A real-time AI-assisted seismic monitoring system based on new nodal stations with 4G telemetry and its application in the Yangbi MS 6.4 aftershock monitoring in southwest China

Junlun Li , Huajian Yao , Baoshan Wang , Yang Yang , Xin Hu , Lishu Zhang , Beng Ye , Jun Yang , Xiaobin Li , Feng Liu , Guoyi Chen , Chang Guo , Wen Yang
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引用次数: 11

Abstract

A rapidly deployable dense seismic monitoring system which is capable of transmitting acquired data in real time and analyzing data automatically is crucial in seismic hazard mitigation after a major earthquake. However, it is rather difficult for current seismic nodal stations to transmit data in real time for an extended period of time, and it usually takes a great amount of time to process the acquired data manually. To monitor earthquakes in real time flexibly, we develop a mobile integrated seismic monitoring system consisting of newly developed nodal units with 4G telemetry and a real-time AI-assisted automatic data processing workflow. The integrated system is convenient for deployment and has been successfully applied in monitoring the aftershocks of the Yangbi MS 6.4 earthquake occurred on May 21, 2021 in Yangbi County, Dali City, Yunnan in southwest China. The acquired seismic data are transmitted almost in real time through the 4G cellular network, and then processed automatically for event detection, positioning, magnitude calculation and source mechanism inversion. From tens of seconds to a couple of minutes at most, the final seismic attributes can be presented remotely to the end users through the integrated system. From May 27 to June 17, the real-time system has detected and located 7 905 aftershocks in the Yangbi area before the internal batteries exhausted, far more than the catalog provided by China Earthquake Networks Center using the regional permanent stations. The initial application of this integrated real-time monitoring system is promising, and we anticipate the advent of a new era for Real-time Intelligent Array Seismology (RIAS), for better monitoring and understanding the subsurface dynamic processes caused by Earth's internal forces as well as anthropogenic activities.

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基于新型4G遥测节点站的人工智能实时辅助地震监测系统及其在西南杨壁6.4级余震监测中的应用
一个能够实时传输采集数据并自动分析数据的可快速部署的密集地震监测系统是大地震后减灾的关键。然而,目前的地震节点站要实现长时间的实时数据传输是相当困难的,对采集到的数据进行人工处理通常需要花费大量的时间。为了灵活地实时监测地震,我们开发了一个移动综合地震监测系统,该系统由新开发的节点单元组成,具有4G遥测和实时人工智能辅助的自动数据处理工作流。该综合系统部署方便,已成功应用于2021年5月21日云南省大理市杨壁县杨壁6.4级地震余震监测。采集到的地震数据通过4G蜂窝网络几乎实时传输,然后进行事件检测、定位、震级计算和震源机制反演等自动处理。从几十秒到几分钟,最终的地震属性可以通过集成系统远程呈现给最终用户。从5月27日到6月17日,在内部电池耗尽之前,实时系统在杨壁地区检测并定位了7905次余震,远远超过了中国地震台网中心使用区域常设站提供的目录。这种综合实时监测系统的初步应用前景广阔,我们预计实时智能阵列地震学(RIAS)的新时代将到来,以便更好地监测和理解由地球内力和人为活动引起的地下动态过程。
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