DocumentCode
3349835
Title
Research on rotary dump health monitoring expert system based on causality diagram theory
Author
Quan, Liu ; Jingsong, Li
Author_Institution
Sch. of Inf. Eng., Wuhan Univ. of Technol., Wuhan
fYear
2008
fDate
21-24 Sept. 2008
Firstpage
296
Lastpage
299
Abstract
Causality diagram theory is a kind of uncertainty reasoning theory based on the belief network. It expresses the knowledge and causality relationship by diagrammatic form and direct causality intensity. Furthermore, it resolves the shortages of the belief network, and realizes a hybrid model which can process discrete and continuous variations. The theory of causality diagram model and the steps of causality diagram reasoning methodology are studied in this paper, and a model of rotary dump health monitoring expert system is proposed. In addition, this paper establishes the causality diagram of rotary dump and converts it to the causality tree. According to the causality tree of rotary dump, the causality diagram reasoning methodology composed of four steps is described. Finally, an application of rotary dump health monitoring expert system is shown, and the system performance analysis is discussed.
Keywords
belief networks; causality; condition monitoring; diagnostic expert systems; fault diagnosis; inference mechanisms; mechanical engineering computing; belief network; causality diagram reasoning methodology; causality diagram theory; rotary dump health monitoring expert system; uncertainty reasoning theory; Application software; Artificial intelligence; Couplings; Diagnostic expert systems; Expert systems; Knowledge representation; Monitoring; Probability distribution; System performance; Uncertainty; Causality Diagram; Expert System; Fault Diagnosis; Reasoning on Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Cybernetics and Intelligent Systems, 2008 IEEE Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-1673-8
Electronic_ISBN
978-1-4244-1674-5
Type
conf
DOI
10.1109/ICCIS.2008.4670773
Filename
4670773
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