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Research on Seismic Acceleration Waveform Reproduction Based on Time-Frequency Hybrid Integration Algorithm

Authors :
Ying-Qing Guo
Han-Qi Zhang
Yi-Na Wang
Jun Dai
Source :
IEEE Access, Vol 10, Pp 94887-94897 (2022)
Publication Year :
2022
Publisher :
IEEE, 2022.

Abstract

For the quadratic integration of seismic acceleration signal with noise and unknown initial velocity and displacement, the obtained displacement signal has serious trend error, which leads to the problem that the electrodynamic seismic simulation shaker under displacement control mode cannot accurately reproduce the seismic wave. This paper proposes the time-frequency hybrid integration algorithm based on time domain and frequency domain integration characteristics. The algorithm mainly includes two steps. The first step is to use the improved low-frequency attenuation algorithm to integrate the seismic acceleration for the first time in the frequency domain to obtain the corresponding velocity signal. The second step is to integrate the velocity signal directly in the time domain and combine it with the removal of the constant and linear terms algorithm to obtain the corresponding displacement signal. The accuracy and effectiveness of the algorithm are verified by numerical analysis and shaking table test. The results show that compared with the traditional hybrid integral algorithm, the performance improvement rates of displacement peak error and absolute error of the proposed time-frequency hybrid integral algorithm are 31.75% and 26.01%, respectively, and the accuracy of acceleration waveform reproduction is improved by 27.29%. Furthermore, when using this algorithm for the shaking table test of the seismic acceleration signal, the maximum peak error rate is only 4.92%. Therefore, this algorithm can effectively suppress the baseline drift and error accumulation caused by low-frequency noise and unknown initial state to realize the accurate reproduction of the acceleration waveform of the seismic simulation shaking table.

Details

Language :
English
ISSN :
21693536
Volume :
10
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.b653f07e905a498fb32723e8710d02c9
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2022.3202969