Research on Sea Ice and Local Ice Load Monitoring System for Polar Cargo Vessels

Sea ice and the resulting loads are major safety concerns for vessels operating in ice-covered regions. This study presents a tailored sea ice and local ice load monitoring system specifically designed for polar cargo vessels. The system employs shipboard cameras coupled with a DeepLab v3+-based algorithm to achieve real-time ice concentration identification, demonstrating 90.68% accuracy when validated against historical Arctic Sea ice imagery. For structural load monitoring, we developed a hybrid methodology integrating numerical simulations, full-scale strain measurements, and classification society standards, enabling the precise evaluation of ice-induced structural responses. The system’s operational process is demonstrated through comprehensive case studies of characteristic ice collision scenarios. Furthermore, this system serves as an exemplary implementation of a navigation assistance framework for polar cargo vessels, offering both real-time operational guidance and long-term reference data for enhancing ice navigation safety.

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Institutions

Publication Details

Journal
Journal of Marine Science and Engineering
Published
2025-04-18
DOI
https://doi.org/10.3390/jmse13040808
Citations
3
Primary Topic
Arctic and Antarctic ice dynamics
Type
article
Field-Weighted Citation Impact
3.90

Funders

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article

Research on Sea Ice and Local Ice Load Monitoring System for Polar Cargo Vessels

Shunying Ji, Shiqin He, Xiaohong Chen, HongYuan JIANG et al.
3 citations
Journal of Marine Science and Engineering
Arctic and Antarctic ice dynamics
3.90
article

Research on Sea Ice and Local Ice Load Monitoring System for Polar Cargo Vessels

Shunying Ji, Shiqin He, Xiaohong Chen, HongYuan JIANG, Jinhui Jiang
article en
3 citations

Abstract

Sea ice and the resulting loads are major safety concerns for vessels operating in ice-covered regions. This study presents a tailored sea ice and local ice load monitoring system specifically designed for polar cargo vessels. The system employs shipboard cameras coupled with a DeepLab v3+-based algorithm to achieve real-time ice concentration identification, demonstrating 90.68% accuracy when validated against historical Arctic Sea ice imagery. For structural load monitoring, we developed a hybrid methodology integrating numerical simulations, full-scale strain measurements, and classification society standards, enabling the precise evaluation of ice-induced structural responses. The system’s operational process is demonstrated through comprehensive case studies of characteristic ice collision scenarios. Furthermore, this system serves as an exemplary implementation of a navigation assistance framework for polar cargo vessels, offering both real-time operational guidance and long-term reference data for enhancing ice navigation safety.

Journal of Marine Science and EngineeringVol. 13(4)
Shanghai Jiao Tong University (CN), Dalian University of Technology (CN), Shanghai Ship and Shipping Research Institute (CN)
National Natural Science Foundation of China, Ministry of Industry and Information Technology of the People's Republic of China, National Key Research and Development Program of China
Openalex Percentile: Top 7%
Arctic and Antarctic ice dynamics
3.90
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Research on Sea Ice and Local Ice Load Monitoring System for Polar Cargo Vessels — Shunying Ji, Shiqin He, et al. · Journal of Marine Science and Engineering (2025) | TGRS Research Map | TGRS