Power Transformer Fault Diagnosis Based on DGA Using a Convolutional Neural Network With Noise in Measurements

Power Transformer Fault Diagnosis Based on DGA Using a Convolutional Neural Network With Noise in Measurements

Fault type diagnosis is a very important tool to maintain the continuity of power transformer operation. Dissolved gas analysis (DGA) is one of the most effective and widely used techniques for predicting the power transformer fault types. In this paper, a convolutional neural network (CNN) model is...

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Bibliographic Details
Main Authors: Ibrahim B. M. Taha, Saleh Ibrahim, Diaa-Eldin A. Mansour
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Power transformer
fault diagnosis
convolution neural network
noises in measurements
Online Access:https://ieeexplore.ieee.org/document/9505669/

Internet

https://ieeexplore.ieee.org/document/9505669/

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