Deep Learning-Based Partial Transfer Fault Diagnosis Methodology for Electromechanical Systems-Reference-Cited by-同舟云学术

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Deep Learning-Based Partial Transfer Fault Diagnosis Methodology for Electromechanical Systems

Published:2023-09-12 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA)
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Author:

Arellano-Espitia Francisco¹,Delgado-Prieto Miguel²,Valls-Perez Joan¹,Saucedo-Dorantes Juan Jose³,Osornio-Rios Roque Alfredo³

Affiliation:

1. Technical University of Catalonia,MCIA Research Center,Departament of Electronic Engineering,Terrassa,Spain

2. Technical University of Catalonia,MCIA Research Center,Departament of Automatic Control,Terrassa,Spain

3. Autonomous University of Queretaro,HSPdigital CA-Mecatronica Engineering Faculty,San Juan del Rio,Mexico

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10275065/10275329/10275407.pdf?arnumber=10275407

Reference21 articles.

1. Generative adversarial networks for data augmentation in machine fault diagnosis

2. Generative Adversarial Networks;goodfellow;Advances in Neural Information Processing System,2014

3. Partial Transfer Learning with Selective Adversarial Networks

4. A Fine-Grained Adversarial Network Method for Cross-Domain Industrial Fault Diagnosis

5. Deep transfer network with joint distribution adaptation: A new intelligent fault diagnosis framework for industry application

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