DocumentCode
1778768
Title
Fault Diagnosis for Gas Turbine Blade Based on ABC-RVM Algorithm
Author
Chen Li-Wei ; Pu Ying-Dong
Author_Institution
Coll. of Inf. & Commun. Eng., Harbin Eng. Univ., Harbin, China
fYear
2014
fDate
18-20 Sept. 2014
Firstpage
93
Lastpage
97
Abstract
In this paper, a fault diagnosis scheme for gas turbine blade is developed. The proposed system is based on the artificial bee colony algorithm optimize relevance vector machine (ABC-RVM) to accomplish this goal. First the characteristics extraction was researched, then Then ABC-RVM is used for the intelligent fault diagnosis and health warning provides scientific theory and effective method for the fault diagnosis.
Keywords
blades; fault diagnosis; gas turbines; learning (artificial intelligence); mechanical engineering computing; optimisation; ABC-RVM algorithm; artificial bee colony algorithm; gas turbine blade; health warning; intelligent fault diagnosis; relevance vector machine; Blades; Fault diagnosis; Sociology; Statistics; Support vector machines; Training; Turbines; ABC-RVM; fault diagnosis; temperature signal;
fLanguage
English
Publisher
ieee
Conference_Titel
Instrumentation and Measurement, Computer, Communication and Control (IMCCC), 2014 Fourth International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4799-6574-8
Type
conf
DOI
10.1109/IMCCC.2014.27
Filename
6994997
Link To Document