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Fractal slope-based seismic wave detection method

Yang Changwei, Zhang Kaiwen, Wu Dongsheng, Zhang Zhifang, Su Ke, Qu Liming and Zhang Liang
Fractal slope-based seismic wave detection method
Bulletin of the Seismological Society of America (July 2023) 113 (6): 2311-2322

Abstract

Automatic P-wave arrival detection is the first task in an earthquake early warning systems. This study proposes a novel detection method for this based on a fractal slope (FS). We improved the calculation method of the fractal dimension to increase the calculation speed and proposed a continuous algorithm. Furthermore, we applied FS in conjunction with the short-term average over the long-term average (STA/LTA), named STA/LTA + FS. We designed orthogonal experiments with different parameters and selected a total of 40,020 sets of seismic waves from the Japanese dataset to test the best parameters. A total of 45,302 sets of seismic waves from the STanford EArthquake dataset and the Chinese dataset were selected to test the generality of the proposed method. The results show that the mean error in detection time of the proposed method is +0.042 s for different datasets. In addition, STA/LTA + FS is robust over a wide range of signal-to-noise ratio, epicentral distance, and magnitude, with the percentage of timing errors below 0.5 s higher than 95%.


ISSN: 0037-1106
EISSN: 1943-3573
Serial Title: Bulletin of the Seismological Society of America
Serial Volume: 113
Serial Issue: 6
Title: Fractal slope-based seismic wave detection method
Affiliation: Southwest Jiaotong University, Chengdu, China
Pages: 2311-2322
Published: 20230703
Text Language: English
Publisher: Seismological Society of America, Berkeley, CA, United States
References: 35
Accession Number: 2023-051836
Categories: Seismology
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. 4 tables
Secondary Affiliation: China Railway Wuhan Bureau Group, Wuhan, CHN, ChinaChina Academy of Railway Sciences, Beijing, CHN, ChinaSouthwest Communication University, Xipu Campus, Chengdu, CHN, China
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2023, American Geosciences Institute. Abstract, Copyright, Seismological Society of America. Reference includes data from GeoScienceWorld, Alexandria, VA, United States
Update Code: 202332
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