DocumentCode :
3332197
Title :
A knowledge-based approach to real time signal monitoring
Author :
O´Neill, D.M. ; Mullarkey, P.W.
Author_Institution :
Schlumberger-Doll Res. Center, Ridgefield, CT, USA
fYear :
1989
fDate :
6-10 Mar 1989
Firstpage :
133
Lastpage :
140
Abstract :
A method is presented for describing, observing, and classifying, phenomena in signal data. The approach consists of two main parts: a declarative formalism for describing the events of interest and how they relate to real-world phenomena, and a runtime agent that utilizes these descriptions to detect and classify observations made from real-time signals. A prototype implementation of this approach, called the Observation Classification System (OCS), has been developed and has been used in applications ranging from experiment monitoring to data quality analysis
Keywords :
computerised monitoring; computerised signal processing; knowledge based systems; knowledge representation; real-time systems; Observation Classification System; declarative formalism; knowledge representation; knowledge-based; real time signal monitoring; real-time signals; real-world phenomena; runtime agent; signal data; Artificial intelligence; Condition monitoring; Data analysis; Diagnostic expert systems; Event detection; Knowledge representation; Prototypes; Runtime; Signal processing; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence Applications, 1989. Proceedings., Fifth Conference on
Conference_Location :
Miami, FL
Print_ISBN :
0-8186-1902-3
Type :
conf
DOI :
10.1109/CAIA.1989.49146
Filename :
49146
Link To Document :
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