DECOUPLING CONTROL METHOD FOR MARINE NUCLEAR POWER PLANT BASED ON NEURAL NETWORK INVERSE SYSTEM

2019 ◽  
Vol 2019.27 (0) ◽  
pp. 1184
Author(s):  
Areai Nuerlan ◽  
Pengfei Wang ◽  
Fuyu Zhao
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Control Method ◽  
Inverse System ◽  
Decoupling Control

Study on Sensor with Mechanical Properties in Nuclear Power Plant with Application of BP Neural Network to Fault Tolerant Control

2013 ◽  
Vol 644 ◽  
pp. 56-59
Author(s):  
Jin Yang Li ◽  
Hong Xia ◽  
Shou Yu Cheng
Keyword(s):  
Neural Network ◽  
Mechanical Properties ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Bp Neural Network ◽  
Nuclear Power ◽  
Control Method ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Level Sensor

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.

Deep rectifier neural network applied to the accident identification problem in a PWR nuclear power plant

2019 ◽  
Vol 133 ◽  
pp. 400-408 ◽  
Author(s):  
Marcelo Carvalho dos Santos ◽  
Victor Henrique Cabral Pinheiro ◽  
Filipe Santana Moreira do Desterro ◽  
Renato Koga de Avellar ◽  
Roberto Schirru ◽  
...  
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Identification Problem
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