Title :
Redundant backup and diagnostic system of MPM-20 engine
Author :
Nyulaszi, Ladislav ; Madarasz, Ladislav ; Andoga, Rudolf ; Gaspar, V.
Author_Institution :
Dept. of Cybern. & Artificial Intell., Tech. Univ. Kosice, Kosice, Slovakia
Abstract :
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.
Keywords :
jet engines; neural nets; redundancy; MPM 20 engine; computational models; diagnostic system; identification methods; neural networks; progressive development; redundant backup system; turbojet engine; Computational intelligence; Computational modeling; Data models; Engines; Neural networks; Reliability; Sensors; backup; diagnostic system; majority method; neural network; technical diagnostics;
Conference_Titel :
Computational Intelligence and Informatics (CINTI), 2013 IEEE 14th International Symposium on
Conference_Location :
Budapest
Print_ISBN :
978-1-4799-0194-4
DOI :
10.1109/CINTI.2013.6705241