IDENTIFICATION AND MODEL UPDATING OF A NON-STATIONARY VIBRATING SYSTEM

Non-stationary systems, which are commonly encountered in many fields of science, are characterized by time-varying features and require time-frequency methods for their analysis. This study considers the problem of identification and model updating of a non-stationary vibrating system. In particular, a number of identification methods and a model updating procedure are evaluated and compared through application to a time-varying “bridge-like” laboratory structure. The identification approaches include Frequency Response Function based parameter estimation techniques, Subspace Identification and Functional Series modelling. All methods are applied to both output-only and input-out-put data. Model updating is based upon a theoretical model of the structure obtained using a Rayleigh-Ritz methodology, which is updated to account for time-dependence and nonlinearity via the identification results. Interesting comparisons, among both identification and model updating results, are performed. The results of the study demonstrate high modelling accuracy, illustrating the effectiveness of model updating techniques in non-stationary vibration modelling.Copyright © 2004 by ASME

[1]  G. N. Fouskitakis,et al.  On the Estimation of Nonstationary Functional Series TARMA Models: An Isomorphic Matrix Algebra Based Method , 2001 .

[2]  Mark Richardson,et al.  PARAMETER ESTIMATION FROM FREQUENCY RESPONSE MEASUREMENTS USING RATIONAL FRACTION POLYNOMIALS (TWENTY YEARS OF PROGRESS) , 1982 .

[3]  J. Cooper,et al.  A time–frequency technique for the stability analysis of impulse responses from nonlinear aeroelastic systems , 2003 .

[4]  Maciej Niedzwiecki,et al.  Identification of Time-Varying Processes , 2000 .

[5]  J.B. Allen,et al.  A unified approach to short-time Fourier analysis and synthesis , 1977, Proceedings of the IEEE.

[6]  Spilios D. Fassois,et al.  On the estimation of non-stationary functional series tarma models , 2005, 2005 13th European Signal Processing Conference.

[7]  M. B. Priestley,et al.  Non-linear and non-stationary time series analysis , 1990 .

[8]  Gaoyong Luo,et al.  Vibration modelling with fast Gaussian wavelet algorithm , 2002 .

[9]  Bart De Moor,et al.  N4SID: Subspace algorithms for the identification of combined deterministic-stochastic systems , 1994, Autom..

[10]  John E. Mottershead,et al.  Finite Element Model Updating in Structural Dynamics , 1995 .

[11]  Sun Ung Lee,et al.  THE DIRECTIONAL CHOI–WILLIAMS DISTRIBUTION FOR THE ANALYSIS OF ROTOR-VIBRATION SIGNALS , 2001 .

[12]  S. Conforto,et al.  SPECTRAL ANALYSIS FOR NON-STATIONARY SIGNALS FROM MECHANICAL MEASUREMENTS: A PARAMETRIC APPROACH , 1999 .

[13]  Spilios D. Fassois,et al.  Non-stationary mechanical vibration modeling and analysis via functional series tarma models , 2003 .

[14]  Khaled H. Hamed,et al.  Time-frequency analysis , 2003 .

[15]  Bart De Moor,et al.  Subspace algorithms for the stochastic identification problem, , 1993, Autom..

[16]  S. Fassois,et al.  NON-STATIONARY FUNCTIONAL SERIES TARMA VIBRATION MODELLING AND ANALYSIS IN A PLANAR MANIPULATOR , 2000 .

[17]  Spilios D. Fassois,et al.  A polynomial-algebraic method for non-stationary TARMA signal analysis - Part I: The method , 1998, Signal Process..

[18]  J. Schoukens,et al.  Parametric identification of transfer functions in the frequency domain-a survey , 1994, IEEE Trans. Autom. Control..