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Proceedings Paper

A Model Expert System For Machine Failure Diagnosis (MED)
Author(s): Yin Liqun
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Paper Abstract

MED is a model expert system for machine failure diagnosis. MED can help the repairer quickly determine milling machine electrical failure. The key points in MED are a simple method to deal with the "subsequent visit" problem in machine failure diagnosis, a weighted list to interfere in the control of AGENDA to imitate an expert's continuous thinking process and to keep away erratic questioning and problem running away caused by probabilistic reasoning, the structuralized AGENDA, the characteristics of machine failure diagnosis and people's thinking pattern in faulure diagnosis. The structuralized AGENDA gives an idea to supply a more powerful as well as flexible control strategy in best-first search by using AGENDA. The "subsequent visit" problem is a very complicated task to solve, it will be convenient to deal with it by using a simple method to keep from consuming too much time in urgent situations. Weighted list also gives a method to improve control in inference of expert system. The characteristics of machine failure diagnosis and people's thinking pattern are both important for building a machine failure diagnosis expert system. When being told failure phenomena, MED can determine failure causes through dialogue. MED is written in LISP and run in UNIVAC 1100/10 and IBM PC/XT computers. The average diagnosis time per failure is 11 seconds to CPU, 2 minites to terminal operation, and 11 minites to a skilful repairer.

Paper Details

Date Published: 11 May 1987
PDF: 8 pages
Proc. SPIE 0786, Applications of Artificial Intelligence V, (11 May 1987); doi: 10.1117/12.940614
Show Author Affiliations
Yin Liqun, Academia Sinica (China)


Published in SPIE Proceedings Vol. 0786:
Applications of Artificial Intelligence V
John F. Gilmore, Editor(s)

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