Application of BPNN and CBR on Fault Diagnosis for Missile Electronic Command System

Author

Zhao, Jiu-ling ; Zhao, Jiu-Fen

Author_Institution

Second Artillery Eng. Inst., Xi´´an

Volume

2

fYear

0

fDate

0-0 0

Firstpage

5796

Lastpage

5799

Abstract

Based on the complexity of the mobile missile electronic command system (MMECS), applying the single method in system fault diagnosis can hardly achieve satisfactory results. The fault diagnosis system combining the BP neural network (BPNN) method and the case-based reasoning (CBR) method was presented. The framework of the mixed neural network and the case presentation was put forward. The question of redundancy reasoning was solved, moreover, it can interpret the diagnoses by providing the successful case. Finally, with the example of voice interrupt, the system´s correctness and validity was proved. It is shown that the system is suitable for both the operators training and online decision making for the army

Keywords

backpropagation; case-based reasoning; control engineering computing; decision making; fault diagnosis; military avionics; military computing; missiles; BP neural network; case-based reasoning; mixed neural network; mobile missile electronic command system; online decision making; redundancy reasoning; system fault diagnosis; Artificial neural networks; Decision making; Fault diagnosis; Inference mechanisms; Missiles; Multi-layer neural network; Neural networks; Redundancy; Weapons; !Fault diagnosis Neural Network Missile electronic command system CBR;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on

Conference_Location

Dalian

Print_ISBN

1-4244-0332-4

Type

conf

DOI

10.1109/WCICA.2006.1714187

Filename

1714187