DocumentCode :
577819
Title :
The method of multi-sources fault diagnosis in gas turbine & compressor unit based on SDG and Bayes theory
Author :
Song, Yong-jie ; Xu, Bao-chang
Author_Institution :
Dept. of Autom., China Univ. of Pet. (Beijing), Beijing, China
fYear :
2012
fDate :
6-8 July 2012
Firstpage :
2973
Lastpage :
2976
Abstract :
With the development of Natural Gas Pipeline in China, gas turbine & compressor unit has been widely used, so the fault diagnosis of its equipment is important particularly. In this paper, the method based on SDG (Signed Directed Graph) and Bayes theory is applied to fault diagnosis of the equipment. According to SDG model and Bayes theory, this method finds the consistent path and gets the optimizing model of the diagnosis. Then the optimal combination is calculated by implicit enumeration method. Finally, this method is applied to the lubrication system of gas turbine & compressor unit. The results show that this method can complete the multi-sources fault diagnosis quantitatively and improve the diagnosis resolution effectively.
Keywords :
Bayes methods; compressors; directed graphs; fault diagnosis; gas turbines; lubrication; pipelines; Bayes theory; China; SDG; compressor unit; diagnosis resolution; gas turbine; implicit enumeration method; lubrication system; multisource fault diagnosis; multisource fault diagnosis method; natural gas pipeline; signed directed graph; Equations; Fault diagnosis; Lubrication; Mathematical model; Natural gas; Pipelines; Turbines; Bayes; SDG; multi-sources fault diagnosis; the gas turbine & compressor unit;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
Type :
conf
DOI :
10.1109/WCICA.2012.6358380
Filename :
6358380
Link To Document :
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