Modeling of Indian strong motion data using Empirical Mode Decomposition technique

In India, the frequency of occurrence of earthquakes is more, especially in Himalaya, northeast India and Gujarat region. Therefore it becomes essential to estimate the seismic inputs for such earthquakes to reduce the structural damage. From engineering point of view, the most sought-after data is the strong motion accelerograms (SMA), recorded in the places where earthquake has occurred. The article analyzes the Indian strong motion records of past earthquakes by empirical mode decomposition (EMD) technique and in-turn presents few strong ground motion parameters, which finds its use in the simulation of artificial ground motions. The recorded earthquake acceleration time histories are decomposed into a finite number of empirical modes of oscillation. The instantaneous frequency and amplitude of these modes and evolutionary power spectral density (PSD) is estimated from the Hilbert Huang transform (HHT). Strong motion parameters such as spectral and temporal centroid, spectral and temporal standard deviation, instantaneous power, Arias intensity, correlation coefficient of frequency and time are derived from the evolutionary PSD. The variation of these parameters with magnitude and distance of the recording station has been examined. Empirical equations to estimate these ground motion parameters are derived from the strong motion data by regression analysis. These equations can be used by engineers to estimate the design ground motion. KeywordsEvolutionary Power Spectral Density; Empirical Mode Decomposition; Hilbert Huang Transform; Ground motion prediction equations; design ground motion