Infrared Technology, Volume. 47, Issue 8, 1027(2025)

Substation Equipment Fault Identification Based on UFPN-Fuse Network

Changzheng DENG1, Mengqing GONG1, Tian FU2, Mingze LIU1, and Pengyu XIA3
Author Affiliations
  • 1College of Electrical and New Energy, China Three Gorges University, Yichang 443002, China
  • 2Hubei Communications Investment Technology Development Co. LTD., Wuhan 430000, China
  • 3State Grid Sichuan Electric Power Extra High Voltage Company, Chengdu 610041, China
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    References(4)

    [2] [2] Jadin M S, Taib S. Recent progress in diagnosing the reliability of electrical equipment by using infrared thermography[J].Infrared Physics & Technology, 2012,55(4): 236-245.

    [4] [4] LI Y, ZHAO K, REN F, et al. Research on super-resolution image reconstruction based on low-resolution infrared sensor[J].IEEE Access, 2020,8: 69186-69199.

    [6] [6] WANG T, HE Y, LI B, et al. Transformer fault diagnosis using self-powered RFID sensor and deep learning approach[J].IEEE Sensors Journal, 2018,18(15): 6399-6411.

    [7] [7] ZOU H, HUANG F. A novel intelligent fault diagnosis method for electrical equipment using infrared thermography[J].Infrared Physics & Technology, 2015,73: 29-35.

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    DENG Changzheng, GONG Mengqing, FU Tian, LIU Mingze, XIA Pengyu. Substation Equipment Fault Identification Based on UFPN-Fuse Network[J]. Infrared Technology, 2025, 47(8): 1027

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    Paper Information

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    Received: Mar. 29, 2023

    Accepted: Sep. 15, 2025

    Published Online: Sep. 15, 2025

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