Chinese Journal of Ship Research, Volume. 16, Issue 1, 158(2021)

Condition monitoring method for marine engine room equipment based on machine learning

Ruihan WANG1,2, Hui CHEN1,2, and Cong GUAN1,2
Author Affiliations
  • 1School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, China
  • 2Key Laboratory of High Performance Ship Technology of Ministry of Education, Wuhan University of Technology, Wuhan 430063, China
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    References(10)

    [3] CHEN H, ZHANG Z H, GUAN C et al. Optimization of sizing and frequency control in battery/supercapacitor hybrid energy storage system for fuel cell ship[J]. Energy, 197, 117285(2020).

    [13] ZHANG L W, LIN J, KARIM R. An angle-based subspace anomaly detection approach to high-dimensional data: with an application to industrial fault detection[J]. Reliability Engineering & System Safety, 142, 482-497(2015).

    [16] [16] MALM L A, ENSTRM J, HULTMAN A. Main engine damage study[EBOL]. [20201016]. http:www.swedishclub.com.

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    Ruihan WANG, Hui CHEN, Cong GUAN. Condition monitoring method for marine engine room equipment based on machine learning[J]. Chinese Journal of Ship Research, 2021, 16(1): 158

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    Paper Information

    Category: Intelligent Engine Room

    Received: Oct. 20, 2020

    Accepted: --

    Published Online: Mar. 27, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.02150

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