{"title":"Online detection and location estimation of earthquake events using continuous wavelet transform","authors":"S. Saha, D. Mukherjee, S. Mukhopadhyay","doi":"10.1109/CMI.2016.7413714","DOIUrl":null,"url":null,"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.","PeriodicalId":244262,"journal":{"name":"2016 IEEE First International Conference on Control, Measurement and Instrumentation (CMI)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE First International Conference on Control, Measurement and Instrumentation (CMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CMI.2016.7413714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.