Research on Classification Method of Urban Underground Cable Partial Discharge Defects

Author:

Qian Li1,Lingyu Liu2,Guang Han2,Xiaoyun Sun2,Haiqing Zheng2,Jun Zhang1,Baoan Liu1,Kang Guo1

Affiliation:

1. State Grid Hebei Electric Power Co., Ltd.,Shijiazhuang Power Supply Branch,Shijiazhuang,China

2. Shijiazhuang Tiedao University,Shijiazhuang,China

Funder

Department of Education of Hebei Province

Shijiazhuang Tiedao University

Publisher

IEEE

Reference19 articles.

1. Partial discharge pattern recognition based on deep convolutional networks in complex data sources[J];song;High Voltage Technology,2018

2. High voltage cable partial discharge pattern recognition based on convolutional neural network[J];yang;Power Automation Equipment,2018

3. Feature extraction of partial discharge signal based on multi-resolution high order singular spectrum entropy analysis[J];yang;Power Grid Technology,2016

4. PRPD Spectrum Recognition of transformer Based on Multi-layer feature Fusion CNN [J];li;Electrical Measurement & Instrumentation,2020

5. Recurrent Neural Network for Partial Discharge Diagnosis in Gas-Insulated Switchgear

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