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Título del libro: Proceedings Of The 17th International Conference On Soil Mechanics And Geotechnical Engineering: The Academia And Practice Of Geotechnical Engineering
Título del capítulo: Treatment of geoseismic data as a non-stationary process

Autores UNAM:
SILVIA RAQUEL GARCIA BENITEZ; MIGUEL PEDRO ROMO ORGANISTA;

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Autores externos:

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Idioma:
Inglés

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Año de publicación:
2009

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Palabras clave:

Data processing techniques; Earthquake recording; Empirical Mode Decomposition; Frequency characteristic; Hilbert Huang transforms; Hilbert transformations; Localized features; Mexico City; Motion characteristics; Nonlinear soil behavior; Nonstationary; Nonstationary process; Oscillation system; Seismic data analysis; Seismic load; Site amplification; Soft soils; Time variations; Time-varying frequency; Data processing; Fourier analysis; Geotechnical engineering; Seismology; Soil mechanics; Signal processing

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Resumen:

The traditional Fourier-spectra-based tools do not adequately capture the evolutionary and localized features of the natural-systems responses. When these systems are subjected to seismic loads the Fourier analysis may misinterpret the information due to the timevariation of frequency characteristics in non-stationary processes. This study explores the use of the Hilbert-Huang Transform for analyzing earthquake recordings and the associated dynamic-soil behavior. The HHT, integrated by the Empirical Mode Decomposition and the Hilbert Transformation, is an empirical based data-analysis method with an adaptive basis of expansion that can produce physically meaningful representations of data from nonlinear and non-stationary processes. Hilbert-Huang Transform enables engineers to analyze non-stationary oscillation systems and to obtain more detailed intensity descriptions on time-varying frequency diagrams. HHT is used in this work to examine responses of soft-soils deposits in Mexico City. The results indicate that the proposed methodology is able to extract some motion characteristics useful in geoseismic studies which are not properly seen when are employed conventional data processing techniques. © 2009 IOS Press.

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Entidades citadas de la UNAM:

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Fuente:


ISBN:
9781607500315
Editorial:
IOS Press

Tipo de producto:
Conference Paper

DOI:
10.3233/978-1-60750-031-5-2723