极地研究

极地研究 ›› 2025, Vol. 37 ›› Issue (3): 574-584.DOI: 10.13679/j.jdyj.20230075

• 研究论文 • 上一篇    下一篇

基于多状态故障树的北极船舶冰困风险预警模型

姜河蓉1,吴铭燕2,付姗姗1,2,敖晨韵3,王胜正3   

  1. 1上海船舶运输科学研究所有限公司, 水路交通控制全国重点实验室/航运技术交通行业重点实验室, 上海 200135; 
    2上海海事大学交通运输学院, 上海 201306; 
    3上海海事大学商船学院, 上海 201306

  • 收稿日期:2023-11-24 修回日期:2024-03-01 出版日期:2025-09-30 发布日期:2025-09-25
  • 通讯作者: 付姗姗
  • 基金资助:
    国家自然科学基金、上海市科技创新行动计划社会发展科技攻关项目、上海市青年科技启明星项目和水路交通控制全国重点实验室开放课题基金项目

A risk early warning model for the prevention of ships becoming stuck in ice when navigating in Arctic waters based on a multi-state fault tree

JIANG Herong1, WU Mingyan2, FU Shanshan1,2, AO Chenyun3, WANG Shengzheng3   

  1. 1State Key Laboratory of Maritime Technology and Safety/Key Laboratory of Marine Technology Ministry of Communications, Shanghai Ship and Shipping Research Institute Co. Ltd., Shanghai 200135, China;
    2School of Transport & Communications, Shanghai Maritime University, Shanghai 201306, China;
    3College of Merchant Marine, Shanghai Maritime University, Shanghai 201306, China
  • Received:2023-11-24 Revised:2024-03-01 Online:2025-09-30 Published:2025-09-25

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摘要： 北极海冰状态和气候变化给船舶航行安全保障带来了挑战, 为降低船舶冰困的风险, 保障船员和船舶安全, 开展北极航行船舶冰困风险预警研究具有重要意义。本文从气候环境、海况、冰况、船舶和人为因素等方面对诱发北极航行船舶冰困的风险因素进行了识别, 结合船舶航行分级预警规则构建了基于多状态故障树的北极航行船舶冰困风险预警模型, 同时对海冰环境、船舶运行状态等组合场景下的船舶冰困风险进行了概率预测。本预警模型由16个节点(包含12个基本事件、3个中间事件和1个顶事件)组成, 且节点设定了报警、警告、提醒和安全4种状态等级, 可根据北极航行船舶实测数据进行冰困风险动态预警。

关键词: 船舶冰困, 多状态故障树, 风险预警, 北极航行

Abstract: The Arctic sea ice environment and climate change in Arctic waters cause challenges to the safety and security of ship navigation. In order to reduce the risk of ships becoming stuck in ice and protect the safety of crews and ships, it is important to investigate relevant risk early warning systems for ships sailing in Arctic waters. This paper identifies the risk factors for ships being stuck in ice when navigating in Arctic waters from the perspectives of weather, ocean and sea ice conditions, ship, and sailors. A multi-state fault tree risk warning model was constructed based on navigational warning classifications, and the probability prediction was carried out to determine the risk of ships becoming stuck in ice under the combined scenarios of sea ice conditions and ship operation state. Sixteen nodes (including twelve basic events, three intermediate events, and one top event) were identified in the risk warning model for ships sailing in the Arctic, and the nodes were assigned to four state levels: alarm, warning, reminder, and safe. The model provides a dynamic risk warning system based on in situ data from ships sailing in Arctic waters.

Key words: ships stuck in ice,  multi-state fault tree,  risk early warning,  Arctic shipping