Development of deep reinforcement learning-based fault diagnosis method for rotating machinery in nuclear power plants

G Qian, J Liu - Progress in Nuclear Energy, 2022 - Elsevier
Rotating machinery fault can cause accidents like loss of flow or turbine trip that seriously
threaten the operation safety of nuclear power plants (NPPs). Artificial intelligence …

Fault diagnosis based on gated recurrent unit network with attention mechanism and transfer learning under few samples in nuclear power plants

G Qian, J Liu - Progress in Nuclear Energy, 2023 - Elsevier
Fault diagnosis (FD) of rotating machines is critical to the safety and economic operation of
nuclear power plants (NPPs). Gated Recurrent Unit (GRU) is a gating mechanism in …

[HTML][HTML] Fault diagnosis techniques for nuclear power plants: a review from the artificial intelligence perspective

B Qi, J Liang, J Tong - Energies, 2023 - mdpi.com
Fault diagnosis plays an important role in complex and safety-critical systems such as
nuclear power plants (NPPs). With the development of artificial intelligence (AI), extensive …

Fault diagnosis based on conditional generative adversarial networks in nuclear power plants

G Qian, J Liu - Annals of Nuclear Energy, 2022 - Elsevier
Fault diagnosis techniques can detect abnormal states of equipment or systems, give
warning information timely, help to optimize the maintenance schedule, reduce unplanned …

[HTML][HTML] Imbalanced sample fault diagnosis method for rotating machinery in nuclear power plants based on deep convolutional conditional generative adversarial …

Z Wang, H Xia, J Zhang, B Yang, W Yin - Nuclear Engineering and …, 2023 - Elsevier
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 …

[HTML][HTML] A review on data-driven condition monitoring of industrial equipment

R Qi, J Zhang, K Spencer - Algorithms, 2022 - mdpi.com
This paper presents an up-to-date review of data-driven condition monitoring of industrial
equipment with the focus on three commonly used equipment: motors, pumps, and bearings …

[HTML][HTML] Rapid identification of green tea varieties based on FT-NIR spectroscopy and LDA/QR

J Wang, X Wu, J Zheng, B Wu - Food Science and Technology, 2022 - SciELO Brasil
There are many substances beneficial to human body in tea. In this study, we put forward
innovative strategies to quickly and harmlessly identify Chinese green tea varieties. Near …

An improved generative adversarial network for fault diagnosis of rotating machine in nuclear power plant

Z Wang, H Xia, W Yin, B Yang - Annals of Nuclear Energy, 2023 - Elsevier
Due to the wide application and high safety requirements of rotating machines in nuclear
power plants (NPPs), it has received more and more attention. The rotating machines fault …

Fault diagnosis using imbalanced data of rolling bearings based on a deep migration model

H Wang, X Zhang - IEEE Access, 2024 - ieeexplore.ieee.org
To address the problem that uneven sample distribution can affect the accuracy and stability
of fault diagnosis outcomes, we propose a deep transfer learning-Res2Net-convolutional …

A time-saving fault diagnosis using simplified fast GAN and triple-type data transfer learning

H Zhong, S Yu, H Trinh, R Yuan… - Structural Health …, 2024 - journals.sagepub.com
Existing intelligent fault diagnosis approaches demand substantial data for training
diagnostic models. However, factors such as the inherent characteristics of bearings …