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

Jin Yang Li; Hong Xia; Shou Yu Cheng

doi:10.4028/www.scientific.net/AMR.644.56

Paper Titles

Study of Adaptive Control System of Magneto-Rheological Fluid Dampers with Mechanical Properties Subject to Impact Loading
p.37

Research on Performance Influence of the Coin Recognition Device by Coil Parameters Based on Mechanical Properties
p.42

The Development of Automatic Electronic Granulation Counter Based on Mechanical Properties
p.47

Study on the Online Detecting Technology for Partial Discharge of Power Equipment with Mechanical Properties
p.51

Study on Sensor with Mechanical Properties in Nuclear Power Plant with Application of BP Neural Network to Fault Tolerant Control
p.56

Research on the Remote Monitoring System of Photovoltaic Power Station Based on CAN Bus and GPRS with Mechanical Properties
p.60

Research on Electronic Expansion Valve Opening Mechanical Properties of Multi-Link Inverter Air-Con Based on Neural Network
p.64

Application of Fuzzy Neural Network to Fault Diagnosis of Sensor with Mechanical Properties in Nuclear Power Plant
p.68

Intelligent Control of Valve-Controlled Electro-Hydraulic System in Erecting Device Based on Mechanical Mechanics
p.72

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 644Study on Sensor with Mechanical Properties in...

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

Abstract:

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.

You might also be interested in these eBooks

Advanced Research on Intelligent Systems and Mechanical Engineering

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 644)

Pages:

56-59

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.644.56

Citation:

Cite this paper

Online since:

January 2013

Authors:

Jin Yang Li, Hong Xia, Shou Yu Cheng

Keywords:

Active Fault Tolerant Control, BP Neural Network (BPNN), Nuclear Power Plant (NPP)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Zhihong Deng. Fault Tolerant Control of Nuclear Power Plant Steam Generator on Ovation System. Harbin Engineering University, (2009).

Google Scholar

[2] Jia Wang. Fault Diagnoss and Tolarent Control Research of Small Ractor. Harbin Engineering University, (2006).

Google Scholar

[3] Zhihong Deng, Xiaocheng Shi, Guoqing Xia, Mingyu Fu. Fault tolerant control for steam generators in nuclear power plant. Nuclear Power Engineering, Vol. 31(2010), p: 107-111, 116.

Google Scholar

[4] Donghua Zhou, Yinzhong Ye. Modern Fault Diagnosis and Fault Tolerant Control. Tsinghua University Press, (2000).

Google Scholar

[5] Liqun Han. Artificial Neural Network Tutorial. Beijing University of Posts and Telecommunications Press, (2006).

Google Scholar

[6] Wei Li, Ke Ma, Baoyun Lu. Predictive active fault-tolerant control of multiple models based on BP networks. Journal of Gansu Sciences, Vol. 20(2008), p: 107-111.

Google Scholar