天津科技 ›› 2023, Vol. 50 ›› Issue (3): 43-46.

• 基础研究 • 上一篇    下一篇

基于数字孪生技术开展 LNG 船舶设备故障诊断及预测

斯园园, 周毅, 孙冰, 李萌, 蒙学昊   

  1. 中海油能源发展采油服务公司 天津 300452
  • 收稿日期:2023-01-19 出版日期:2023-03-25 发布日期:2023-12-27

Fault Diagnosis and Prediction of LNG Ship Equipment Based on Digital Twin Technology

SI Yuanyuan, ZHOU Yi, SUN Bing, LI Meng, MENG Xuehao   

  1. CNOOC Energy Technology & Services-Oil Production Services Co.,Tianjin 300452,China
  • Received:2023-01-19 Online:2023-03-25 Published:2023-12-27

摘要: 在人工智能、大数据、物联网背景下,开展数字化在船舶管理中的应用研究已经成为 LNG 船舶行业焦点和发展趋势。通过开展船舶数字化运营技术研究,借助建立的智能化管理平台,优化船舶运营管理模式,提供全生命周期的数字化运营服务。以海洋石油301为目标船,通过数字化三维模型开发、复杂航海场景的动态演化模拟、可视化运营管理等技术开展 LNG 船舶设备故障诊断及预测研究。

关键词: 数字孪生, 故障诊断, 预测

Abstract: Under the background of artificial intelligence,big data,and the Internet of Things,the application research of digitalization in ship management has become the focus and development trend of the LNG ship industry. Through the research of ship digital operation technology and the establishment of intelligent management platform,the ship operation management mode is optimized to provide digital operation services throughout the life cycle. Taking the HYSY 301 as the target ship,the fault diagnosis and prediction of LNG ship equipment are carried out through the development of digital three-dimensional model,dynamic evolution simulation technology of complex navigation scenarios,visual operation management and other technologies.

Key words: digital twin, fault diagnosis, prediction

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