期刊论文

Xie, Jinsen(jinsen_xie@usc.edu.cn);Zhou, Jianliang(zjl@usc.edu.cn)

英文

Energies

1996-1073

2022

15

22

8629-

10.3390/en15228629

Conceptualization, B.L. and J.L.; methodology, B.L.; software, J.L.; validation, J.X.; formal analysis, B.L.; investigation, B.L.; resources, B.L.; data curation, J.L.; writing—original draft preparation, B.L.; writing—review and editing, J.L.; visualization, J.Z.; supervision, J.X.; project administration, J.X.; funding acquisition, J.Z. All authors have read and agreed to the published version of the manuscript. This work is supported by the National Natural Science Foundation of China (Grant No.71974091 and No.12175101), Scientific Research Fund of Hunan Provincial Education Department (Grant No.18C0414), Natural Science Foundation of Hunan province (Grant No.2022JJ30481), and the Postgraduate Scientific Research Innovation Project of Hunan Province (CX20220970).

本校为第一机构

As artificial intelligence technology has progressed, numerous businesses have used intelligent diagnostic technology. This study developed a deep LSTM neural network for a nuclear power plant to defect diagnostics. PCTRAN is used to accomplish data extraction for distinct faults and varied fault degrees of the PCTRAN code, and some essential nuclear parameters are chosen as feature quantities. The training, validation, and test sets are collected using random sampling at a ratio of 7:1:2, and the proper hyperparameters are selected to construc...