Evaluation of transfer learning approaches for partial discharge classification in hydrogenerators-Reference-Cited by-同舟云学术

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Evaluation of transfer learning approaches for partial discharge classification in hydrogenerators

Published:2022-11-17 Issue: Volume: Page:
ISSN:
Container-title:2022 Workshop on Communication Networks and Power Systems (WCNPS)
language:
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Author:

Lopes Frederico H. R.¹^ORCID,Zampolo Ronaldo F.¹,Oliveira Rodrigo M. S.¹^ORCID,Dmitriev Victor¹^ORCID

Affiliation:

1. Electrical Engineering Graduate Program, Federal University of Pará,Belém,Pará,Brazil

Funder

ANEEL

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9969577/9969673/09969682.pdf?arnumber=9969682

Reference18 articles.

1. Deep neural networks for understanding and diagnosing partial discharge data

2. Partial Discharge Classification Using Deep Learning Methods-Survey of Recent Progress;barrios;Energies,2019

3. A Novel Application of Deep Belief Networks in Learning Partial Discharge Patterns for Classifying Corona, Surface, and Internal Discharges

4. A Convolutional Neural Network-Based Model for Multi-Source and Single-Source Partial Discharge Pattern Classification Using Only Single-Source Training Set

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Novel Self-Organizing Probability Maps Applied to Classification of Concurrent Partial Discharges from Online Hydro-Generators;Energies;2024-05-04

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