Reliability Modeling Using an Adaptive Neuro-Fuzzy Inference System: Gas Turbine Application

被引：5
作者：
Hadroug, Nadji [1 ,2 ]
Hafaifa, Ahmed [1 ,2 ]
Iratni, Abdelhamid [3 ]
Guemana, Mouloud [1 ,4 ]
机构：
[1] Univ Djelfa, Fac Sci & Technol, Appl Automat & Ind Diagnost Lab, Djelfa, Algeria
[2] Univ Djelfa, Gas Turbine Joint Res Team, Djelfa, Algeria
[3] Univ Bordj Bou Arreridj, Fac Sci & Technol, El Anceur, Algeria
[4] Univ Medea, Fac Sci & Technol, Medea, Algeria
来源：
FUZZY INFORMATION AND ENGINEERING | 2021年 / 13卷 / 02期
关键词：
Reliability analyzes; reliability modeling; adaptive neuro-fuzzy inference system; gas turbine system; FATIGUE RELIABILITY; WIND TURBINE; AVAILABILITY; PROGNOSTICS; ANFIS;
D O I：
10.1080/16168658.2021.1915451
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Recently, the development of the industry requires monitoring and follow-up of the working conditions of the facilities, to determine the reliability, availability, and durability of these systems, for objectively estimating the service life of these installations with reduced maintenance costs. In this sense, this work proposes a novel approach to reliability modeling, to determine failure assessment indicators based on an adaptive neuro-fuzzy inference system applied on a gas turbine. This is in order to describe the behavior of this rotating machine and to estimate their operating safety parameters, to improve its performance in terms of maintainability, availability, and operational safety with effective durability. The application of fuzzy rules to reliability estimation with practical implementations is innovative, making it possible to provide solutions to problems of reliable identification of gas turbines in their complex operating environments.
引用
收藏
页码：154 / 183
页数：30
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