Summary of A Survey on Data-driven Fault Diagnostic Techniques For Marine Diesel Engines, by Ayah Youssef (diapro) et al.
A Survey on Data-Driven Fault Diagnostic Techniques for Marine Diesel Engines
by Ayah Youssef, Hassan Noura, Abderrahim El Amrani, El Mostafa El Adel, Mustapha Ouladsine
First submitted to arxiv on: 16 Apr 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper focuses on fault diagnosis in marine diesel engines, a crucial aspect for maritime safety and operational efficiency. Marine diesel engines are essential components of marine vessels, and their reliable performance is vital for safe navigation. The swift identification and resolution of faults are necessary to prevent breakdowns, enhance safety, and reduce the risk of catastrophic failures at sea. Proactive fault diagnosis enables timely maintenance, minimizes downtime, and ensures the overall reliability and longevity of marine diesel engines. The paper highlights the importance of fault diagnosis, emphasizing subsystems, common faults, and recent advancements in data-driven approaches for effective marine diesel engine maintenance. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about fixing problems in big machines that power boats and ships. These machines are very important because they help keep people safe while sailing the seas. If these machines break down, it can be a big problem! So, finding and fixing problems quickly is really important. This helps keep everyone safe and reduces the risk of something bad happening at sea. The paper talks about how to do this using special computer tools and methods. |
