Publication
Title
Frequency-domain generalized total least-squares identification for modal analysis
Author
Abstract
This contribution focuses on the area of modal analysis and studies the applicability of total least-squares (TLS) algorithms for the estimation of modal parameters in the frequency-domain from input-output Fourier data. These algorithms can be preferable to classical frequency response function based curve-fitting methods. This is certainly the case when periodic excitation is applied and an errors-in-variables noise model can be determined. The proposed generalized total least-squares (GTLS) algorithm provides an accurate modal parameter estimation by the integration of this noise model in the parametric identification process. Modal-based design and comfort improvement, damage assessment and structural health monitoring, and finite element model updating are important applications that strongly rely on a high accuracy of the modal model. In this paper it is shown how frequency-domain TLS and GTLS estimators can be numerically optimized to handle large amounts of modal data. In order to use an errors-in-variables noise model, a linear approximation is necessary in order to obtain a fast implementation of the GTLS algorithm. The validity of this approximation is a function of the signal-to-noise ratio of the input Fourier data and is evaluated by means of Monte Carlo simulations and experimental data. (C) 2003 Elsevier Ltd. All rights reserved.
Language
English
Source (journal)
Journal of sound and vibration / University of Southampton. Institute of Sound and Vibration Research. - London
Publication
London : 2004
ISSN
0022-460X
Volume/pages
278:1-2(2004), p. 21-38
ISI
000224594200002
Full text (Publisher's DOI)
UAntwerpen
Faculty/Department
Publication type
Subject
External links
Web of Science
Record
Identification
Creation 04.11.2014
Last edited 05.06.2017