A Fuzzy Rule Based Dystem for Fault Diagnosis, Using Oil Analysis Results

سال انتشار: 1390
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 734

فایل این مقاله در 8 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

JR_IJIEPR-22-2_002

تاریخ نمایه سازی: 7 شهریور 1393

چکیده مقاله:

Maintenance, as a support function, plays an important roe 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, ard herein quantified and used in decision making. In this research, it is intended to justify the importance of historix data in oil analysis for fault detection, Initial rules derived by desision trees and visualization then these fault diagnosis rules corrected by experts. with the access to decent information sources, the wear behaviours 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.

کلیدواژه ها:

Condition Monitoring ، Oil Analysis ، Wear Behavior ، Fuzzy Rule Based System

نویسندگان

Saeed Ramezani

Logistics Studies &Researches Venter, Imam Hossein University

Azizollah Mehmariani

School of Economic Sciences, Scientific Counselor and Director of the Iranian Students Affairs in South-East Asia