Study on Fault Diagnosis Model of Condensate and Feed Water System Based Information Fusion

Author

Ma, Jie ; Zhang, Yusheng ; Guo, Lifeng ; Zhang, Jun

Author_Institution

Coll. of Naval Archit. & Power, Naval Univ. of Eng., Wuhan, China

fYear

2010

fDate

25-27 June 2010

Firstpage

2092

Lastpage

2096

Abstract

Based on the analysis of condensate and feed water system, a fault knowledge repository is established considering operation experience. The D-S inference of Information Fusion theory has the ability of dealing with uncertain information and Artificial Neural Network (ANN) has the advantage of high tolerance and robust. In this paper, a model for fault diagnosis utilizing D-S theory of evidence together with BP network is presented and introduced to the diagnosis of condensate and feed water system. The simulation experiment proves that the system is able to improve the reliability of the diagnosis and decrease the uncertainty markedly.

Keywords

fault diagnosis; inference mechanisms; neural nets; nuclear power stations; sensor fusion; artificial neural network; condensate water system; fault diagnosis model; feed water system; information fusion theory; Artificial neural networks; Atmospheric modeling; Fault diagnosis; Feeds; Monitoring; Training; Valves; BP neural network; Condensate and feed water system; D-S inference; Fault diagnosis; Information fusion;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Control Engineering (ICECE), 2010 International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-6880-5

Type

conf

DOI

10.1109/iCECE.2010.515

Filename

5629923