sampling method (WTESM). Therefore, at first, the acceleration recorded in an earthquake using WTESM was studied in 5 levels. And then for calculating the strong ground parameters (SGP) and the NSRA of the structure the filtered wave was used instead of using the main earthquake record (MER). The wavelet stages result in a more lenient filtered wave and it is better for calculating SGP and NSR because the noise is filtered. The method suggested for a large number of earthquakes was used and the results are detailed in the case of Kermanshah earthquake. Results show that in case of using WTESM, SGP error estimation would be less than 2% and the calculation error for NSRA would be less than 11%.

Keywords

Main Subjects


[1] Boore, D. M. (1983). “Stochastic simulation of high-frequency ground motions based on seismological models of the radiated spectra.” Bulletin of the Seismological Society of America, vol. 73, pp. 1865-1894.

[2] Yaghmaei-Sabegh, S., Ruiz-García, J. (2016). “Nonlinear response analysis of SDOF systems subjected to doublet earthquake ground motions: A case study on 2012 Varzaghan–Ahar” events. Engineering Structures, vol. 110, pp. 281-292.

[3] Rathje, E. M., Abrahamson, N. A., Bray, J. D. (1998). “Simplified frequency content estimates of earthquake ground motions. Journal of Geotechnical and Geoenvironmental Engineering.” Vol. 124, pp. 150-159.

[4] Heidari, A., Salajegheh, E. (2008). “Wavelet analysis for processing of earthquake records.” Asian Journal of Civil Engineering, 9(5), 513-524

[5] Salajegheh, E., Heidari, A. (2005a). “Optimum design of structures against earthquake by wavelet neural network and filter banks.” Earthquake engineering & structural dynamics, vol. 34(1), pp. 67-82.

[6] Salajegheh, E., Heidari, A. (2005b). “Time history dynamic analysis of structures using filter banks and wavelet transforms.” Computers & structures, vol. 83(1), pp. 53-68.

[7] Salajegheh, E., Gholizadeh, S., Torkzadeh, P. (2007). “Optimal desigin of structures with frequency constraints using wavelet back propagation neural.” Asian Journal of Civil Engineering, Vol. 8, pp. 97-111.

[8] Gholizadeh, S., Samavati, O. A. (2011). “Structural optimization by wavelet transforms and neural networks.” Applied Mathematical Modelling, Vol. 35(2), pp. 915-929.

[9] Salajegheh, E., Gholizadeh, S. (2012). “Structural seismic optimization using metaheuristics and neural networks: a review.” Computational Technology Reviews, Vol. 5(1), pp. 109-137.

[10] Pnevmatikos, N. G., Hatzigeorgiou, G. D. (2017). “Damage detection of framed structures subjected to earthquake excitation using discrete wavelet analysis” Bulletin of Earthquake Engineering, vol. 15, pp. 227-248.

[11] Heidari, A., Raeisi, J. (2018). “Optimum Design of Structures Against earthquake by Simulated Annealing Using Wavelet Transform.” Soft Computing in Civil Engineering, doi: 10.22115/scce.2018.125682.1055

[12] Chopra, A.K. (1995). “Dynamics of Structures” vol. 3. Prentice Hall, New Jersey.

[13] Paz, M. (2012). “Structural dynamics: theory and computation.” Springer Science & Business Media.

[14] Heidari, A., Raeisi, J., Kamgar, R. (2018). “APPLICATION OF WAVELET THEORY IN DETERMINING OF STRONG GROUND MOTION PARAMETERS.” International Journal of Optimization in Civil Engineering, vol. , pp. 103-115.

[15] Raeisi, J. (2017). “Investigation of strong ground motion using a wavelet theory for hydraulic structure in far fault.” MSc Thesis, Department of Civil Engineering, Shahrekord University, Iran. Shahrekord, Iran.

[16] Pahlavan-Sadegh, S. (2018). “Approximation of nonlinear m response spectrum of hydraulic structures using wavelet theory.” MSc Thesis, Department of Civil Engineering, Shahrekord University, Shahrekord, Iran.

[17] Heidari, A., Raeisi, J., Kamgar., R., “The application of wavelet theory with denoising to estimate the parameters of earthquake”. Scientia Iranica, Accepted Manuscript, 2019. DOI: 10.24200/SCI.2019.50675.1815

[18] Heidari, A., Pahlavan sadegh, S., Raeisi., J., “Investigating the effect of soil type on non-linear response spectrum using wavelet theory”, International Journal of Civil Engineering, Accepted Manuscript, 2019, https://doi.org/10.1007/s40999-019-00394-6

[19] Daubechies, I. (1990). “The wavelet transform, time-frequency localization and signal analysis.” IEEE transactions on information theory, vol. 36, pp. 961-1005.

[20] Naderpour, H., Fakharian, P., (2016), “A Synthesis of Peak Picking Method and Wavelet Packet Transform for Structural Modal Identification”, KSCE Journal of Civil Engineering, Volume 20, Issue 7, pp 2859–2867; DOI: 10.1007/s12205-016-0523-4.

[21] Rioul O, Vetterli M. 1991. “Wavelets and signal processing.” IEEE special magazine, pp. 14–38.

[22] Woods, J. W. (1991). “Subband image coding.” Kluwer Academic Publishers, Dordrecht.

[23] Arias, A. (1970). “Measure of earthquake intensity”, Massachusetts Inst. of Tech. Cambridge. Univ. of Chile, Santiago de Chile.

[24] Park, Y. J., Ang, A. H. S., Wen, Y. K. (1985). “Seismic damage analysis of reinforced concrete buildings.” Journal of Structural Engineering, vol. 111, pp. 740-757.

[25] Kramer, S. L. (1996). “Geotechnical Earthquake Engineering.” Prentice Hall. New York.

[26] Housner GW. (1975). “Measures of severity of earthquake ground shaking.” In: Proceedings of the first US national conference on earthquake engineering, Ann Arbor, MI.