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Nuclear Technology Volume 209, 2023 - Issue 9
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Research Articles

A CNN-LSTM–Based Model to Fault Diagnosis for CPR1000

Changan Rena University of South China, School of Nuclear Science and Technology, Hengyang, Hunan, 421000, China;b Hunan Institute of Technology, School of Computer Science and Engineering, Hengyang, Hunan, 421000, ChinaView further author information
,
He Lic Ministry of Ecology and Environment, Nuclear and Radiation Safety Center, Beijing, ChinaView further author information
,
Jichong Leia University of South China, School of Nuclear Science and Technology, Hengyang, Hunan, 421000, ChinaORCID Iconhttps://orcid.org/0000-0002-0380-2792View further author information
ORCID Icon,
Jie Liud University of South China, School of Computing/Software, Hengyang, Hunan, 421000, ChinaView further author information
,
Wei Lia University of South China, School of Nuclear Science and Technology, Hengyang, Hunan, 421000, ChinaView further author information
,
Kekun Gaod University of South China, School of Computing/Software, Hengyang, Hunan, 421000, ChinaView further author information
,
Guocai Huangd University of South China, School of Computing/Software, Hengyang, Hunan, 421000, ChinaView further author information
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Xiaohua Yanga University of South China, School of Nuclear Science and Technology, Hengyang, Hunan, 421000, China;d University of South China, School of Computing/Software, Hengyang, Hunan, 421000, ChinaCorrespondence[email protected]
View further author information
&
Tao Yua University of South China, School of Nuclear Science and Technology, Hengyang, Hunan, 421000, ChinaView further author information
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Pages 1365-1372 | Received 28 Apr 2022, Accepted 30 Mar 2023, Published online: 11 May 2023

References

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