Intelligent Safety Monitoring System for Nuclear Power Plant Based on the Convolution Neural Network

Author(s):  
Xu-Tao Bai ◽  
Dan-Dan Sun ◽  
Xiao-Chen Zhang ◽  
Bao-Cheng Sun
Author(s):  
Jung-Soo Kim ◽  
In-Koo Hwang ◽  
Jung-Tak Kim ◽  
Byung-Soo Moon ◽  
Joon Lyou

2013 ◽  
Vol 644 ◽  
pp. 56-59
Author(s):  
Jin Yang Li ◽  
Hong Xia ◽  
Shou Yu Cheng

All kinds of sensor with mechanical properties often can go wrong in nuclear power plant. In this kind of situation, it puts forward a kind of active fault tolerant control method based on the improved BP neural network. Firstly, the method will train sensor by BP neural network. Secondly, it will be established dynamic model bank in all kinds of running state. The system will be detected by using BP neural network real time. When the sensor goes wrong, it will be controled by reconstruction. Taking pressurizer water-level sensor as the case, a simulation experiment was performed on the nuclear power plant simulator. The results showed that the proposed method is valid for the fault tolerant control of sensor in nuclear power plant.


2003 ◽  
Vol 43 (1-4) ◽  
pp. 397-404 ◽  
Author(s):  
K. Nabeshima ◽  
T. Suzudo ◽  
S. Seker ◽  
E. Ayaz ◽  
B. Barutcu ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document