DocumentCode :
2615529
Title :
On evolutionary optimisation of Markov models of aero engines
Author :
Breikin, Timofei ; Kulikov, Gennady ; Arkov, Valentin ; Fleming, Peter
Author_Institution :
Dept. of Autom. Control Syst., Ulfa State Aviation Tech. Univ., Ufa, Russia
fYear :
2000
fDate :
2000
Firstpage :
235
Lastpage :
239
Abstract :
An application of genetic algorithms for aviation engine dynamic model structure optimisation is considered. A method for Markov models utilisation for gas turbine engine nonparametric nonlinear stochastic modelling is described. A technique of Markov model based engine condition monitoring is presented. The evolutionary computational techniques are implemented for optimal selection of gas turbine engine Markov model parameters. The real engine data was used for identification and optimisation of the engine Markov model. The results of genetic algorithm application for engine model optimisation are shown
Keywords :
Markov processes; aerospace engines; condition monitoring; gas turbines; genetic algorithms; Markov models; aero engines; aviation engine; dynamic model structure optimisation; engine condition monitoring; evolutionary computational techniques; evolutionary optimisation; gas turbine engine; nonparametric nonlinear stochastic modelling; Aerodynamics; Aircraft propulsion; Condition monitoring; Engines; Fault detection; Genetic algorithms; Nonlinear dynamical systems; Predictive models; Testing; Turbines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control, 2000. Proceedings of the 2000 IEEE International Symposium on
Conference_Location :
Rio Patras
ISSN :
2158-9860
Print_ISBN :
0-7803-6491-0
Type :
conf
DOI :
10.1109/ISIC.2000.882930
Filename :
882930
Link To Document :
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