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An Expert System Shell for Fault Diagnosis

Published online by Cambridge University Press:  30 October 2001

Jie Yang ,
Chenzhou Ye  and
Xiaoli Zhang
Jie Yang
Affiliation:
Institute of Image Processing & Recognition, Shanghai Jiao-Tong University, Shanghai 200030 (P. R. of China)
Chenzhou Ye
Affiliation:
Institute of Image Processing & Recognition, Shanghai Jiao-Tong University, Shanghai 200030 (P. R. of China)
Xiaoli Zhang
Affiliation:
Institute of Image Processing & Recognition, Shanghai Jiao-Tong University, Shanghai 200030 (P. R. of China)
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Abstract

Traditional expert systems for fault diagnosis have a bottleneck in knowledge acquisition, and have limitations in knowledge representation and reasoning. A new expert system shell for fault diagnosis is presented in this paper to develop multiple knowledge models (object model, rules, neural network, case-base and diagnose models) hierarchically based on multiple knowledge. The structure of the expert system shell and the knowledge representation of multiple models are described. Diagnostic algorithms are presented for automatic modeling and hierarchical reasoning. It will be shown that the expert system shell is very effective in building diagnostic expert systems.

Keywords

Expert system shellFault diagnosisRough setArtificial Neural NetworkCase-based reasoning
Type
Research Article
Information
Robotica , Volume 19 , Issue 6 , September 2001 , pp. 669 - 674
Copyright
© 2001 Cambridge University Press

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