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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2404.10363 |
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| _version_ | 1866916208439197696 |
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| author | Youssef, Ayah Noura, Hassan Amrani, Abderrahim El Adel, El Mostafa El Ouladsine, Mustapha |
| author_facet | Youssef, Ayah Noura, Hassan Amrani, Abderrahim El Adel, El Mostafa El Ouladsine, Mustapha |
| contents | Fault diagnosis in marine diesel engines is vital for maritime safety and operational efficiency.These engines are integral to marine vessels, and their reliable performance is crucial for safenavigation. Swift identification and resolution of faults are essential to prevent breakdowns,enhance safety, and reduce the risk of catastrophic failures at sea. Proactive fault diagnosisfacilitates timely maintenance, minimizes downtime, and ensures the overall reliability andlongevity of marine diesel engines. This paper explores the importance of fault diagnosis,emphasizing subsystems, common faults, and recent advancements in data-driven approachesfor effective marine diesel engine maintenance |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_10363 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Survey on Data-Driven Fault Diagnostic Techniques for Marine Diesel Engines Youssef, Ayah Noura, Hassan Amrani, Abderrahim El Adel, El Mostafa El Ouladsine, Mustapha Machine Learning Fault diagnosis in marine diesel engines is vital for maritime safety and operational efficiency.These engines are integral to marine vessels, and their reliable performance is crucial for safenavigation. Swift identification and resolution of faults are essential to prevent breakdowns,enhance safety, and reduce the risk of catastrophic failures at sea. Proactive fault diagnosisfacilitates timely maintenance, minimizes downtime, and ensures the overall reliability andlongevity of marine diesel engines. This paper explores the importance of fault diagnosis,emphasizing subsystems, common faults, and recent advancements in data-driven approachesfor effective marine diesel engine maintenance |
| title | A Survey on Data-Driven Fault Diagnostic Techniques for Marine Diesel Engines |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2404.10363 |