A method for alarming water level of boiler drum on nuclear power plant based on BP Neural Network

2014 ◽  
Author(s):  
Yalei Quan ◽  
Xuhong Yang
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Water Level ◽  
Bp Neural Network ◽  
Nuclear Power ◽  
Boiler Drum

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.

The Research of PWR Steam Generator with Water Level Control Based on RBF Neural Network

2014 ◽  
Vol 1014 ◽  
pp. 344-350
Author(s):  
Xu Hong Yang ◽  
Yang Jian ◽  
Cheng Chen Feng ◽  
Yang Xue
Keyword(s):  
Neural Network ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Water Level ◽  
Steam Generator ◽  
Nuclear Power ◽  
Rbf Neural Network ◽  
Stable Operation ◽  
Level Control ◽  
Non Linear System

In the steam generator with water level control system of nuclear power plant, there are various uncertainties in the controlled devices. Any actual system had certain nonlinear. Because of the steam generator is very important equipment in nuclear power plants, water level control plays a decisive role for the safe operation of nuclear power plant and it required stable operation and fast response of the whole system. For the highly complex, non-linear system , the traditional cascade PID control had been used cannot obtain satisfactory control effect, this paper try to use RBF neural network to optimize the PID parameters. The simulation experiments show that: the rbf neural network optimized controller made the control system’s robustness and control quality superior than the traditional PID controller, and described the method can be applied more widely.

Water Level Control of Steam Generator in Nuclear Power Plant Based on Intelligent MFAC-PID

2021 ◽  
Author(s):  
Yonglu Du ◽  
Haotian Li ◽  
Minrui Fei ◽  
Ling Wang ◽  
Pinggai Zhang ◽  
...  
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Water Level ◽  
Steam Generator ◽  
Nuclear Power ◽  
Level Control

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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