Infrared Technology, Volume. 46, Issue 6, 712(2024)

Non-contact Diagnosis of Cable Joint Insulation Deterioration Based on Deep Learning Surface Temperature

Danzhao YAN1, Jing CHEN2, Wangyao LAN3, and Yipeng LIAO4、*
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
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    References(7)

    [5] [5] LI L L, YONG J, XU W. On-line cable condition monitoring using natural power disturbances[J]. IEEE Transactions on Power Delivery, 2019,34(4): 1242-1250.

    [10] [10] HE B L, HUANG Y, YE T, et al. Temperature prediction of power cable joint based on PSO-LSSVM predict model[J]. Electric Power Engineering Technology, 2019, 38(1): 31-35.

    [14] [14] CHENG Y S, ZHAO D W, WANG Y B, et al. Multi-label learning with kernel extreme learning machine autoencoder[J]. Knowledge-Based Systems, 2019, 178: 1-10.

    [17] [17] TKACHUK V. Quantum genetic algorithm based on qutrits and its application[J]. Mathematical Problems in Engineering, 2018(4):8614073.

    [18] [18] GAO Y J, ZHANG F M, ZHAO Y, et al. A novel quantum-inspired binary wolf pack algorithm for difficult knapsack problem[J].International Journal of Wireless and Mobile Computing, 2019, 16(3):222-232.

    [19] [19] YU S J, ZHU J P, CHUN F. A quantum annealing bat algorithm for node localization in wireless sensor networks[J]. Sensors, 2023, 23(2):782-793.

    [22] [22] XU Z N, HU Z W, Zhao L J, et al. Application of temperature field modeling in monitoring of optic-electric composite submarine cable with insulation degradation[J]. Measurement, 2019, 133: 479-494.

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    YAN Danzhao, CHEN Jing, LAN Wangyao, LIAO Yipeng. Non-contact Diagnosis of Cable Joint Insulation Deterioration Based on Deep Learning Surface Temperature[J]. Infrared Technology, 2024, 46(6): 712

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    Paper Information

    Category:

    Received: Jun. 24, 2023

    Accepted: --

    Published Online: Sep. 20, 2024

    The Author Email: Yipeng LIAO (fzu_lyp@163.com。)

    DOI:

    CSTR:32186.14.

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