Research on the Shore-Based Monitoring System for Marine Diesel Engines Based on Digital Twin Technology

The article aims to reduce the latency of ship-shore information interaction, enabling real-time collection of marine diesel engine data and its transmission to the shore for aggregation and feedback, thereby improving data accuracy. This paper explores the application of digital twin technology in shore-based platform monitoring of diesel engine operating conditions. It constructs a digital twin model and integrates various technologies, including data processing, network system design, and the establishment of a digital twin visualization platform, to achieve real-time monitoring, fault diagnosis, and performance optimization of marine diesel engines. Case analysis has verified that the system’s early warning success rate can reach 99.8%, with a false alarm rate of less than 1%. This demonstrates its high warning success rate and low false alarm rate, significantly improving the efficiency and safety of ship management. It also highlights the promising application prospects and practical value of digital twin technology in marine diesel engine monitoring, providing theoretical support and practical guidance for the development of future smart shipping technologies.

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Publication Details

Published
2024-12-27
DOI
https://doi.org/10.1109/icises64179.2024.11116168
Primary Topic
Maritime Navigation and Safety
Type
article
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article

Research on the Shore-Based Monitoring System for Marine Diesel Engines Based on Digital Twin Technology

Yu Chen, Buhui Zeng, Ye Zeng, Yutong Wu et al.
Maritime Navigation and Safety
article

Research on the Shore-Based Monitoring System for Marine Diesel Engines Based on Digital Twin Technology

Yu Chen, Buhui Zeng, Ye Zeng, Yutong Wu, Yilin Mei, Xiayi Ruan
article en

Abstract

The article aims to reduce the latency of ship-shore information interaction, enabling real-time collection of marine diesel engine data and its transmission to the shore for aggregation and feedback, thereby improving data accuracy. This paper explores the application of digital twin technology in shore-based platform monitoring of diesel engine operating conditions. It constructs a digital twin model and integrates various technologies, including data processing, network system design, and the establishment of a digital twin visualization platform, to achieve real-time monitoring, fault diagnosis, and performance optimization of marine diesel engines. Case analysis has verified that the system’s early warning success rate can reach 99.8%, with a false alarm rate of less than 1%. This demonstrates its high warning success rate and low false alarm rate, significantly improving the efficiency and safety of ship management. It also highlights the promising application prospects and practical value of digital twin technology in marine diesel engine monitoring, providing theoretical support and practical guidance for the development of future smart shipping technologies.

Jimei University (CN), Beihang University (CN)
Life below water
Openalex Percentile: Top 61%
Maritime Navigation and Safety
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