DocumentCode :
2403853
Title :
Applying neural networks and other AI techniques to fault detection in satellite communication systems
Author :
Elerin, Liese ; Learoyd, Charles ; Wilson, Beth
Author_Institution :
Raytheon Co., Marlborough, MA, USA
fYear :
1997
fDate :
24-26 Sep 1997
Firstpage :
617
Lastpage :
625
Abstract :
A demonstration program has been completed to apply various artificial intelligence techniques including, neural networks, expert systems, and case-based reasoning to fault detection in satellite communications systems. The GMM program implemented these techniques for global military satellite communications maintenance. Neural networks were designed and trained to analyze incoming built-in-test (BIT) fault signatures from the satellite communications terminal. Expert systems were developed to embed diagnostic knowledge relating to equipment maintenance. The prototype hybrid system uses neural filters to detect faults, which are further processed by expert systems to classify the faults and provide repair directions
Keywords :
case-based reasoning; diagnostic expert systems; fault diagnosis; maintenance engineering; military communication; neural nets; satellite communication; AI techniques; GMM program; built-in-test fault signatures; case-based reasoning; diagnostic knowledge; equipment maintenance; expert systems; fault detection; global military satellite communications maintenance; neural filters; neural networks; repair directions; satellite communication systems; Artificial intelligence; Artificial neural networks; Costs; Diagnostic expert systems; Fault detection; Filters; History; Intelligent networks; Neural networks; Satellite communication;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks for Signal Processing [1997] VII. Proceedings of the 1997 IEEE Workshop
Conference_Location :
Amelia Island, FL
ISSN :
1089-3555
Print_ISBN :
0-7803-4256-9
Type :
conf
DOI :
10.1109/NNSP.1997.622444
Filename :
622444
Link To Document :
بازگشت