Article
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Post-Earthquake Damage Identification of the Buildings with LMSST
Version 1
: Received: 22 May 2023 / Approved: 23 May 2023 / Online: 23 May 2023 (10:55:32 CEST)
A peer-reviewed article of this Preprint also exists.
Kumar, R.; Singh, V.; Ismail, M. Post-Earthquake Damage Identification of Buildings with LMSST. Buildings 2023, 13, 1614. Kumar, R.; Singh, V.; Ismail, M. Post-Earthquake Damage Identification of Buildings with LMSST. Buildings 2023, 13, 1614.
Abstract
The natural frequency of buildings decreases during a strong-motion earthquake, and the structure loses its stiffness. As a result, understanding the damaging process in the structure owing to changes in structural properties is critical during a seismic excitation. The time-frequency technique can detect the damaged building’s time-varying frequency contents. Wigner distributions (WD), Wigner-Ville distributions (WVD), pseudo-Wigner-Ville distributions (PWVD), smoothed pseudo-Wigner-Ville distributions (SPWVD), and synchrosqueezing transforms (SST) have all become popular in recent years for a variety of earthquake engineering applications, including building damage detection. This study proposes the local maximum synchrosqueezing transform (LMSST) for detecting frequency shifts in buildings during strong earthquakes. The data presented in the research show that the suggested method outperforms as compared to the conventional time-frequency methods for detecting frequency shifting in earthquake-damaged structures.
Keywords
Cross-term; Fourier transform; Frequency shifting; Time-frequency method; Natural frequency
Subject
Engineering, Safety, Risk, Reliability and Quality
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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