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Fault prediction method for nuclear power machinery based on bayesian PPCA recurrent neural network model

NUCLEAR ENERGY SCIENCE AND ENGINEERING | Updated：2021-01-26

- Fault prediction method for nuclear power machinery based on bayesian PPCA recurrent neural network model Cover Article Enhanced Publication
- Nuclear Science and Techniques Vol.31, Issue 8, (2020)
- Affiliations：
  
  State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment, China Nuclear Power Engineering Company Ltd.,Shenzhen,China,518172;School of Mechanical and Automotive Engineering, South China University of Technology,Guangzhou,China,510640;Dongchuan Road,Shanghai,China,200240
- Author bio：
- Funds：
- DOI：10.1007/s41365-020-00792-9 CLC：
- Published：01 August 2020，
  
  Published Online：29 July 2020，
  
  Received：17 April 2020，
  
  Revised：10 June 2020，
  
  Accepted：14 June 2020
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Cite this article
Jun Ling, Gao-Jun Liu, Jia-Liang Li, et al. Fault prediction method for nuclear power machinery based on bayesian PPCA recurrent neural network model. [J]. Nuclear Science and Techniques 31(8):75(2020)
DOI：

Jun Ling, Gao-Jun Liu, Jia-Liang Li, et al. Fault prediction method for nuclear power machinery based on bayesian PPCA recurrent neural network model. [J]. Nuclear Science and Techniques 31(8):75(2020) DOI： 10.1007/s41365-020-00792-9.

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