Selection of pulse-like ground motions with strong velocity-pulses using moving-average filtering

脉搏(音乐) 选择(遗传算法) 声学 物理 大地测量学 地质学 计算机科学 人工智能 光学 探测器
作者
Zhiwang Chang,Qinhao Gao,Giorgio Monti,Haihong Yu,Shaoyang Yuan
出处
期刊:Soil Dynamics and Earthquake Engineering [Elsevier]
卷期号:164: 107574-107574 被引量:1
标识
DOI:10.1016/j.soildyn.2022.107574
摘要

Pulse-like ground motions with strong velocity-pulses are of special concern for engineers when designing or assessing structures built adjacent to active tectonic faults. This study intends to propose a new approach that makes use of the moving-average filtering (MAF) for selecting ground motions with strong velocity-pulses. Specifically, MAF is employed to filter out the high-frequency content of ground motions, so that relatively smooth waveforms could be extracted and the velocity pulse is easily captured by the peak point method. Then, the pulse-energy relative to the total energy of the ground motion is used as the pulse indicator ( PI ) for selecting pulse-like records. A training set containing 954 components with PGV> 20 cm/s is compiled to determine the PI threshold. The effectiveness of the proposed algorithm is verified by comparisons with previous methods. Finally, by using the proposed method it is shown that pulse-like features can be observed in a couple of orientations, and the identified velocity pulses are seen occurring at sites in the propagation direction of the fault rupture front. • This paper proposes a new algorithm for selecting strong velocity-pulses based on the moving-average filtering (MAF). • Ground motions with PGV >20 cm/s and PI > 0.35 can quantitatively be classified as velocity-pulses. • The velocity-pulses identified by MAF are seen occurring at sites in the propagation direction of the fault rupture front.
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