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