Research on Intelligent Online Monitoring and Robust Self-Correction for Nuclear Reactor Sensors

Xu Fenqin; Yan Xiaoyu; Pang Bo; Zhao Dou; Tu Yan

doi:10.13832/j.jnpe.2024.090019

Volume 46 Issue 5

Oct. 2025

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Article Navigation > Nuclear Power Engineering > 2025 > 46(5): 234-242

Xu Fenqin, Yan Xiaoyu, Pang Bo, Zhao Dou, Tu Yan. Research on Intelligent Online Monitoring and Robust Self-Correction for Nuclear Reactor Sensors[J]. Nuclear Power Engineering, 2025, 46(5): 234-242. doi: 10.13832/j.jnpe.2024.090019

Citation:

Xu Fenqin, Yan Xiaoyu, Pang Bo, Zhao Dou, Tu Yan. Research on Intelligent Online Monitoring and Robust Self-Correction for Nuclear Reactor Sensors[J]. Nuclear Power Engineering, 2025, 46(5): 234-242. doi: 10.13832/j.jnpe.2024.090019

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Research on Intelligent Online Monitoring and Robust Self-Correction for Nuclear Reactor Sensors

doi: 10.13832/j.jnpe.2024.090019

Xu Fenqin^{1, 2
,},
Yan Xiaoyu^{3
,
,},
Pang Bo^{1, 2
,
,},
Zhao Dou³,
Tu Yan³

1.
Department of Nuclear Science and Technology, Shenzhen University (SZU), Shenzhen, Guangdong, 518060, China
2.
Institute of Nuclear Power Operation Safety Technology (INPOST), Affiliated with the National Energy R&D Center on Nuclear Power Operation and Life Management, Shenzhen, Guangdong, 518060, China
3.
Nuclear Power Institute of China, Chengdu, 610213, China

Received Date: 2024-08-15
Rev Recd Date: 2024-11-15

Available Online: 2025-10-15

Publish Date: 2025-10-15

Abstract

Abstract

A novel training dataset processing method with high robustness was proposed to address the poor robustness in data-driven analytic redundant sensor models, and an sensor online monitoring and self-correction method was developed based on a auto-associative multivariate Long Short-Term Memory (LSTM) artificial neural network model. The method was validated using actual sensor measurement data retrieved from a pressurized water reactor engineering test facility. The results indicate that this research method can achieve high-precision and robust reconstruction of sensor signals, hence meets the requirements of online monitoring and robust self-correction of nuclear reactor sensors.
- Nuclear reactor,
- Sensor online monitoring,
- Auto-associative multivariate long short-term memory (LSTM),
- Robust self-correction

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References(24)

References

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