A Deep Neural Network to Identify Vacuum Degrees in Vacuum Interrupter Based on Partial Discharge Diagnosis-Reference-Cited by-同舟云学术

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A Deep Neural Network to Identify Vacuum Degrees in Vacuum Interrupter Based on Partial Discharge Diagnosis

Published:2022 Issue: Volume:10 Page:95125-95131
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Nhung-Nguyen Hong¹,Youn Young-Woo²,Kim Yong-Hwa³^ORCID

Affiliation:

1. Department of Electronic Engineering, Myongji University, Yongin, South Korea

2. Smart Grid Research Division, Korea Electrotechnology Research Institute, Changwon, South Korea

3. Department of Data Science, Korea National University of Transportation, Uiwang, South Korea

Funder

Korea Institute of Energy Technology Evaluation and Planning (KETEP), Ministry of Trade, Industry and Energy (MOTIE), South Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09831777.pdf?arnumber=9831777

Reference25 articles.

1. Deep Residual Learning for Image Recognition

2. Deep Learning for Computer Vision: A Brief Review

3. Deep Neural Networks for High Dimension, Low Sample Size Data

4. Determination of gas pressure in vacuum interrupter based on partial discharge

5. Reliability and Field Experience of Vacuum Interrupters

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