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Research on Fault Diagnosis of Ship Diesel Generator System Based on IVY-RF

Author

Listed:
  • Hui Ouyang

    (Wuhan Second Ship Design and Research Institute, Wuhan 430064, China)

  • Weibo Li

    (School of Automation, Wuhan University of Technology, Wuhan 430070, China)

  • Feng Gao

    (School of Automation, Wuhan University of Technology, Wuhan 430070, China)

  • Kangzheng Huang

    (School of Automation, Wuhan University of Technology, Wuhan 430070, China)

  • Peng Xiao

    (School of Automation, Wuhan University of Technology, Wuhan 430070, China)

Abstract

Ship diesel generator systems are critical to ship navigation. However, due to the harsh marine environment, the systems are prone to failures, and traditional fault diagnosis methods are difficult to meet requirements regarding accuracy, robustness, and reliability. For this reason, this paper proposes a fault diagnosis method for a ship diesel generator system based on the IVY algorithm-optimized random forest (IVY-RF). Firstly, a model of a ship diesel generator system was constructed using MATLAB/Simulink, and the operation data under fault and normal working conditions were collected. Then, the data were preprocessed and time-domain features were extracted. Finally, the IVY-optimized random forest model was used to identify, diagnose, and classify faults. The simulation results show that the IVY-RF method could identify faulty and normal states with 100% accuracy and distinguish 12 types with 100% accuracy. Compared to seven different algorithms, the IVY-RF improved accuracy by at least 0.17% and up to 67.45% on the original dataset and by at least 1.19% and up to 49.40% in a dataset with 5% noise added. The IVY-RF-based fault diagnosis method shows excellent accuracy and robustness in complex marine environments, providing a reliable fault identification solution for ship power systems.

Suggested Citation

  • Hui Ouyang & Weibo Li & Feng Gao & Kangzheng Huang & Peng Xiao, 2024. "Research on Fault Diagnosis of Ship Diesel Generator System Based on IVY-RF," Energies, MDPI, vol. 17(22), pages 1-18, November.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:22:p:5799-:d:1525280
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    References listed on IDEAS

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    3. Zheng Wang & Li Xia & Yongji Wang & Lei Liu, 2014. "Fault Diagnosis System Based on Multiagent Technique for Ship Power System," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-7, March.
    4. Chai, Merlin & Bonthapalle, Dastagiri Reddy & Sobrayen, Lingeshwaren & Panda, Sanjib K. & Wu, Die & Chen, XiaoQing, 2018. "Alternating current and direct current-based electrical systems for marine vessels with electric propulsion drives," Applied Energy, Elsevier, vol. 231(C), pages 747-756.
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