Fault Diagnosis of System-Level Equipment with a Deep Learning Framework

Kexuan Wang; Chunyang Zeng; Xiaoliang Zhu

doi:10.1051/e3sconf/202126701043

All issues

Volume 267 (2021)

E3S Web Conf., 267 (2021) 01043

References

Open Access

Issue		E3S Web Conf. Volume 267, 2021 7^th International Conference on Energy Science and Chemical Engineering (ICESCE 2021)


Article Number		01043
Number of page(s)		5
Section		Energy Development and Utilization and Energy-Saving Technology Application
DOI		https://doi.org/10.1051/e3sconf/202126701043
Published online		04 June 2021

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[1] Y Zhao, Q Zhang and C L Dong. Design and implementation of nuclear power plant fault diagnosis expert system based on DUCG[J]. Atomic Energy Science and Technology, 2016. [Google Scholar]

[2] J Shi, et al. Default diagnosing system of steam generator for nuclear power plant[J]. Journal of Harbin Engineering University, 2001. [Google Scholar]

[3] G Zhou, Y Li. Application of Integrated Neural Network Method to Fault Diagnosis of Nuclear Steam Generator[J]. Atomic Energy ence and Technology, 2009. [Google Scholar]

[4] X G Lin, X W Jiang, T Liu, et al. Application of genetic neural network in steam generator fault diagnosing[J]. Nuclear Power Engineering, 2005. [Google Scholar]

[5] L D Gu. Application and research of energy-saving technology in urban thermal power plants[D]. Southeast University, 2018. [Google Scholar]