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Multicycle Incipient Fault Detection and Location for Medium Voltage Underground Cable

  • Published:2017-06 Issue:3 Volume:32 Page:1450-1459
  • ISSN:0885-8977
  • Container-title:IEEE Transactions on Power Delivery
  • language:
  • Short-container-title:IEEE Trans. Power Delivery

Author:

Zhang Wenhai,Xiao Xianyong,Zhou Kai,Xu Wilsun,Jing Yindi

Funder

China Scholarship Council

Miaozi Project in Science and Technology Innovation Program of Sichuan Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Cited by 45 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Detection and Identification of Underground Cable Incipient Faults Based on Denoising Autoencoder and Optimized Convolutional Neural Network;2023 International Conference on Power System Technology (PowerCon);2023-09-21

2. Cable Fault Detection and Diagnosis Method Based on Convolutional Neural Network;2023 IEEE International Conference on Image Processing and Computer Applications (ICIPCA);2023-08-11

3. A Method for Medium Voltage Underground Cables Incipient Faults Diagnosis and Location Using Sheath Current;2023 3rd International Conference on Energy Engineering and Power Systems (EEPS);2023-07-28

4. Research on Characterizing and Detecting Voltage Disturbance Due to the Incipient Fault of MV Power Cables;Transactions on Electrical and Electronic Materials;2023-06-05

5. Power disturbance waveform analysis and proactive application in power systems;Energy Conversion and Economics;2023-04
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