Reference : Coupling principal component analysis and Kalman filtering algorithms for on-line air...
Scientific journals : Article
Engineering, computing & technology : Aerospace & aeronautics engineering
Physical, chemical, mathematical & earth Sciences : Space science, astronomy & astrophysics
Physical, chemical, mathematical & earth Sciences : Physics
http://hdl.handle.net/2268/19949
Coupling principal component analysis and Kalman filtering algorithms for on-line aircraft engine diagnostics
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 >]
Apr-2009
Control Engineering Practice
Pergamon Press - An Imprint of Elsevier Science
17
4
494-502
Yes (verified by ORBi)
International
0967-0661
[en] Condition monitoring ; Jet engine ; Kalman filter ; Principal component analysis ; Information fusion
[en] Engine health monitoring has been an area of intensive research for more than three decades. Numerous methods have been developed with the goal of performing an accurate assessment of the engine condition. It is generally accepted that a practical implementation of a monitoring tool will rely on a combination of several techniques. In this framework, the present contribution proposes an original approach for coupling two diagnostic tools in order to enhance the capability of an engine health monitoring system. One tool is based on a principal component analysis scheme and the other is based on a Kalman filter technique. The three methodologies are compared and the benefit of the combined tool is demonstrated on simulated fault cases which can be expected in a commercial turbofan layout. (C) 2008 Elsevier Ltd. All rights reserved.
Researchers ; Professionals ; Students
http://hdl.handle.net/2268/19949
10.1016/j.conengprac.2008.09.008

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