Intelligent Fault Diagnosis of Substation Equipment on theBasis of Deep Learning and Knowledge Graph

Falong XIAO; Yuezhong WU; Xuehao SHEN; Zhenkai HE; Ye QIN

doi:10.12204/j.issn.1000-7229.2022.03.008

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Electric Power Construction ›› 2022, Vol. 43 ›› Issue (3) : 66-74. DOI: 10.12204/j.issn.1000-7229.2022.03.008

Application of Artificial Intelligence in Power Grid Fault Diagnosis and Location ·Hosted by Professor WANG Xiaojun, Associate Professor LUO Guomin and Associate Professor SHI Fang·

Intelligent Fault Diagnosis of Substation Equipment on theBasis of Deep Learning and Knowledge Graph

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{{article.zuoZheEn_L}}. {{article.title_en}}[J]. {{journal.qiKanMingCheng_EN}}, 2022, 43(3): 66-74 https://doi.org/10.12204/j.issn.1000-7229.2022.03.008

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Administrator：State Grid Corporation of China
Sponsors：
State Grid Economic and Technological Research Institute Co. Ltd
China Power Engineering Consulting Group Co., Ltd
China Electric Power Research Institute
Editor in Chief: Zhang Quan
Associate Editor-in-Chief:KANG Chongqing, BI Tianshu, LI Hui
Executive Editor-in-Chief:YANG Weihong, SHENG Yi
Editorial Director:WEI Xihui
CN: 11-2583/TM
ISSN: 1000-7229

Address: Tower A225, SGCC, Future Science & Technology Park, Beijing 102209, China
Post Code: 102209
Editor’s Tel: 86-10-66602697
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Web Site: http://www.cepc.com.cn
Post Issue Number: 82-679
CODEN: DJIIAQ

Received	Published
2021-05-19	2022-03-01
Issue Date
2022-03-24

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