Imbalanced sample fault diagnosis method for rotating machinery in nuclear power plants based on deep convolutional conditional generative adversarial network

Imbalanced sample fault diagnosis method for rotating machinery in nuclear power plants based on deep convolutional conditional generative adversarial network

Rotating machinery is widely applied in important equipment of nuclear power plants (NPPs), such as pumps and valves. The research on intelligent fault diagnosis of rotating machinery is crucial to ensure the safe operation of related equipment in NPPs. However, in practical applications, data-drive...

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Bibliographic Details
Main Authors:	Zhichao Wang, Hong Xia, Jiyu Zhang, Bo Yang, Wenzhe Yin
Format:	Article
Language:	English
Published:	Elsevier 2023-06-01
Series:	Nuclear Engineering and Technology
Subjects:	Nuclear power plant Imbalanced sample fault diagnosis Deep convolutional neural network Conditional generative adversarial network Rotating machinery
Online Access:	http://www.sciencedirect.com/science/article/pii/S1738573323001092

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