DocumentCode
2269247
Title
Intelligent fault detection and diagnostics in solar plants
Author
Coleman, Andon ; Zalewski, Janusz
Author_Institution
Dept. of Comput. Sci., Florida Gulf Coast Univ., Fort. Myers, FL, USA
Volume
2
fYear
2011
fDate
15-17 Sept. 2011
Firstpage
948
Lastpage
953
Abstract
This paper discusses fault detection and diagnostics in a solar power plant. After reviewing relevant work, description of a data acquisition system for solar plant monitoring is presented and the list of potential faults to be taken care of is given. Then Bayesian belief network is built to intelligently reason about potential causes of faults detected. Finally, a practical implementation of a computer system to retrieve data, extract relevant information, and reason about fault detection in real time is presented.
Keywords
belief networks; data acquisition; fault diagnosis; solar power stations; Bayesian belief network; data acquisition system; fault diagnostics; intelligent fault detection; solar plants; Bayesian methods; Data acquisition; Fault detection; Instruments; Inverters; Power generation; Temperature measurement; data acquisition; fault detection; fault diagnostics; fault tolerance; solar plant;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), 2011 IEEE 6th International Conference on
Conference_Location
Prague
Print_ISBN
978-1-4577-1426-9
Type
conf
DOI
10.1109/IDAACS.2011.6072914
Filename
6072914
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