Volume 22, Number 2 (IJIEPR 2011)                   IJIEPR 2011, 22(2): 91-98 | Back to browse issues page


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Ramezani S, Memariani A. A Fuzzy Rule Based System for Fault Diagnosis, Using Oil Analysis Results. IJIEPR. 2011; 22 (2) :91-98
URL: http://ijiepr.iust.ac.ir/article-1-286-en.html

School of Economic Sciences, Scientific Counselor and Director of the Iranian Students Affairs in South-East Asia , memar@iranembassy.com
Abstract:   (4354 Views)

 

  Condition Monitoring,

  Oil Analysis, Wear Behavior,

  Fuzzy Rule Based System

 

Maintenance , as a support function, plays an important role in manufacturing companies and operational organizations. In this paper, fuzzy rules used to interpret linguistic variables for determination of priorities. Using this approach, such verbal expressions, which cannot be explicitly analyzed or statistically expressed, are herein quantified and used in decision making.

In this research, it is intended to justify the importance of historic data in oil analysis for fault detection. Initial rules derived by decision trees and visualization then these fault diagnosis rules corrected by experts. With the access to decent information sources, the wear behaviors of diesel engines are studied. Also, the relation between the final status of engine and selected features in oil analysis is analyzed. The dissertation and analysis of determining effective features in condition monitoring of equipments and their contribution, is the issue that has been studied through a Data Mining model.
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Subject: Other Related Subject
Received: 2011/07/19

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