Research on Fault Diagnosis of Civil Aircraft Based on AFPN

Author

Wang, Xiuyan ; Xue, Binbin ; Li, Zongshuai ; Lin, Jiaquan

Author_Institution

Coll. of Aeronaut. Autom., Civil Aviation Univ. of China, Tianjin, China

Volume

2

fYear

2011

fDate

28-30 Oct. 2011

Firstpage

39

Lastpage

42

Abstract

As the knowledge in the fault diagnosis of civil aircraft is dynamic and uncertain, a method based on the Adaptive Fuzzy Petri Net(APFN) is proposed to solve the problem. AFPN not only takes the descriptive advantages of fuzzy Petri net, but also has learning ability like neural network. By this mean, firstly set up a fuzzy Petri net using the fuzzy production rule. Then the parameters of the fuzzy Petri net are trained by BP learning algorithm. At last, when the weights of the fuzzy Petri net are fixed, the fault origin can be found through the fault inference. At the end of the paper, an experiment is designed to demonstrate that the approach is feasible and effective in fuzzy reasoning.

Keywords

Petri nets; aircraft; backpropagation; civil engineering; fault diagnosis; fuzzy reasoning; neural nets; AFPN; BP learning algorithm; adaptive fuzzy Petri net; civil aircraft; fault diagnosis; fuzzy reasoning; learning ability; neural network; Adaptive systems; Aircraft; Atmospheric modeling; Fault diagnosis; Generators; Production; Training; Adaptive Fuzzy Petri Net; civil aircraft; fault diagnosis; learning ability;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Design (ISCID), 2011 Fourth International Symposium on

Conference_Location

Hangzhou

Print_ISBN

978-1-4577-1085-8

Type

conf

DOI

10.1109/ISCID.2011.111

Filename

6079731