DocumentCode :
3072793
Title :
Intelligent Fault Diagnosis System Research on AeroEngine
Author :
Qu, Peishu ; Dong, Wenhui ; Sang, Zhiguo ; Sheng, Yong
Author_Institution :
Dept. of Phys., Dezhou Univ., Dezhou, China
fYear :
2011
fDate :
16-17 July 2011
Firstpage :
63
Lastpage :
66
Abstract :
This paper, we take neural network technology into the field of test of aircraft engine endo scopic. introduced general framework of the diagnostic expert system of aircraft engines based on neural network and giving an improved reasoning method, established the BP network model, take the common faults of B747-200F´s CFM56 engine, for example, take a simulation test of fault diagnosis, and compared with the actual fault data, proved that the system can intelligently determine fault type, Which can further help quickly and accurately locate and solve the fault for aircraft maintenance personnel, and improving the work efficiency, so it has very greater practical value.
Keywords :
aerospace engines; aircraft maintenance; backpropagation; case-based reasoning; diagnostic expert systems; fault diagnosis; neural nets; BP network; CFM56 engine; aeroengine; aircraft engine; aircraft maintenance personnel; diagnostic expert system; intelligent fault diagnosis system; neural network technology; reasoning; Cognition; Decision making; Engines; Expert systems; Injuries; Maintenance engineering; Training; Back propagation algorithm; Expert system; aeroengine; artificial neural network; video probe inspection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Society (ISCCS), 2011 International Symposium on
Conference_Location :
Kota Kinabalu
Print_ISBN :
978-1-4577-0644-8
Type :
conf
DOI :
10.1109/ISCCS.2011.25
Filename :
6004266
Link To Document :
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