Title :
Reasoning from uncertain data: a bit enhancement
Author :
Cooper, Laurence J. ; Smith, Dennis E.
Author_Institution :
SIGMAX, New Freedom, PA, USA
Abstract :
It is proposed that artificial intelligence (AI) principles, coupled with powerful Bayesian statistical inference techniques, can be successfully applied to built-in-test (BIT) technology and can significantly contribute to the improvement of avionics BIT diagnostic capabilities. The goal is to extract more information from available data provided by the BIT, rather than to expand its testing capabilities. The proposed approach is illustrated by a TACAN (tactical air navigation) example
Keywords :
Bayes methods; aircraft instrumentation; artificial intelligence; automatic testing; electronic equipment testing; inference mechanisms; military systems; probability; statistical analysis; Bayesian statistical inference; TACAN; automatic testing; avionics; bit; built-in-test; tactical air navigation; Aerospace electronics; Artificial intelligence; Bayesian methods; Built-in self-test; Data mining; Information analysis; Isolation technology; Logic; Testing; Uncertainty;
Conference_Titel :
AUTOTESTCON '89. IEEE Automatic Testing Conference. The Systems Readiness Technology Conference. Automatic Testing in the Next Decade and the 21st Century. Conference Record.
Conference_Location :
Philadelphia, PA
DOI :
10.1109/AUTEST.1989.81112
