Online detection and location estimation of earthquake events using continuous wavelet transform

S. Saha, D. Mukherjee, S. Mukhopadhyay
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引用次数: 3

Abstract

Online detection of onset of an earthquake and estimation of its epicenter is of paramount importance. Manual analysis is still the final resort to characterize a seismic event and various seismic phases (waves) associated with it. In this paper, an attempt has been made at multi-scale modeling of seismic array signal to automate detection of event onset, estimation of event location and automatic/ unsupervised report generation. The technique works in wavelet domain, exploiting the non-stationary property of seismic waves. After an event is detected, a section of the data around the P onset is used to calculate the azimuth and apparent velocity of the signal. These two parameters are thereafter used to estimate the epicenter latitude-longitude. All these parameters are estimated in near real time as soon as the P-phase of seismic signal reaches the detector(s). Data from Gauribidanur seismic array is used for demonstrating the efficacy of the proposed methodology.
基于连续小波变换的地震事件在线检测与定位估计
在线检测地震的发生和估计震中是至关重要的。人工分析仍然是描述地震事件和与之相关的各种地震相(波)的最后手段。本文尝试对地震阵列信号进行多尺度建模,以实现事件发生的自动检测、事件位置的自动估计和自动/无监督报告的生成。该技术工作在小波域,利用地震波的非平稳特性。在检测到事件后,使用P起点附近的数据的一部分来计算信号的方位角和表观速度。这两个参数随后被用来估计震中的经纬度。当地震信号的p相位到达检测器时,所有这些参数都能近乎实时地估计出来。利用高里比都努尔地震台阵的数据验证了所提出方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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