Data Mining for Building Rule-based Fault Diagnosis Systems

This paper aims at developing rule-based fault diagnosis (RBFD) systems using data mining techniques, where we address a problem of generating rules for faults with low probability of occurrence but considerable conceptual importance. Main technical contributions include a multilayer structure of ru...

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Bibliographic Details
Main Author: Dianhui Wang
Format: Conference Proceeding
Language:English
Subjects:
Computer science
Control systems
Data engineering
Data mining
Diagnostic expert systems
Electronic mail
Engines
Fault diagnosis
multilayer classifiers
Nonhomogeneous media
Power engineering and energy
rule-based expert systems
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Description
Summary:This paper aims at developing rule-based fault diagnosis (RBFD) systems using data mining techniques, where we address a problem of generating rules for faults with low probability of occurrence but considerable conceptual importance. Main technical contributions include a multilayer structure of rule generation and use, and a regularization model embedding some information on recognition rate, coverage rate and generalization capability for rule optimization. A case study is carried out by an engine diagnostics to illustrate effectiveness of our methodology.
ISSN:1934-1768
2161-2927
DOI:10.1109/CHICC.2006.280946