Monitoring of Composite Insulators in Transmission Lines: A Hydrophobicity Diagnostic Method Using Aerial Images and Residual Neural Networks
Author:
Affiliation:
1. Mechatronic Engineering and Automation, Foshan University, Foshan, China
2. EHV Power Transmission Company of China Southern Power Grid, Guangzhou Bureau, Guangzhou, China
3. Guangdong Shuangdian Technology Company, Ltd., Dongguan, China
Funder
Guangdong General University Innovation Team
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Energy Engineering and Power Technology
Link
http://xplorestaging.ieee.org/ielx7/61/10192508/10049209.pdf?arnumber=10049209
Reference26 articles.
1. Using a pattern recognition-based technique to assess the hydrophobicity class of silicone rubber materials
2. Hydrophobicity classification of composite insulators based on convolutional neural networks
3. On-line estimating the level of hydrophobicity of composite insulators using the digital images
4. Estimation of the Hydrophobicity of a Composite Insulator Based on an Improved Probabilistic Neural Network
5. Experimental investigation on composite insulators AC flashover performance with fan-shaped non-uniform pollution under electro-thermal stress
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1. Influence of inclination angle on the pollution flashover voltage of contaminated silicone rubber;IET Science, Measurement & Technology;2024-08-22
2. A Fault Detection Method for Power Transmission Lines Using Aerial Images;2024 International Conference on Unmanned Aircraft Systems (ICUAS);2024-06-04
3. Hydrophobicity classification of polymeric insulators using a masked autoencoder model in vision transformer;Computers and Electrical Engineering;2024-05
4. Image Visibility Patch Aided Hydrophobic Class Detection of Silicone Rubber Insulators Employing Bi-LSTM Network;2023 IEEE 3rd International Conference on Smart Technologies for Power, Energy and Control (STPEC);2023-12-10
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