Integrating diagnostic knowledge

Author

Havlicsek, Bruce I.

Author_Institution

Westinghouse Electr. Corp., Hunt Valley, MD, USA

Volume

4

Issue

11

fYear

1989

Firstpage

54

Lastpage

59

Abstract

The use of artificial intelligence technique to access, analyze, and integrate different types of knowledge under a single diagnostic concept is described. Repair statistics and field experience are handled by an empirical knowledge (shallow reasoning) diagnostic system in order to retain the experience of expert test personnel. Computer-aided-design knowledge is handled by model-based (deep reasoning) diagnostic systems in order to extract diagnostics directly from design data. Combining these approaches overcomes limitations of the individual techniques and provides a more powerful diagnostic system. The Westinghouse expert diagnostic system is considered as an example.<>

Keywords

automatic test equipment; expert systems; Westinghouse expert diagnostic system; artificial intelligence; deep reasoning; design data; diagnostic knowledge; empirical knowledge; expert test personnel; integration; repair statistics; shallow reasoning; Artificial intelligence; Computational modeling; Data mining; Databases; Design automation; Personnel; Power system modeling; Statistical analysis; Statistics; System testing;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems Magazine, IEEE

Publisher

ieee

ISSN

0885-8985

Type

jour

DOI

10.1109/62.41756

Filename

41756