Redundant Backup and Diagnostic System of MPM-20 Engine

被引：0

作者：

Nyulaszi, Ladislav ^{[1
]}

Madarasz, Ladislav ^{[1
]}

Andoga, Rudolf

Gaspar, Vladimir ^{[1
]}

机构：

[1] TU Kosice, Dept Cybernet & Artificial Intelligence, FEEaI, Kosice 04200, Slovakia

来源：

14TH IEEE INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND INFORMATICS (CINTI) | 2013年

关键词：

technical diagnostics; backup; majority method; neural network; diagnostic system;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Progressive development of turbojet engine requires focus not only on improving performance, but also high reliability and safety are very important. That's why we put more and more emphasis on concepts like diagnostics and backup, which represent the basic techniques and methods that contribute to increased safety of any complex system. The article deals with the design of diagnostics/backup system, which uses majority method and backup through computational models that take advantage of experimental identification methods and neural networks. The proposed system for jet engines was subsequently tested in laboratory conditions (LIRS LM - Laboratory of Intelligent Control Systems of Jet Engines) on a small turbojet engine MPM-20, where confirmed its functionality and reliability.

引用

页码：43 / 47

页数：5

共 14 条

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