A Fuzzy Rule Based System for Fault Diagnosis, Using Oil Analysis Results
Publish place: 7th International Industrial Engineering Conference
Publish Year: 1389
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
IIEC07_242
تاریخ نمایه سازی: 7 خرداد 1389
Abstract:
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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Authors
Saeed Ramezani
Logistics Studies & Researches Center, Imam Hossein Uni
Mostafa Yousofi
Tarbiat Modares Uni, Faculty of Industrial Engineering
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