Mass estimation of loose parts in nuclear power plant based on multiple regression

2012 ◽  
Vol 23 (5) ◽  
pp. 054011 ◽  
Author(s):  
Yuanfeng He ◽  
Yanlong Cao ◽  
Jiangxin Yang ◽  
Chunbiao Gan
2010 ◽  
Vol 437 ◽  
pp. 384-388
Author(s):  
Hua Wen Zheng ◽  
Yan Long Cao ◽  
Jiang Xin Yang ◽  
Yuan Feng He

A new method for mass estimation of loose parts in nuclear power plant (NPP) based on the support vector machine (SVM) was proposed. It includes analyses of the relationship between the impact signals’ frequency spectrum and the mass of loose part, then formation of a vector consisting of linear predictive coding (LPC) parameters, which represent the shape of spectrum of impact signal. Using the vector as input data and the mass of loose part as the output data to train the SVM, the mass estimation can be done by the trained SVM model. Experimental results show that the method has higher accuracy and easier to achieve than the traditional methods. It provides a new way for mass estimation of loose part in NPP.


2004 ◽  
Vol 231 (1) ◽  
pp. 99-107 ◽  
Author(s):  
Young Woo Chang ◽  
Jae-Cheon Jung ◽  
Poong-Hyun Seong

2020 ◽  
Vol 39 (5) ◽  
pp. 6339-6350
Author(s):  
Esra Çakır ◽  
Ziya Ulukan

Due to the increase in energy demand, many countries suffer from energy poverty because of insufficient and expensive energy supply. Plans to use alternative power like nuclear power for electricity generation are being revived among developing countries. Decisions for installation of power plants need to be based on careful assessment of future energy supply and demand, economic and financial implications and requirements for technology transfer. Since the problem involves many vague parameters, a fuzzy model should be an appropriate approach for dealing with this problem. This study develops a Fuzzy Multi-Objective Linear Programming (FMOLP) model for solving the nuclear power plant installation problem in fuzzy environment. FMOLP approach is recommended for cases where the objective functions are imprecise and can only be stated within a certain threshold level. The proposed model attempts to minimize total duration time, total cost and maximize the total crash time of the installation project. By using FMOLP, the weighted additive technique can also be applied in order to transform the model into Fuzzy Multiple Weighted-Objective Linear Programming (FMWOLP) to control the objective values such that all decision makers target on each criterion can be met. The optimum solution with the achievement level for both of the models (FMOLP and FMWOLP) are compared with each other. FMWOLP results in better performance as the overall degree of satisfaction depends on the weight given to the objective functions. A numerical example demonstrates the feasibility of applying the proposed models to nuclear power plant installation problem.


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