Fault diagnosis for power system based on a special Bayesian network

To deal with a lot of uncertain information existing in the grid when faulted, this article uses a special Bayesian network-Noisy-or, Noisy-and nodes model to build object-oriented Bayesian networks. An error back propagation algorithm is used to train the Bayesian network so as to update the networ...

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Bibliographic Details
Published inTENCON 2015 - 2015 IEEE Region 10 Conference pp. 1 - 6
Main Authors Wang Tao, Zhu Yi, Gao Zhanjun
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2015
Subjects
Bayes methods
Bayesian networks
Circuit breakers
Fault diagnosis
fault probability
Integrated circuit modeling
Noise measurement
Noisy-or and Noisy-and nodes model
parameter learning
Power systems
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Summary:To deal with a lot of uncertain information existing in the grid when faulted, this article uses a special Bayesian network-Noisy-or, Noisy-and nodes model to build object-oriented Bayesian networks. An error back propagation algorithm is used to train the Bayesian network so as to update the network's parameters. Finally a case simulation is presented to prove the accuracy and validity of this method for power system fault diagnosis.
ISBN:9781479986392
1479986399
ISSN:2159-3442
2159-3450
DOI:10.1109/TENCON.2015.7372723