Chinese Journal of Construction Machinery, Volume. 23, Issue 3, 548(2025)

Bayesian theory based hydraulic component fault diagnosis method

QIU Zhiwei1, LI Wanli1, WANG Daozhi1, FAN Siwen1, and SUN Yougang2
Author Affiliations
  • 1School of Mechanical Engineering, Tongji University, Shanghai 201800, China
  • 2Institute of Rail Transit, Tongji University, Shanghai 201800, China
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    References(9)

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    [5] [5] JI X, REN Y, TANG H, et al. An intelligent fault diagnosis approach based on Dempster-Shafer theory for hydraulic valves [J]. Measurement, 2020, 165: 1-10.

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    [8] [8] HHUANG K, WU S, LI F, et al. Fault diagnosis of hydraulic systems based on deep learning model with multirate data samples [J]. IEEE Transactions on Neural Networks and Learning Systems, 2022, 33(11): 6789-6801.

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    QIU Zhiwei, LI Wanli, WANG Daozhi, FAN Siwen, SUN Yougang. Bayesian theory based hydraulic component fault diagnosis method[J]. Chinese Journal of Construction Machinery, 2025, 23(3): 548

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    Paper Information

    Received: --

    Accepted: Aug. 25, 2025

    Published Online: Aug. 25, 2025

    The Author Email:

    DOI:10.15999/j.cnki.311926.2025.03.030

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