Reference : A Quadratic Programming Framework for Constrained and Robust Jet Engine
Parts of books : Contribution to collective works
Engineering, computing & technology : Mechanical engineering
Physical, chemical, mathematical & earth Sciences : Mathematics
Physical, chemical, mathematical & earth Sciences : Physics
Engineering, computing & technology : Aerospace & aeronautics engineering
Physical, chemical, mathematical & earth Sciences : Space science, astronomy & astrophysics
http://hdl.handle.net/2268/19961
A Quadratic Programming Framework for Constrained and Robust Jet Engine
English
Borguet, Sébastien mailto [Université de Liège - ULg > Département d'aérospatiale et mécanique > Turbomachines et propulsion aérospatiale >]
Léonard, Olivier mailto [Université de Liège - ULg > Département d'aérospatiale et mécanique > Turbomachines et propulsion aérospatiale >]
2009
EUCASS Advances in Aerospace Sciences : Propulsion Physics
Torus Press
675-698
978-2-7598-0411-5
Moscow
[en] Kalman filters ; jet engine ; Quadratic Programming Framework
[en] Kalman filters are largely used in the jet engine community for condition monitoring purpose. This algorithm gives a good estimate of the engine condition provided that the residuals between the model prediction and the measurements are zero-mean, Gaussian random variables. In the case of sensor faults, this assumption does not hold anymore and consequently the diagnosis is spoiled. This contribution presents a recursive estimation algorithm based on a Quadratic Programming formulation which provides robustness against sensor faults and allows constraints on the health parameters to be specified. The improvements in estimation accuracy brought by this new algorithm are illustrated by a series of typical test-cases that may be encountered on current turbofan engines.
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/19961

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