DocumentCode :
615417
Title :
Fault diagnosis of the satellite power system based on the Bayesian network
Author :
Siyun Xie ; Xiafu Peng ; Xunyu Zhong ; Chengrui Liu
Author_Institution :
Dept. of Autom., Xiamen Univ., Xiamen, China
fYear :
2013
fDate :
26-28 April 2013
Firstpage :
1004
Lastpage :
1008
Abstract :
The satellite power system is an important piece of the satellite system; targeting on the problems of complex fault mechanisms and uncertainty between fault type and fault symptoms, the method of Bayesian network fault diagnosis in the satellite power system has been raised. In the learning process of Bayesian network structure, this algorithm adopts statistical strategy for the rule library provided by many experts, extracts causal relationship from expert knowledge base, fills in the causal relationship table, thereby sets up the fault diagnosis hierarchical structure model in the satellite power system based on Bayesian network. Simulation shows that the Bayesian network fault diagnosis model is effectively solving the uncertainties in fault diagnosis.
Keywords :
artificial satellites; belief networks; fault diagnosis; learning (artificial intelligence); power engineering computing; power system reliability; statistical analysis; Bayesian network; causal relationship table; fault diagnosis hierarchical structure model; fault mechanism; fault symptom; fault type; learning process; rule library; satellite power system; statistical strategy; Bayes methods; Laboratories; Topology; Voltage control; Bayesian network; fault diagnosis; satellite power system;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science & Education (ICCSE), 2013 8th International Conference on
Conference_Location :
Colombo
Print_ISBN :
978-1-4673-4464-7
Type :
conf
DOI :
10.1109/ICCSE.2013.6554060
Filename :
6554060
Link To Document :
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