CNN-based Classification of Contaminated High Voltage Insulator Surface
Author:
Affiliation:
1. Nazarbayev University,Department of Electrical and Computer Engineering,Nur-Sultan,Kazakhstan
2. Almaty University of Power Engineering and Telecommunications,Department of Power Engineering,Almaty,Kazakhstan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9854509/9854408/09854762.pdf?arnumber=9854762
Reference27 articles.
1. Evaluation of Power Insulator Detection Efficiency with the Use of Limited Training Dataset
2. A Contactless Insulator Contamination Levels Detecting Method Based on Infrared Images Features and RBFNN
3. Fault Detection of Insulators Using Second-order Fully Convolutional Network Model
4. High Voltage Insulators Condition Analysis using Convolutional Neural Network
5. Accurate Surface Condition Classification of High Voltage Insulators based on Deep Convolutional Neural Networks
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1. A fault detection method for transmission line components based on synthetic dataset and improved YOLOv5;International Journal of Electrical Power & Energy Systems;2024-06
2. Stacked Ensemble Deep Learning for Outdoor Insulator Surface Condition Classification: A Profound Study on Water Droplets;IEEE Access;2023
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