Feature extraction from seismic accelerograms is a key issue in characterization of earthquake damage in structures. Until today, a number of effective classical parameters such as peak ground acceleration (PGA) and Arias intensity have been proposed for analyzing the earthquake motion records. The aim of this paper is to search for new crucial characteristic seismic parameters which provide information pertinent to the damage indicators of the structures. The first proposed parameter is the maximum amplitude (A HHT max ) and the second is the mean amplitude (A HHT mean ). Emphasis of our work has been placed on the use of the Hilbert-Huang transform (HHT). A set of 13 natural accelerograms from worldwide well-known sites with strong seismic activity have been used. The HHT has been applied to the nonlinear and non-stationary data (earthquake recordings). Each complex seismic accelerogram is decomposed into several simple components called intrinsic mode functions (IMFs). Using the IMFs a three-dimensional time-frequency distribution of earthquake excitation is computed and two new seismic parameters are proposed and evaluated. After the numerical computation of all the seismic parameters (classical and proposed), nonlinear dynamic analysis is carried out to provide the post-seismic damage status of the structure under study. Two structural damage indices are utilized and the degree of interrelation among them and the seismic parameters is provided by correlation coefficients. Furthermore, two different reinforced concrete structures are examined. Results indicate the high correlation of the new seismic parameters (A HHT max , A HHT mean ) with the damage indices and confirm that HHT is a promising tool for extracting information to characterize damage in structures.
The Hilbert–Huang transform is used to generate artificial seismic signals compatible with the acceleration spectra of natural seismic records. Artificial spectrum-compatible accelerograms are utilized instead of natural earthquake records for the dynamic response analysis of many critical structures such as hospitals, bridges, and power plants. The realistic estimation of the seismic response of structures involves nonlinear dynamic analysis. Moreover, it requires seismic accelerograms representative of the actual ground acceleration time histories expected at the site of interest. Unfortunately, not many actual records of different seismic intensities are available for many regions. In addition, a large number of seismic accelerograms are required to perform a series of nonlinear dynamic analyses for a reliable statistical investigation of the structural behavior under earthquake excitation. These are the main motivations for generating artificial spectrum-compatible seismic accelerograms and could be useful in earthquake engineering for dynamic analysis and design of buildings.
According to the proposed method, a single natural earthquake record is deconstructed into amplitude and frequency components using the Hilbert–Huang transform. The proposed method is illustrated by studying 20 natural seismic records with different characteristics such as different frequency content, amplitude, and duration. Experimental results reveal the efficiency of the proposed method in comparison with well-established and industrial methods in the literature.
In this work, a new methodology for generating spectrum-compatible accelerograms is presented. The proposed methodology considers the non-stationary and non-linear characteristics of seismic signals and utilizes the Hilbert–Huang transform (HHT) to analyse them. The two reported drawbacks of HHT, i.e. the mode mixing phenomenon and the end effects issue, are resolved through the proposed methodology. More specifically, the advantages of the recently introduced complementary ensemble empirical mode decomposition (CEEMD) are exploited in order to eliminate the mode mixing phenomenon. Moreover, the application of the proposed method only to the strong motion duration of the seismic signal assists to overcome the end effects issue. Thirty natural seismic records of different characteristics, such as frequency content, amplitude and duration, are employed as initial seed signals to demonstrate the proposed method. To illustrate the effectiveness of the proposed technique, comparisons with three established methods for generating spectrum-compatible seismic accelerograms are also provided.
In this paper an efficient classification system in the area of earthquake engineering is reported. The proposed method uses a set of artificial accelerograms to examine several types of damages in specific structures. With the use of seismic accelerograms, a set of twenty seismic parameters have been extracted to describe earthquakes. Previous studies based on artificial neural networks and neuro-fuzzy classification systems present satisfactory classification results in different types of earthquake damages. In this approach a genetic algorithm (GA) was used to find the optimal feature subset of the seismic parameters that minimizes the computational cost and maximizes the classification performance. Experimental results indicate that the use of the GA was able to classify the structural damages with classification rates up to 92%.
Part 11: Simulations and Fuzzy ModelingInternational audienceA new efficient approach for generating spectrum-compatible seismic accelerograms is proposed. It is based on the Hilbert-Huang Transform (HHT); one natural seismic accelerogram is decomposed into frequency and amplitude components. The components are appropriately modified to synthesize the artificial seismic accelerogram that appears to have compatible acceleration spectrum with the natural seismic accelerogram. The HHT is an adaptive signal processing technique for analyzing nonlinear and non-stationary data such as seismic accelerograms. With HHT a seismic accelerogram is decomposed into a finite and small set of components. These components have well defined instantaneous frequencies, estimated by the first derivative of the phase of the analytic signal. The method is tested using twenty natural seismic records and a comparison with two established methodologies is provided
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