DocumentCode :
1903698
Title :
Application of Expert System Fuzzy BP Neural Network in Fault Diagnosis of Piston Engine
Author :
Quan, Zhang ; Nanyu, Chen ; Jun, Huang ; Zhijun, Meng
Author_Institution :
Sch. of Aeronaut. Sci. & Eng., Beihang Univ., Beijing, China
Volume :
3
fYear :
2012
fDate :
23-25 March 2012
Firstpage :
604
Lastpage :
607
Abstract :
Due to the limitation of BP neural network in fault diagnosis, an improved fault diagnosis method based on Expert System, Fuzzy Theory and improved BP neural network is presented in this paper. And then it is applied in the fault diagnosis of one piston engine. Firstly, a fault database of the piston engine is established by using Expert System, Secondly, the fault symptom is pre-processed with Fuzzy Theory to obtain training samples for neural network, in the end, simulations of fault diagnosis based on BP neural network and improved BP neural network are accomplished by employing the MATLAB software. The simulation results indicate that this method maintains fast convergence, high diagnostic accuracy and it can diagnosis engine failure effectively.
Keywords :
aerospace computing; aerospace engines; backpropagation; expert systems; fault diagnosis; fuzzy set theory; helicopters; mechanical engineering computing; military vehicles; neural nets; pistons; remotely operated vehicles; MATLAB software; expert system fuzzy BP neural network; fault database; fault diagnosis method; fuzzy theory; military actions; piston engine; unmanned helicopter; Accuracy; Data mining; Engines; Expert systems; Fault diagnosis; Pistons; Training; BP neural network; Expert System; Fuzzy Theory; fault diagnosis; piston engine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-0689-8
Type :
conf
DOI :
10.1109/ICCSEE.2012.170
Filename :
6188246
Link To Document :
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