Article (Scientific journals)
Comparison of adaptive filters for gas turbine performance monitoring
Borguet, Sébastien; Léonard, Olivier
2010In Journal of Computational and Applied Mathematics, 234 (7), p. 2202-2212
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Keywords :
Kalman filters; gas path analysis; adaptive estimation; Generalised Likelihood Ratio; covariance matching
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 recognizing 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 :
Physics
Materials science & engineering
Mechanical engineering
Engineering, computing & technology: Multidisciplinary, general & others
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 filters for gas turbine performance monitoring
Publication date :
2010
Journal title :
Journal of Computational and Applied Mathematics
ISSN :
0377-0427
eISSN :
1879-1778
Publisher :
Elsevier Science, Amsterdam, Netherlands
Volume :
234
Issue :
7
Pages :
2202-2212
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 26 August 2009

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