On the evolutionary characteristics of the acceleration records generated from linear time-variant systems

This paper discusses the time-varying characteristics of the output signals resulted from Linear Time Variant (LTV) systems using level-crossing properties. These systems, used for generating synthetic records based on a target record, contain two identification processes: 1) amplitude modulating fu...

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Bibliographic Details
Published inScientia Iranica Vol. 24; no. 6; pp. 2817 - 2831
Main Authors Waezi, Z, Rofooei, F R
Format Journal Article
LanguageEnglish
Published Tehran Sharif University of Technology 01.11.2017
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ISSN1026-3098
2345-3605
DOI10.24200/sci.2017.4254

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Summary:This paper discusses the time-varying characteristics of the output signals resulted from Linear Time Variant (LTV) systems using level-crossing properties. These systems, used for generating synthetic records based on a target record, contain two identification processes: 1) amplitude modulating function; and 2) time-varying Impulse Response Function (IRF) parameters. To track the IRF parameters efficiently, the zero-crossing and positive minima/negative maxima cumulative curves are usually utilized as the measures of the instantaneous spectral power. Using spectral moments, analytic relations for zero-crossing and positive minima/negative maxima cumulative count are developed with respect to the IRF's evolutionary power spectrum. In order to investigate the low-frequency components of the output records efficiently, the zero-crossing rate of the velocity and the displacement records are tracked and rigorous analytic equations for their descriptions are developed. Some of the issues concerning application of the developed equations are explored using two LVT models, and the limitations of the proposed procedures are explained. Through introduction of new compatibility measures, the necessity of implementing Monte Carlo simulations would no longer be needed, and it would be possible to generate synthetic acceleration records with desirable evolutionary characteristics with much shorter computation time.
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ISSN:1026-3098
2345-3605
DOI:10.24200/sci.2017.4254