摘要
为解决传统船舶运维工作的复杂化与高成本,本文采用数字孪生技术构建智慧船舶运维管控系统,通过对数据的处理与决策,提升管理效率、实现可视化管理。通过传感器采集船舶数据,先通过集成算法对数据进行预处理,后结合数字孪生模型进行深度分析,从而实现对船舶实时的监控和预测维护。该方案在数据预处理方面准确率高达约95%,故障通知时间约为0.06 s,有效提升了船舶运维效率和安全性,同时降低了成本并增强了风险响应能力。可视化界面使管理人员操作和决策更直观,提升用户体验。提供智能船舶运维管控解决方案,集数据采集、处理、分析和反馈为一体,推动智能船舶技术发展,为数字孪生应用提供借鉴。智能化运维有望支持全球航运业数字化转型,提升航运安全、效率。
The rapid advancement of information technology has presented new challenges and opportunities for smart ships.To address the complexity and high costs associated with traditional ship operation and maintenance,this article employs digital twin technology to construct a smart ship operation and maintenance control system.Through data processing and decision-making,it enhances management efficiency and enables visual management.Ship data is collected via sensors,which is preprocessed using integrated algorithms first and then subjected to in-depth analysis in combination with the digital twin model,thereby achieving real-time monitoring and predictive maintenance of the ship.This solution achieves an accuracy rate of approximately 95%in data preprocessing and a fault notification time of approximately 0.06 seconds,effectively improving the efficiency and safety of ship operation and maintenance,while reducing costs and enhancing risk response capabilities.The visual interface makes the operations and decisions of management personnel more intuitive,enhancing the user experience.This article offers an intelligent ship operation and maintenance control solution that integrates data collection,processing,analysis,and feedback,promoting the development of smart ship technology and providing a reference for the application of digital twin.Intelligent operation and maintenance is expected to support the digital transformation of the global shipping industry and enhance shipping safety and efficiency.
作者
曾步辉
陈宇
杨江河
葛政
杨馨雨
姜箫恒
ZENG Buhui;CHEN Yu;YANG Jianghe;GE Zheng;YANG Xinyu;JIANG Xiaoheng(Marine Engineering College,Jimei University,Xiamen 361021,China;National Marine Experimental Teaching Demonstration Center,Xiamen 361021,China)
出处
《舰船科学技术》
北大核心
2025年第15期139-144,共6页
Ship Science and Technology
基金
国家级大学生创新创业项目(202310390007,202310390026)。
关键词
数字孪生技术
智慧船舶
可视化远程运维管控系统
数据处理
故障诊断
digital twin technology
smart ship
visual remote operation and maintenance control system
data processing
fault diagnosis
