A fault diagnosis method based on Auxiliary Classifier Generative Adversarial Network for rolling bearing

Chunming Wu; Zhou Zeng

doi:10.1371/journal.pone.0246905

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Open Access

Peer-reviewed

Research Article

A fault diagnosis method based on Auxiliary Classifier Generative Adversarial Network for rolling bearing

Chunming Wu,

Roles Conceptualization, Formal analysis, Funding acquisition, Supervision, Writing – review & editing

Affiliations Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education, Northeast Electric Power University, Jilin, China, Department of Electrical Engineering, Northeast Electric Power University, Jilin, China
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Zhou Zeng

Roles Data curation, Methodology, Software, Writing – original draft

* E-mail: 1143879389@qq.com

Affiliation Department of Electrical Engineering, Northeast Electric Power University, Jilin, China

https://orcid.org/0000-0002-2222-6807

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A fault diagnosis method based on Auxiliary Classifier Generative Adversarial Network for rolling bearing

Chunming Wu,
Zhou Zeng

Published: March 1, 2021
https://doi.org/10.1371/journal.pone.0246905

About the Authors

Chunming Wu

Roles Conceptualization, Formal analysis, Funding acquisition, Supervision, Writing – review & editing

Affiliations Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education, Northeast Electric Power University, Jilin, China, Department of Electrical Engineering, Northeast Electric Power University, Jilin, China

Zhou Zeng

Roles Data curation, Methodology, Software, Writing – original draft

* E-mail: 1143879389@qq.com

Affiliation Department of Electrical Engineering, Northeast Electric Power University, Jilin, China

https://orcid.org/0000-0002-2222-6807

Competing Interests

The authors have declared that no competing interests exist.

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Electrical faults
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Vibration
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Signal processing
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Gaussian noise
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Damage mechanics
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Game theory
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Deep learning
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Pollution
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