Article: Influence of model order and number of block rows on accuracy and precision of modal parameter estimates in stochastic subspace identification Journal: International Journal of Lifecycle Performance Engineering (IJLCPE) 2014 Vol.1 No.4 pp.317 - 334 Abstract: The accurate estimation of the modal properties of civil structures in operational conditions is critical in a number of applications, including structural health monitoring. The available algorithms allow confident estimations of modal frequencies and mode shapes. Damping estimates, instead, are jeopardised by large error bounds, related to the non-linear behaviour of damping as well as to inherent limits of the estimators and eventually poor measurements. In general, the variability of modal parameter estimates is due not only to environmental factors but also to the performance of the estimator. Thus, the accuracy of the estimator has to be optimised to avoid errors in automated modal parameter identification. In this paper, the influence of model order and number of block rows on the accuracy of estimates via stochastic subspace identification (SSI) is investigated. An approach able to provide narrow error bounds and improve the reliability of SSI-based automated modal identification algorithms is discussed. Inderscience Publishers - linking academia, business and industry through research

Title: Influence of model order and number of block rows on accuracy and precision of modal parameter estimates in stochastic subspace identification

Authors: Carlo Rainieri; Giovanni Fabbrocino

Addresses: Structural and Geotechnical Dynamics Laboratory StreGa, DiBt Department, University of Molise, Via Duca degli Abruzzi – 86039 Termoli, Campobasso, Italy ' Structural and Geotechnical Dynamics Laboratory StreGa, DiBt Department, University of Molise, Via Duca degli Abruzzi – 86039 Termoli, Campobasso, Italy

Abstract: The accurate estimation of the modal properties of civil structures in operational conditions is critical in a number of applications, including structural health monitoring. The available algorithms allow confident estimations of modal frequencies and mode shapes. Damping estimates, instead, are jeopardised by large error bounds, related to the non-linear behaviour of damping as well as to inherent limits of the estimators and eventually poor measurements. In general, the variability of modal parameter estimates is due not only to environmental factors but also to the performance of the estimator. Thus, the accuracy of the estimator has to be optimised to avoid errors in automated modal parameter identification. In this paper, the influence of model order and number of block rows on the accuracy of estimates via stochastic subspace identification (SSI) is investigated. An approach able to provide narrow error bounds and improve the reliability of SSI-based automated modal identification algorithms is discussed.

Keywords: operational modal analysis; stochastic subspace identification; SSI; error estimation; inverse problems; sensitivity analysis; model order; block rows; modal parameter estimation; civil structures; modal identification.

DOI: 10.1504/IJLCPE.2014.064099

International Journal of Lifecycle Performance Engineering, 2014 Vol.1 No.4, pp.317 - 334

Received: 14 Oct 2013
Accepted: 25 Feb 2014
Published online: 30 Aug 2014 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article

Title: Influence of model order and number of block rows on accuracy and precision of modal parameter estimates in stochastic subspace identification

Keep up-to-date