Source location and mass estimation in loose parts monitoring of LWR's

1985 ◽  
Vol 15 ◽  
pp. 583-594 ◽  
Author(s):  
B.J. Olma
2000 ◽  
Vol 36 (2) ◽  
pp. 109-122 ◽  
Author(s):  
Jung-Soo Kim ◽  
Joon Lyou

2012 ◽  
Vol 23 (5) ◽  
pp. 054011 ◽  
Author(s):  
Yuanfeng He ◽  
Yanlong Cao ◽  
Jiangxin Yang ◽  
Chunbiao Gan

2020 ◽  
Vol 52 (4) ◽  
pp. 846-855
Author(s):  
Seongin Moon ◽  
Seongjin Han ◽  
To Kang ◽  
Soonwoo Han ◽  
Munsung Kim

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.


2014 ◽  
Vol 70 ◽  
pp. 242-248
Author(s):  
Li-Xian Fang ◽  
Tian-Tian Ji ◽  
Fu Zeng ◽  
Wei Zhang ◽  
Yong-Cheng Xie ◽  
...  

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