Deep learning for P-wave arrival picking in earthquake early warning

作     者：Wang Yanwei Li Xiaojun Wang Zifa Shi Jianping Bao Enhe Wang Yanwei;Li Xiaojun;Wang Zifa;Shi Jianping;Bao Enhe

作者机构：College of Architecture and Civil EngineeringBeijing University of TechnologyBeijing 100022China Guangxi Key Laboratory of Geomechanics and Geotechnical EngineeringGuilin University of TechnologyGuilin 541004China College of Architecture and Civil EngineeringHenan UniversityKaifeng 475004China Institute of Engineering MechanicsChina Earthquake AdministrationHarbin 150080China China Academy of Railway SciencesChina Railway CorporationBeijing 100081China 

出 版 物：《Earthquake Engineering and Engineering Vibration》 (地震工程与工程振动（英文刊）)

年 卷 期：2021年第20卷第2期

页      面：391-402页

核心收录：

学科分类：070801[理学-固体地球物理学] 07[理学] 0708[理学-地球物理学] 

基　　金：National Natural Science Foundation of China under Grant Nos.51968016 and 5197083806 the Guangxi Innovation Driven Development Project(Science and Technology Major Project,Grant No.Guike AA18118008) 

主　　题：P-wave arrival convolution neural network deep learning earthquake early warning 

摘      要：Fast and accurate P-wave arrival picking significantly affects the performance of earthquake early warning(EEW)*** P-wave picking algorithms used in EEW have encountered problems of falsely picking up noise,missing P-waves and inaccurate P-wave arrival *** address these issues,an automatic algorithm based on the convolution neural network(DPick)was developed,and trained with a moderate number of data sets of 17,717 *** to the widely used approach of the short-term average/long-term average of signal characteristic function(STA/LTA),DPick is 1.6 times less likely to detect noise as a P-wave,and 76 times less likely to miss *** terms of estimating P-wave arrival time,when the detection task is completed within 1 s,DPick′s detection occurrence is 7.4 times that of STA/LTA in the 0.05 s error band,and 1.6 times when the error band is 0.10 *** verified that the proposed method has the potential for wide applications in EEW.