Nonlinear identification; Subspace-based method; Spurious poles; Model reduction; Frequency residuals
Abstract :
[en] The introduction of the frequency-domain nonlinear subspace identification (FNSI) method in 2013 constitutes one in a series of recent attempts toward developing a realistic, first-generation framework applicable to complex structures. If this method showed promising capabilities when applied to academic structures, it is still confronted with a number of limitations which needs to be addressed. In particular, the removal of nonphysical poles in the identified nonlinear models is a distinct challenge. In the present paper, it is proposed as a first contribution to operate directly on the identified state-space matrices to carry out spurious pole removal. A modal-space decomposition of the state and output matrices is examined to discriminate genuine from numerical poles, prior to estimating the extended input and feedthrough matrices. The final state-space model thus contains physical information only and naturally leads to nonlinear coefficients free of spurious variations. Besides spurious variations due to nonphysical poles, vibration modes lying outside the frequency band of interest may also produce drifts of the nonlinear coefficients. The second contribution of the paper is to include residual terms, accounting for the existence of these modes. The proposed improved FNSI methodology is validated numerically and experimentally using a full-scale structure, the Morane-Saulnier Paris aircraft.
Disciplines :
Aerospace & aeronautics engineering
Author, co-author :
De Filippis, Giovanni; Politecnico di Bari
Noël, Jean-Philippe ; Université de Liège - ULiège > Département d'aérospatiale et mécanique > Laboratoire de structures et systèmes spatiaux
Kerschen, Gaëtan ; Université de Liège - ULiège > Département d'aérospatiale et mécanique > Laboratoire de structures et systèmes spatiaux
Soria, Leonardo; Politecnico di Bari
Stephan, Cyrille; ONERA
Language :
English
Title :
Model reduction and frequency residuals for a robust estimation of nonlinearities in subspace identification
Publication date :
September 2017
Journal title :
Mechanical Systems and Signal Processing
ISSN :
0888-3270
eISSN :
1096-1216
Publisher :
Elsevier, Atlanta, United States
Volume :
93
Pages :
312-331
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
F.R.S.-FNRS - Fonds de la Recherche Scientifique [BE]
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