Deep Ensemble Model for Unknown Partial Discharge Diagnosis in Gas-Insulated Switchgears Using Convolutional Neural Networks

Deep Ensemble Model for Unknown Partial Discharge Diagnosis in Gas-Insulated Switchgears Using Convolutional Neural Networks

Deep neural networks (DNNs) are widely used for fault classification using partial discharges (PDs) to evaluate various electrical apparatuses and achieve high classification accuracy pertaining to trained PD faults. However, there is a risk of false alarm in the case of untrained PD faults because...

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Bibliographic Details
Main Authors: Vo-Nguyen Tuyet-Doan, Ha-Anh Pho, Byeongho Lee, Yong-Hwa Kim
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Fault diagnosis
convolutional neural network (CNN)
ensemble model
partial discharges (PDs)
gas-insulated switchgear (GIS)
Online Access:https://ieeexplore.ieee.org/document/9444415/

Internet

https://ieeexplore.ieee.org/document/9444415/

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