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Experiences with an expert system technology for real-time monitoring and diagnosis of industrial processes

Abstract

The complexity of modern industrial processes and the large amount of data available to their operators make it difficult to monitor their status and diagnose potential failures. Although there have been many attempts to apply knowledge-based technologies to this problem, there have not been any convincing success. This paper describes recent experiences with a technology that combines artificial intelligence and simulation techniques for building real-time monitoring and diagnosis systems. A prototype system for monitoring and diagnosing the feedwater system of a nuclear power plant built using this technology is described. The paper then describes several interesting classes of failures that the prototype is capable of diagnosing. (author). 19 refs, 6 figs.
Authors:
Chou, Q B; [1]  Mylopoulos, J; [2]  Opala, J [3] 
  1. Ontario Hydro, Toronto, ON (Canada)
  2. Toronto Univ., ON (Canada)
  3. CAE Electronics, Montreal, Quebec (Canada)
Publication Date:
Dec 31, 1996
Product Type:
Conference
Report Number:
INIS-mf-15517; CONF-9605269-
Reference Number:
SCA: 210000; PA: AIX-28:031004; EDB-97:054265; SN: 97001765424
Resource Relation:
Conference: Specialists` meeting on monitoring and diagnosis systems to improve nuclear power plant reliability and safety, Gloucester (United Kingdom), 14-17 May 1996; Other Information: PBD: 1996; Related Information: Is Part Of Monitoring and diagnosis systems to improve nuclear power plant reliability and safety. Proceedings of the specialists` meeting; PB: 271 p.
Subject:
21 NUCLEAR POWER REACTORS AND ASSOCIATED PLANTS; NUCLEAR POWER PLANTS; EXPERT SYSTEMS; REAL TIME SYSTEMS; ARTIFICIAL INTELLIGENCE; DIAGNOSTIC TECHNIQUES; KNOWLEDGE BASE; MONITORING; RELIABILITY; SAFETY; SIMULATION
OSTI ID:
454182
Research Organizations:
International Atomic Energy Agency, Vienna (Austria); Nuclear Electric plc, Barnwood (United Kingdom)
Country of Origin:
IAEA
Language:
English
Other Identifying Numbers:
Other: ON: DE97620704; TRN: XA9743558031004
Availability:
INIS; OSTI as DE97620704
Submitting Site:
INIS
Size:
pp. 31-40
Announcement Date:

Citation Formats

Chou, Q B, Mylopoulos, J, and Opala, J. Experiences with an expert system technology for real-time monitoring and diagnosis of industrial processes. IAEA: N. p., 1996. Web.
Chou, Q B, Mylopoulos, J, & Opala, J. Experiences with an expert system technology for real-time monitoring and diagnosis of industrial processes. IAEA.
Chou, Q B, Mylopoulos, J, and Opala, J. 1996. "Experiences with an expert system technology for real-time monitoring and diagnosis of industrial processes." IAEA.
@misc{etde_454182,
title = {Experiences with an expert system technology for real-time monitoring and diagnosis of industrial processes}
author = {Chou, Q B, Mylopoulos, J, and Opala, J}
abstractNote = {The complexity of modern industrial processes and the large amount of data available to their operators make it difficult to monitor their status and diagnose potential failures. Although there have been many attempts to apply knowledge-based technologies to this problem, there have not been any convincing success. This paper describes recent experiences with a technology that combines artificial intelligence and simulation techniques for building real-time monitoring and diagnosis systems. A prototype system for monitoring and diagnosing the feedwater system of a nuclear power plant built using this technology is described. The paper then describes several interesting classes of failures that the prototype is capable of diagnosing. (author). 19 refs, 6 figs.}
place = {IAEA}
year = {1996}
month = {Dec}
}