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ISSN 2096-7780 CN 10-1665/P

杨应召. 基于实时测震数据的可视化系统的设计与实现[J]. 地震科学进展, 2020, (9): 20-24. DOI: 10.3969/j.issn.2096-7780.2020.09.004
引用本文: 杨应召. 基于实时测震数据的可视化系统的设计与实现[J]. 地震科学进展, 2020, (9): 20-24. DOI: 10.3969/j.issn.2096-7780.2020.09.004
Yingzhao Yang. Design and implementation of visualization system based on real-time seismic data[J]. Progress in Earthquake Sciences, 2020, (9): 20-24. DOI: 10.3969/j.issn.2096-7780.2020.09.004
Citation: Yingzhao Yang. Design and implementation of visualization system based on real-time seismic data[J]. Progress in Earthquake Sciences, 2020, (9): 20-24. DOI: 10.3969/j.issn.2096-7780.2020.09.004

基于实时测震数据的可视化系统的设计与实现

Design and implementation of visualization system based on real-time seismic data

  • 摘要: 为研究在地震速报等基于测震数据的业务场景中,对于地震事件检测等中间处理结果的可视化问题,本文设计实现了一套基于实时测震数据的可视化系统。该系统利用分布式消息队列Kafka实现了流式数据的缓存,利用分布式实时数据处理框架Flink实现了震相到时拾取和地震事件检测,最终利用大数据可视化组件Echarts实现了基于全国范围的各个地震台站的震相到时统计情况展示地图。通过部署与应用,该系统达到了设计的目的,实现了应有的功能,满足了实际需求。

     

    Abstract: In order to study the visualization of intermediate processing results such as seismic event detection in the business scenarios based on seismic data such as earthquake quick report, a set of visualization system based on real-time seismic data is designed and implemented in this paper. The system uses distributed message queue Kafka to realize streaming data caching, and uses a distributed real-time data processing framework Flink, to realize seismic phase arrival time pick-up and seismic event detection. Finally, it uses the big data visualization component Echarts to display the seismic phase arrival time statistics of various seismic stations nationwide. Through the deployment and application, the system achieves the purpose of design, realizes its functions, and meets the actual needs.

     

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