Chinese Journal of Ship Research, Volume. 17, Issue 6, 118(2022)

Stacking-based method for predicting remaining useful life of engine room equipment

Chaoyou GUO1, Zhe XU2, and Qian YAO3
Author Affiliations
  • 1College of Power Engineering, Naval University of Engineering, Wuhan 430033, China
  • 2The 92942 Unit of PLA, Beijing 100161, China
  • 3The 92578 Unit of PLA, Beijing 100161, China
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    References(10)

    [4] [4] PECHT M. Prognostics health management of electronics[M]. Hoboken: Wiley, 2008.

    [5] [5] PECHT M G, KANG M. Prognostics health management of electronics: fundamentals, machine learning, the inter of things[M]. Hoboken: John Wiley Sons Ltd. , 2018.

    [6] MAHAMAD A K, SAON S, HIYAMA T. Predicting remaining useful life of rotating machinery based artificial neural network[J]. Computers & Mathematics with Applications, 60, 1078-1087(2010).

    [19] [19] CHEN T Q, GUESTRIN C. XGBoost: a scalable tree boosting system[C]Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery Data Mining. San Francisco: ACM, 2016: 785–794.

    [20] [20] NECTOUX P, GOURIVEAU R, MEDJAHER K, et al. PRONOSTIA: an experimental platfm f bearings accelerated degradation tests[C]Proceedings of IEEE International Conference on Prognostics Health Management. Colado: IEEE, 2012.

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    Chaoyou GUO, Zhe XU, Qian YAO. Stacking-based method for predicting remaining useful life of engine room equipment[J]. Chinese Journal of Ship Research, 2022, 17(6): 118

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    Paper Information

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    Received: Nov. 30, 2021

    Accepted: --

    Published Online: Mar. 26, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.02672

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