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Artificial intelligence recognition method of living body electric shock in low voltage distribution networks
ID：98 View Protection：ATTENDEE Updated Time：2020-10-15 18:43:09 Hits：792 Oral Presentation

Start Time：2020-11-02 17:00（Asia/Shanghai）

Duration：15min

Session：A Power System » A1Session 1 and Session 6

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Abstract
  In the low-voltage distribution network, it is difficult to determine the moment of electric shock and distinguish the types of electric shock by detecting the total leakage current. In order to solve the problems, a recognition method of electric shock based on artificial intelligence is proposed in this paper. The constructed adaptive threshold is used to detect the mutation amount of the total leakage current, which achieves the purpose of determining the moment of electric shock. And then, according to the different waveform characteristics of living and non-living bodies after electric shock, the electric shock accidents are classified. The results show that the proposed method can effectively detect electric shock signals and has reference value for the development of a new generation of residual current protectors.
Keywords
Classification of electric shock accidents, Electric shock signal detection, Low-voltage distribution network, Neural networks
Speaker
Wei Zheng-feng
Fuzhou University

Submission Author
Wei Zheng-feng Fuzhou University
Guo Mou-fa Fuzhou University
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Important Date

  • Conference Date

    Nov 02

    2020

    to

    Nov 04

    2020

  • Oct 27 2020

    Draft paper submission deadline

  • Nov 03 2020

    Contribution Submission Deadline

  • Nov 04 2020

    Registration deadline

  • Nov 17 2020

    Final Paper Deadline

Sponsored By
IEEE IAS Student Chapter of Huazhong University of Science and Technology (HUST)
Organized By
Huazhong University of Science and Technology
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