Research on Comprehensive Identification and Classification Technology for Latent Faults in High- Voltage Switchgear Based on Machine Learning-Reference-Cited by-同舟云学术

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Research on Comprehensive Identification and Classification Technology for Latent Faults in High- Voltage Switchgear Based on Machine Learning

Published:2023-08-18 Issue: Volume:12 Page:777-782
ISSN:
Container-title:2023 International Conference on Advances in Electrical Engineering and Computer Applications (AEECA)
language:
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Author:

Tang Bin¹,Liang Qinqin¹,Han Fangyuan¹,Yu Min¹,Zhang Longfei¹,Luo Zongchang¹,Luo Chuansheng²,Hu Mengzhu¹,Wang Jialin³,Zhu Liping¹

Affiliation:

1. Electric Power Research Institute of Guangxi Power Grid Co., Ltd,Guangxi,China

2. Nanning Power Supply Bureau of Guangxi Power Grid Co., Ltd,Nanning,China

3. Guangxi Power Grid Co., Ltd,Guangxi,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10511267/10511091/10512300.pdf?arnumber=10512300

Reference19 articles.

1. Partial discharge detection on power equipment using a magneto-resistive sensor;Yun;International Journal of Electrical Power and Energy Systems,2023

2. Detection of local discharge of high voltage switch cabinet and analysis of typical local discharge defects;Xiaofei,2022

3. Research on Partial Discharge Detection of Switchgear Based on Ultrasonic Signal Characteristic

4. Analysis of defect diagnosis of partial discharge fault of high voltage switch cabinet;Jiaxin;Mechanical Design and Manufacturing Engineering,2022

5. Radiometric Partial Discharge Detection: A Review

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