Image-Based Partial Discharge Identification in High Voltage Cables Using Hybrid Deep Network-Reference-Cited by-同舟云学术

Image-Based Partial Discharge Identification in High Voltage Cables Using Hybrid Deep Network

Published:2023 Issue: Volume:11 Page:50325-50333
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Aldosari Obaid¹^ORCID,Aldowsari Mohammed A.²,Batiyah Salem Mohammed³^ORCID,Kanagaraj N.¹

Affiliation:

1. Department of Electrical Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Wadi Ad-Dawasir, Saudi Arabia

2. Department of Electrical Engineering, College of Engineering, King Khaled University, Abha, Saudi Arabia

3. Department of Electrical and Electronics Engineering Technology, Yanbu Industrial College, Yanbu Industrial, Al Madinah Al Munawwarah, Saudi Arabia

Funder

Deputyship for Research & Innovation, Ministry of Education, Saudi Arabia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10129861.pdf?arnumber=10129861

Reference23 articles.

1. Partial Discharge Data Augmentation of High Voltage Cables based on the Variable Noise Superposition and Generative Adversarial Network

2. Albumentations: Fast and Flexible Image Augmentations

3. Partial Discharge Classification in Power Electronics Applications using Machine Learning

4. Sensing approaches on paper-based devices: a review

5. A Convolutional Neural Network-Based Deep Learning Methodology for Recognition of Partial Discharge Patterns from High-Voltage Cables

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