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Comparison of Adaptive Filtering Schemes for Gas Turbine Performance Diagnostics
Borguet, Sébastien; Léonard, Olivier
2008In Proceedings of the 4th International Conference on Advanced Computational Methods in Engineering
 

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Keywords :
Kalman filters; turbine engine community; health monitoring purpose; track gradual deterioration; components
Abstract :
[en] Kalman filters are widely used in the turbine engine community for health monitoring purpose. This algorithm has proven its capability to track gradual deterioration with a good accuracy. On the other hand, its response to rapid deterioration is either a long delay in recognising the fault, and/or a spread of the estimated fault on several components. The main reason of this deficiency lies in the transition model of the parameters that assumes a smooth evolution of the engine condition. The aim of this contribution is to compare two adaptive diagnosis tools that combine a Kalman filter and a secondary system that monitors the residuals. This auxiliary component implements on one hand a covariance matching scheme and on the other hand a generalised likelihood ratio test to improve the behaviour of the diagnosis tool with respect to abrupt faults.
Disciplines :
Mechanical engineering
Aerospace & aeronautics engineering
Computer science
Materials science & engineering
Author, co-author :
Borguet, Sébastien ;  Université de Liège - ULiège > Département d'aérospatiale et mécanique > Turbomachines et propulsion aérospatiale
Léonard, Olivier ;  Université de Liège - ULiège > Département d'aérospatiale et mécanique > Turbomachines et propulsion aérospatiale
Language :
English
Title :
Comparison of Adaptive Filtering Schemes for Gas Turbine Performance Diagnostics
Publication date :
2008
Event name :
Fourth International Conference on Advanced Computational Methods in Engineering (ACOMEN'08)
Event organizer :
University of Liège
Event place :
Liège, Belgium
Event date :
26-28 May 2008
Audience :
International
Journal title :
Proceedings of the 4th International Conference on Advanced Computational Methods in Engineering
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since 03 September 2009

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