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首页|期刊导航|中国海洋大学学报(自然科学版)|基于数字孪生的海底地质灾害监测预警技术研究

基于数字孪生的海底地质灾害监测预警技术研究OA北大核心CSTPCD

Research on Submarine Geohazard Monitoring and Early Warning Technology Based on Digital Twin

中文摘要英文摘要

本文创新了基于海底实时监测数据驱动的海底工程地质环境数字孪生模型,建立了一套埕岛油田地质灾害监测预警系统,构建了海底工程地质环境数据库,实现了对海底监测数据的远程实时可视化更新及交互控制.该系统应用于埕岛海底地质灾害监测,在持续运行的 40 天监测周期内,累计警报了 2 次强海底侵蚀灾害,提示了 4 次高浊度事件,真实反映了研究区海底侵蚀变化.本文首次尝试将数字孪生技术融合到海底地质灾害的监测预警中,为区域地质灾害防控提供了一种新的技术参考.

Subsea geohazard monitoring and early warning is very important for the safety of marine en-gineering,but the current subsea geohazard database only stays in the compilation of historical data,which makes it difficult to grasp the changes of marine environment in real time and cannot warn the oc-currence of disasters in time.A digital twin model of seabed engineering and geological environment driven by real-time seabed monitoring data has been innovated to establish a set of seabed geohazard mo-nitoring and early warning system in Chengdao sea area,build a seabed engineering and geological envi-ronment database,and realise remote real-time visualisation update and interactive control of seabed monitoring data.The system was applied to the seabed geohazard monitoring in Chengdao sea area,and during the 40-day monitoring cycle of continuous operation,two strong seabed erosion hazards were warned and four high turbidity events were suggested,which proved that the system operated stably in the early warning of seabed erosion and siltation hazards.The first attempt to integrate digital twin technology into the monitoring and early warning of submarine geohazards provides a new idea for re-gional geohazard risk prevention and control.

李晓萌;陈天;徐玮铎;孙志文;薛凉;朱宪明;范智涵;单红仙;贾永刚

中国海洋大学山东省海洋环境地质工程重点实验室,山东 青岛 266100中国海洋大学山东省海洋环境地质工程重点实验室,山东 青岛 266100||自然资源部海岸带科学与综合管理重点实验室,山东 青岛 266061中国海洋大学信息科学与工程学部,山东 青岛 266100中国海洋大学山东省海洋环境地质工程重点实验室,山东 青岛 266100||崂山实验室海洋地质过程与环境功能实验室,山东 青岛 266237

海洋学

数字孪生海洋地质灾害监测预警海底工程地质环境埕岛油田UE4

digital twinmarine geologicd hazardsmonitoring and early warningsubsea engineering geological environmentChengdao oilfieldUE4

《中国海洋大学学报(自然科学版)》 2024 (005)

102-114 / 13

国家自然科学基金项目(41877223,U190620170);自然资源部海岸带科学与综合管理重点实验室开放基金项目(2021COSIMQ007);中央高校基本科研业务费专项(202161039)资助 Supported by the National Natural Science Foundation of China(41877223,U190620170);the Open Fund of the Key Laboratory of Coastal Zone Science and Integrated Management,Ministry of Natural Resources(2021COSIMQ007);the Central Universities Basic Research Funds(202161039)

10.16441/j.cnki.hdxb.20230056

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