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The development of a deep knowledge diagnostic expert system using fault tree analysis information
Author(s) -
Adamson M. S.,
Roberge P. R.
Publication year - 1991
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.5450690109
Subject(s) - fault tree analysis , expert system , knowledge base , computer science , heuristic , data mining , domain knowledge , domain (mathematical analysis) , process (computing) , operator (biology) , reliability engineering , artificial intelligence , engineering , programming language , mathematics , mathematical analysis , biochemistry , chemistry , repressor , transcription factor , gene
In this paper a diagnostic Knowledge Based Expert System (KBES) prototype for a nuclear Auxiliary Boiler Feed System (ABFS) was developed. A commercial Expert System shell accesses heuristic production rules to quickly resolve the majority of common faults. Supplementing this are a series of C functions which access the Fault Tree data base previously developed during the licensing process. These functions perform diagnostics, give detailed explanations of failure mechanisms, and identify system failure risks through examination of cut sets. The capture of both heuristic and Fault Tree information has resulted in a more exhaustive diagnostic tool with a domain of application unrestricted by the limitations of previous operator experience.