Title :
The information-enhanced BIT design of avionics system based on fuzzy neural network
Author :
Yao Guo-Ping ; Hou Wen-Kui ; Shi Long ; Shi Jun-You
Author_Institution :
Sch. of Reliability & Syst. Eng., Beihang Univ., Beijing, China
Abstract :
Based on the needs of current avionics system fault diagnosis and health management on engineering project, this paper designed a program for fault diagnosis of typical avionics system module based on artificial intelligence. The basic principle of information-enhanced BIT was discussed. Then a fuzzy nature network designed for fault was built which combined self-adaption function. Beside software and hardware diagnosis overall framework is included. This paper provided a strong support for improving the ability of fault diagnosis of avionics products, reducing false alarms.
Keywords :
artificial intelligence; avionics; built-in self test; fault diagnosis; fuzzy neural nets; artificial intelligence; avionics system; fault diagnosis; fuzzy neural network; hardware diagnosis; health management; information-enhanced BIT design; software diagnosis; Aerospace electronics; Biological neural networks; Fault diagnosis; Fuzzy neural networks; Knowledge engineering; Training; BIT(built-in test); avionics system; fault diagnosis; fuzzy nature network;
Conference_Titel :
Mechatronic Sciences, Electric Engineering and Computer (MEC), Proceedings 2013 International Conference on
Conference_Location :
Shengyang
Print_ISBN :
978-1-4799-2564-3
DOI :
10.1109/MEC.2013.6885535
