Monitoring and fault diagnosis of the steam generator system of a nuclear power plant using data-driven modeling and residual space analysis

2005 ◽  
Vol 32 (9) ◽  
pp. 897-912 ◽  
Author(s):  
B. Lu ◽  
B.R. Upadhyaya
2021 ◽  
Vol 9 ◽  
Author(s):  
Guang Hu ◽  
Taotao Zhou ◽  
Qianfeng Liu

Data-driven machine learning (DDML) methods for the fault diagnosis and detection (FDD) in the nuclear power plant (NPP) are of emerging interest in the recent years. However, there still lacks research on comprehensive reviewing the state-of-the-art progress on the DDML for the FDD in the NPP. In this review, the classifications, principles, and characteristics of the DDML are firstly introduced, which include the supervised learning type, unsupervised learning type, and so on. Then, the latest applications of the DDML for the FDD, which consist of the reactor system, reactor component, and reactor condition monitoring are illustrated, which can better predict the NPP behaviors. Lastly, the future development of the DDML for the FDD in the NPP is concluded.


Author(s):  
Zhaoxu Chen ◽  
Xianling Li ◽  
Zhiwu Ke ◽  
Mo Tao ◽  
Yi Feng

This paper proposes a data-driven fault detection approach for nuclear power plant. The approach starts from input and output (I/O) data obtained from operating data of industrial process. Due to the model is not explicitly appeared, the proposed approach is named as implicit model approach (IMA). Residual generator is obtained directly from I/O data rather than from the mechanism, based which the algorithm of IMA-based fault detection is proposed. The main advantage of IMA-based fault detection is that it can circumvent complicated model identification. The approach generates parameterized matrices of residual signal inspired by subspace relevant technology without any prior knowledge about mechanisms of the plant. Fault information has been injected to a simulating platform of a compact reactor in the simulation part, by which we verify the effectiveness of IMA-based fault detection.


2005 ◽  
Vol 235 (23) ◽  
pp. 2477-2484 ◽  
Author(s):  
Seong Sik Hwang ◽  
Hong Pyo Kim ◽  
Joung Soo Kim ◽  
Kenneth E. Kasza ◽  
Jangyul Park ◽  
...  

2019 ◽  
pp. 119-126

Aplicación de la Teoría de Perturbación – Método Diferencial- al Análisis de Sensibilidad en Generadores de Vapor de Centrales Nucleares PWR-Caso Angra I Aplication of the Perturbation Theory- Differential Methodto Sensibility Análisis in PWR Nuclear Power Plant Steam Generator- Angra I Giol Sanders R, Andrade de Lima F, Marques A, Gallardo A, Bruna M, Zúñiga A Institución Peruano de Energía Nuclear Universidad Federal de Rio De Janeiro-Brasil DOI: https://doi.org/10.33017/RevECIPeru2011.0033/ RESUMEN En este trabajo basado en la tesis del Magíster Roberto Giol S. [1] presenta una aplicación del formalismo diferencial de la teoría de perturbación a un modelo termohidráulico homogéneo de simulación del comportamiento estacionario de uno de los generadores de vapor de la Central Nuclear tipo PWR Angra I del Brasil. Se desarrolla un programa de cálculo PERGEVAP tomando como base el código GEVAP de Souza[2]. El programa PERGEVAP permite realizar cálculos de sensibilidad de funcionales lineales (temperatura media del primario)y no lineales (flujo de calor medio a través de las paredes de los tubos del generador) con relación a las variaciones de ciertos parámetros termo-hidráulicos(flujo másico del primario, calor específico, etc), Los resultados obtenidos con este formalismo son luego comparados con los obtenidos del cálculo directo con el propio código GEVAP, pudiéndose verificar una excelente concordancia. Este método se muestra promisorio para efectuar cálculos repetitivos asociados al diseño y análisis de Seguridad de los componentes de las Centrales Nucleares. Descriptores: teoría de perturbación, método diferencial, sensibilidad, generador de vapor, central nuclear PWR. ABSTRACT This report presents an application of the differential approach of the perturbation theory to an homogeneous model of a PWR steam generator in the Angra 1 Nuclear Power Plan in Brazil under steady-state conditions. Program PERGEVAP was built fom the code GEVAP developed by Souza and allows sensitivity calculations of linear (average primary loop temperature) and non-linear (average heat flux) functionals due to variations in some thermo-hydraulics parameters (flow rate, specific heat, , etc). Results obtained with this approach are then compared with direct calculations performed using the GEVAP code, with excellent agreements. The method has good potential to treat repeated calculations needed in the design and safety analysis of the Nuclear Plant components. Keywords: perturbation theory, differential method, steam generator, PWR nuclear Power Plant.


2021 ◽  
Author(s):  
Yonglu Du ◽  
Haotian Li ◽  
Minrui Fei ◽  
Ling Wang ◽  
Pinggai Zhang ◽  
...  

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