[Oral Presentation]Artificial intelligence recognition method of living body electric shock in low voltage distribution networks

Artificial intelligence recognition method of living body electric shock in low voltage distribution networks
ID:98 Submission ID:1719 View Protection:ATTENDEE Updated Time:2020-10-15 18:43:09 Hits:269 Oral Presentation

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

Duration:15min

Session:[A] Power System » [A1] Session 1 and Session 6

Video No Permission Presentation File

Tips: The file permissions under this presentation are only for participants. You have not logged in yet and cannot view it temporarily.

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
Comment submit
Verification code Change another
All comments
Log in Sign up Registration Submit