DocumentCode :
2155348
Title :
Generating fault detection heuristic rules through deep and shallow knowledge of the process
Author :
Calado, J.M.F. ; Roberts, P.D.
Author_Institution :
City Univ., London, UK
Volume :
1
fYear :
1996
fDate :
2-5 Sept. 1996
Firstpage :
299
Abstract :
A combined shallow and deep knowledge based approach, where deep knowledge plays the main role, is presented for fault detection purposes. A systematic methodology for generating fault detection heuristic rules, which are based on deep knowledge of the process under consideration, is developed. In order to facilitate the process behaviour analysis, structural decomposition of the plant, as well as component functions, are considered. Since structural decomposition corresponds to plant topology, it may be easier to implement. The proposed method has been applied for generating fault detection heuristics for a continuous stirred tank reactor. It has been observed that the knowledge based system, achieved by this method, has a good performance and reliability.
Keywords :
fault location; heuristic programming; knowledge engineering; CSTR; continuous stirred tank reactor; deep knowledge; fault detection heuristic rules; knowledge-based system; plant topology; process behaviour analysis; shallow knowledge; structural decomposition;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Control '96, UKACC International Conference on (Conf. Publ. No. 427)
ISSN :
0537-9989
Print_ISBN :
0-85296-668-7
Type :
conf
DOI :
10.1049/cp:19960569
Filename :
651396
Link To Document :
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