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