On-line aircraft engine diagnostic using a soft-constrained Kalman filter

Dewallef, P; Leonard, O; Mathioudakis, K

dc.contributor.author	Dewallef, P	en
dc.contributor.author	Leonard, O	en
dc.contributor.author	Mathioudakis, K	en
dc.date.accessioned	2014-03-01T02:49:51Z
dc.date.available	2014-03-01T02:49:51Z
dc.date.issued	2004	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34758
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-10244257658&partnerID=40&md5=bd707f043e1b6245648dd1d0722f38a9	en
dc.subject.other	Aircraft engines	en
dc.subject.other	Constraint theory	en
dc.subject.other	Data acquisition	en
dc.subject.other	Kalman filtering	en
dc.subject.other	Linearization	en
dc.subject.other	Matrix algebra	en
dc.subject.other	Optimization	en
dc.subject.other	Parameter estimation	en
dc.subject.other	Problem solving	en
dc.subject.other	Regression analysis	en
dc.subject.other	Turbines	en
dc.subject.other	Covariance matrix	en
dc.subject.other	Kalman gains	en
dc.subject.other	Self-constrained Kalman filters	en
dc.subject.other	Turbine engine diagnostic	en
dc.subject.other	Online systems	en
dc.title	On-line aircraft engine diagnostic using a soft-constrained Kalman filter	en
heal.type	conferenceItem	en
heal.publicationDate	2004	en
heal.abstract	The purpose of this contribution is to apply ridge regression to Kalman filtering in order to stabilize a health parameter identification under low or negative redundancy. The resulting algorithm achieves a so-called soft-constrained recursive health parameter identification, i.e. constraints are applied to parameters in a statistical way, contrary to hard-constrained algorithms based on strong equality or inequality constrains. The method is tested on data generated by a steady state turbofan engine model and representing typical component faults. The benefits that can be realized in terms of stability and accuracy are highlighted and some limits of the method are also mentioned.	en
heal.journalName	Proceedings of the ASME Turbo Expo 2004	en
dc.identifier.volume	2	en
dc.identifier.spage	585	en
dc.identifier.epage	594	en