DocumentCode :
807032
Title :
Fault diagnosis of electronic system using artificial intelligence
Author :
Fenton, Billy ; McGinnity, Martin ; Maguire, Liam
Author_Institution :
Ulster Univ., UK
Volume :
5
Issue :
3
fYear :
2002
fDate :
9/1/2002 12:00:00 AM
Firstpage :
16
Lastpage :
20
Abstract :
With increasing system complexity, shorter product life cycles, lower production costs, and changing technologies, the need for intelligent tools for all stages of a product´s lifecycle is becoming increasingly important. The purpose of this article is to give a brief review how AI has been used in the field of electronic fault diagnosis. Topics discussed include: rule-based diagnostic systems; model-based diagnostic systems; case-based reasoning (CBR); fuzzy reasoning and artificial neural networks (ANN); hybrid approaches; IEEE diagnostic standards and automated diagnostic tool future developments.
Keywords :
IEEE standards; automatic test equipment; case-based reasoning; diagnostic expert systems; diagnostic reasoning; electronic equipment testing; failure analysis; fault diagnosis; fuzzy logic; knowledge engineering; neural nets; AI; ANN; CBR; IEEE diagnostic standards; artificial intelligence; artificial neural networks; automated diagnostic tools; case-based reasoning; electronic system fault diagnosis; fuzzy logic; fuzzy reasoning; hybrid diagnostic systems; intelligent tools; model-based diagnostic systems; rule-based diagnostic systems; Artificial intelligence; Circuit faults; Circuit testing; Digital circuits; Fault diagnosis; Knowledge acquisition; Mathematical model; Predictive models; Sequential circuits; Telephony;
fLanguage :
English
Journal_Title :
Instrumentation & Measurement Magazine, IEEE
Publisher :
ieee
ISSN :
1094-6969
Type :
jour
DOI :
10.1109/MIM.2002.1028367
Filename :
1028367
Link To Document :
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