Fault detection and diagnosis of marine diesel engines: A systematic review

Marine diesel engines play a pivotal role in ensuring the smooth operation of maritime vessels. However, given the rigorous operational conditions and the natural wear and tear of engine components, the likelihood of diesel engine failures during voyages is an inherent concern. Preserving the optimal functionality and performance of marine diesel engines is of paramount importance, as it averts the potential repercussions of in-service failures and accidents. Hence, timely and effective fault detection is imperative to minimize operational disruptions and uphold safety standards. Intelligent fault detection and diagnosis (FDD) holds substantial promise in both academic and industrial contexts. While the monitoring of marine diesel engines using various FDD techniques has been a subject of study for decades, various new techniques emerges and there is a notable absence of comprehensive analysis and summarization of the methodologies developed. This paper commences by introducing the operational principles of marine diesel engines and elucidating potential faults. Subsequently, it provides an overview of recent advancements in FDD methods tailored for marine diesel engines, categorizing them into four distinct sections. In alignment with the conventional FDD workflow, the paper delves into discussions concerning model-based, data-driven, knowledge-based, and hybrid approaches. Moreover, it offers insights into the potential future directions of this field.

• Record URL:
  • https://doi.org/10.1016/j.oceaneng.2024.116798
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0029801824001355
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00298018
• Supplemental Notes:
  • © 2024 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Lv, Yaqiong
  • Yang, Xueting
  • Li, Yifan
  • Liu, Jialun
  • 0000-0002-0802-8986
  • Li, Shijie
• Publication Date: 2024-2-15

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 116798
• Serial:
  • Ocean Engineering
  • Volume: 294
  • Issue Number: 0
  • Publisher: Pergamon
  • ISSN: 0029-8018
  • EISSN: 1873-5258
  • Serial URL: http://www.sciencedirect.com/science/journal/00298018

Subject/Index Terms

• TRT Terms: Diagnosis; Fault monitoring; Marine diesel engines; Reviews; Vehicle maintenance
• Subject Areas: Marine Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01908293
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 15 2024 5:04PM