四种震相自动检测技术在前震探测应用中的对比研究

A Comparative Study of Four Automatic Phase Detection Techniques in the Application of Foreshock Detection

摘要:

采用短长时窗比、多频带滤波、深度学习和模板匹配过滤四种地震信号自动检测方法,分别对2010年4月14日青海玉树7.1级、2013年8月31日云南香格里拉、德钦、四川得荣交界5.9级和2014年2月12日新疆于田7.3级地震3次具有明显前震信号的地震事件发生前,震中距最近的玉树台、中甸台和于田台记录到的数十小时连续波形数据进行处理,探索四种自动拾取震相算法在前震信号探测方面的应用效果,补充了前震活动信息。通过对比不同检测方法检测结果的漏检率和误检率,提出利用深度学习检测结果对短长时窗比、多频带滤波检测结果进行补充验证,结果作为模版进行匹配过滤,同时,充分利用深度学习模型广义震相检测 (GPD) 对P波和S波震相自动识别,有助于完善前震震相信息。

Abstract:

This study applies four automatic seismic signal detection methods—short-long time window ratio,multi-band filtering,deep learning,and template matching filtering—to continuous waveform data recorded by the YUS,ZOD,and YUT stations,which are nearest to the epicenters of three major seismic events with well-documented foreshock activity. These events include the M7.1 Yushu earthquake in Qinghai on April 14,2010;the M5.9 earthquake at the junction of Shangri-La, Deqin,and Derong in Yunnan on August 31,2013;and the M7.3 Yutian earthquake in Xinjiang on February 12,2014. The study evaluates the effectiveness of each method in detecting foreshock signals and enhancing foreshock phase information. By comparing false negative and false positive rates,we propose using deep learning results to validate and supplement detections from the short-long time window ratio and multi-band filtering methods. These improved detections are then used as templates for matching and filtering. Additionally,the Generalized Phase Detection (GPD) algorithm is employed for the automatic identification of P and S phases,further enhancing the accuracy and completeness of foreshock phase identification.