A particle swarm optimization‐based support vector machine model to detect charging pile arc faults by using the pre‐treatment generalized S transform-Reference-Cited by-同舟云学术

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A particle swarm optimization‐based support vector machine model to detect charging pile arc faults by using the pre‐treatment generalized S transform

Published:2022-08-03 Issue:9 Volume:2022 Page:928-935
ISSN:2051-3305
Container-title:The Journal of Engineering
language:en
Short-container-title:The Journal of Engineering

Author:

Deng Hanjun¹²,Zeng Wenwei¹²,Huang Rui¹²,Wu Zhiyong¹²,He Xing¹²,Liu Xuan³,Xiao Jianhong¹²,Chen Hao¹²,Liu Mouhai¹²

Affiliation:

1. Measurement center of power supply service center of State Grid Hunan Electric Power Co., Ltd Changsha China

2. Hunan Key Laboratory of Intelligent Electrical Measurement and Application Technology Changsha China

3. China Electric Power Research Institute Co., Ltd. Beijing China

Publisher

Institution of Engineering and Technology (IET)

Subject

General Engineering,Energy Engineering and Power Technology,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/tje2.12175

Reference29 articles.

1. Opportunities and Challenges of Vehicle-to-Home, Vehicle-to-Vehicle, and Vehicle-to-Grid Technologies

2. Electrical Safety Considerations in Large-Scale Electric Vehicle Charging Stations

3. Zhang K. Yin Z. Yang X. Yan Z. Huang Y.:Quantitative assessment of electric safety protection for electric vehicle charging equipment. In: 2017 International Conference on Circuits Devices and Systems (ICCDS) pp.89–94(2017).https://doi.org/10.1109/ICCDS.2017.8120457.

4. Electrical Safety of Plug-In Electric Vehicles: Shielding the Public from Shock

5. A Novel Approach for Arc-Flash Detection and Mitigation: At the Speed of Light and Sound

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