Process Automation Instrumentation, Volume. 46, Issue 8, 66(2025)

Research on Condition Monitoring and Fault Early Warning Model of Rotating Equipment in Thermal Power Plants

ZHENG Zhaohui
Author Affiliations
  • National Energy Tai'an Thermoelectric Co, Ltd, Tai'an 271024, China
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    References(3)

    [2] [2] HEMATILLAKE D,FREETHY D,MCGIVERN J,et al. Design and optimization of a penicillin fed-batch reactor based on a deep learning fault detection and diagnostic model [J]. Industrial & Engineering Chemistry Research,2022,61(13):4 625-4 637.

    [3] [3] PIETRZAK P,WOLKIEWICZ M,ORLOWSKA-KOWALSKA T. PMSM stator winding fault detection and classification based on bispectrum analysis and convolutional neural network [J]. IEEE Transactions on Industrial Electronics,2023,70(5):5 192-5 202.

    [9] [9] XIE J,LIU X,TIAN W,et al. Estimating gridded monthly baseflow from 1981 to 2020 for the contiguous US using long short-term memory (LSTM) networks [J]. Water Resources Research,2022,58(8):1-19.

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    ZHENG Zhaohui. Research on Condition Monitoring and Fault Early Warning Model of Rotating Equipment in Thermal Power Plants[J]. Process Automation Instrumentation, 2025, 46(8): 66

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    Paper Information

    Received: Jan. 29, 2024

    Accepted: Aug. 26, 2025

    Published Online: Aug. 26, 2025

    The Author Email:

    DOI:10.16086/j.cnki.issn1000-0380.2024010120

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