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Vibratory diagnosis by finite element model updating andoperational modal analysis

Published online by Cambridge University Press:  12 June 2013

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Abstract

In this paper, a subspace fitting method is proposed to update, in the time domain, thefinite element model of a rotating machine. The procedure is achieved by minimizing anerror norm, leading to the comparison between experimental and theoretical observabilitymatrices. Experimental observability matrix is obtained through a MOESP subspaceidentification algorithm, by projecting the output signal onto some appropriate subspaces,resulting in a cancellation of input excitations and noises. The theoretical observabilitymatrix is obtained from modal parameters of a finite element model of the structure. Theminimization procedure is carried out through a Gauss-Newton algorithm. The method isapplied to determine the foundation stiffness of an experimental rotating machine subjectto a random noise.

Type
Research Article
Copyright
© AFM, EDP Sciences 2013

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References

Doebling, S.W., Farrar, C.R., Prime, M.B., A summary review of vibration-based damage identification methods, Shock Vibr. Dig. 30 (1998) 91105 CrossRefGoogle Scholar
Mottershead, J.E., Friswell, M.I., Model updating in structural dynamics: a survey, J. Sound Vibr. 167 (1993) 347375 CrossRefGoogle Scholar
L.M. Zhang, An overview of major development and issues in modal identification, In IMAC XXII: A Conference and Exposition on Structural Dynamics, 2004.
Favoreel, W., De Moor, B., Van Overschee, P., Subspace state space system identification for industrial processes, J. Process Control 10 (2000) 149155 CrossRefGoogle Scholar
P. Van Overschee, B. DeMoor, Subspace Identification of Linear Systems: Theory, Implementation, Applications, Kluwer Academic Publishers, 1996
Viberg, M., Wahlberg, B., Ottersten, B., Analysis of state space system identification methods based on instrumental variables and subspace fitting, Automatica 33 (1997) 16031616 CrossRefGoogle Scholar
Lee Swindlehurst, A., Ottersten, B., Roy, R., Kailath, T.. A subspace fitting method for identification of linear state-space models, IEEE Trans. Automatic Control 40 (1995) 311316 CrossRefGoogle Scholar
R. Serra, C. Gontier, M. Raffy, A subspace fitting method for structural modal identification in time domain, In ISMA 25: International Conference on Noise and Vibration Engineering, 2000
Lee Swindlehurst, A., Ottersten, B., Kailath, T. Roy, R., Multiple invariance esprit, IEEE Trans. Signal Process. 40 (1992) 867881 CrossRefGoogle Scholar
Golub, G.H., Pereyra, V., The differentiation of pseudo-inverses and nonlinear least squares problems whose variables separate, SIAM J, 10 (1973) 413432 Google Scholar
Friswell, M.I., Penny, J.E.T., Crack modeling for structural health monitoring, Structural Health Monitoring 1 (2002) 139148 CrossRefGoogle Scholar
M. Lalanne, G. Ferraris, Rotordynamics Prediction in Engineering, Wiley, 1990