scholarly journals A Correlation-Based Feature Selection Algorithm for Operating Data of Nuclear Power Plants

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Yuxuan He ◽  
Hongxing Yu ◽  
Ren Yu ◽  
Jian Song ◽  
Haibo Lian ◽  
...  

Nuclear power plant operating data are characterized by a large variety, strong coupling, and low data value density. When using machine learning techniques for fault diagnosis and other related research, feature selection enables dimensionality reduction while maintaining the physical meaning of the original features, thus improving the computational efficiency and generalization ability of the learning model. In this paper, a correlation-based feature selection algorithm is developed to implement feature selection of nuclear power plant operating data. The proposed algorithm is verified by experiments and compared with traditional correlation-based feature selection algorithms. The experiments and comparison results show that the proposed algorithm is effective in realizing the dimensionality reduction of nuclear power plant operating data.

2014 ◽  
Vol 989-994 ◽  
pp. 2097-2100
Author(s):  
Zheng Zhang ◽  
Hai Bo He ◽  
Hao Liang Lu

In order to satisfy the calculation requirements of nuclear power plant operating in different conditions, the integration and combination of reactor core computation modules have been proposed. By writing logical language instructions, and then read by interpreter, the engineering designers can make grammatical analysis, lexical analysis, semantic analysis and information extraction. In Linux system environment, the interpreter can fulfill computational tasks based on the actual operating parameters of nuclear power plant. The comparison results indicate that the calculated results obtained by the interpreter language are correct. Therefore, it also demonstrates that the interpreter language is valid.


Author(s):  
Ting-Han Lin ◽  
Shun-Chi Wu ◽  
Hwai-Pwu Chou

A novel two-stage feature extraction scheme is proposed in this paper for eliciting discriminant information contained in the data from various nuclear power plant (NPP) sensors to facilitate event identification. Based on the idea of sensor type-wise block projection, the primal features can be extracted without losing the intrinsic structure contained in the multi-sensor data. The features are then subject to further dimensionality reduction by selecting the sensors that are most relevant to the events under consideration. Results from detailed experiments with data generated from a simulator of Taiwan Maanshan NPP illustrate the efficacy of the proposed scheme.


2016 ◽  
Vol 19 (4) ◽  
pp. 241-248
Author(s):  
Son An Nguyen ◽  
Nguyen Trung Tran ◽  
Tuan Quoc Tran ◽  
Cuong Quang Ly ◽  
Lan Thi Ha Le ◽  
...  

In the operation of a nuclear power plant (NPP), to adjust the capacity of NPP is necessary. When the NPP capacity is changed the nuclear fission is also changed. The methods used in changing the capacity of NPP include: changing the boron concentration, changing the position of the control rod groups, and changing the boron concentrations and the position of the control rod groups together. This report presents some results of the research, measurement boron concentrations when nuclear power plans OPR1000 critically state in the cases of ARO, ARI SB, ARI R1, R5 = 191 cm on the basis of the bisection method in the boron concentrations adjustment. The experiment is performed on core the simulator for OPR 1000 nuclear power plant. The results in the 4 cases were similar with NPP operating data using OPR1000 reactor.


2018 ◽  
Vol 3 (3) ◽  
pp. 379
Author(s):  
Chelebiev R.A. ◽  
Skomorokhov A.O.

In this paper, it is investigated nuclear power plant operating data which was obtained from reactor main coolant pumps (MCP) of the third isolated generating plant of Kalinin NPP. It is necessary permanent monitoring for state of all pump components since breakdown of a reactor coolant pump leads to substantial economic losses. It is installed over 50 sensors of different control systems at the every MCP. Received data is stored but it is not analysed for the purpose of discovering  joint dependencies between equipment pieces and unobvious, hidden trends of accident propagation. In this work, it was proposed techniques for detection of hidden anomalies and MCP operating regularity based on factor analysis, clustering and linear regression models. It was written a Python script which automates necessary calculations.


Author(s):  
Dong Ning ◽  
Yongdong Wang ◽  
Hui Li ◽  
Zhanggen Bao

This paper is to compare the sections on materials between ASME-BVC and RCC-M code. This paper states the layout structure and the content about NPP materials specified in the two codes and shows the comparison results. This paper emphasizes particularly on the basic differences between two codes; ASME code focuses on fracture toughness requirements for pressure-retaining ferrite materials and RCC-M code focuses on Susceptibility to intergranular corrosion for austenitic and austenitic-ferrite stainless steel.


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