Title :
Application of Aircraft Fuel Fault Diagnostic Expert System Based on Fuzzy Neural Network
Author :
Long, Hao ; Wang, Xinmin
Author_Institution :
Coll. of Automatics, Beijing Union Univ., Beijing, China
Abstract :
Theories of expert system and fuzzy artificial neural network (ANN) are applied to solve the problem of fault diagnosis in the aircraft fuel system. A multilayer neural network model of the aircraft fuel system is put forward and the integrated aircraft fuel fault diagnostic expert system which solves the problems of knowledge representation and knowledge acquisition of traditional expert system is realized. The hardware-in-loop simulation results show that the expert system diagnoses the fault in accessories rapidly and accurately and it is proved that the expert system is significative and helpful for further development in the aircraft fuel fault diagnosis.
Keywords :
aircraft; expert systems; fault diagnosis; fuel systems; neural nets; aircraft fuel system; fault diagnostic expert system; fuzzy artificial neural network; hardware-in-loop simulation; multilayer neural network model; Aircraft; Artificial neural networks; Diagnostic expert systems; Fault diagnosis; Fuels; Fuzzy neural networks; Fuzzy systems; Hybrid intelligent systems; Multi-layer neural network; Neural networks; Aircraft Fuel System; Expert System; Fault Diagnosis; Fuzzy ANN;
Conference_Titel :
Information Engineering, 2009. ICIE '09. WASE International Conference on
Conference_Location :
Taiyuan, Chanxi
Print_ISBN :
978-0-7695-3679-8
DOI :
10.1109/ICIE.2009.9