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|Title:||On the use of dispersion analysis for model assessment in structural identification||Authors:||Dertimanis, Vasilis||Keywords:||Covariance matrix;Dispersion analysis;Energy analysis;Experimental/operational modal analysis||Category:||Civil Engineering;Civil Engineering||Field:||Engineering and Technology||Issue Date:||1-Nov-2013||Publisher:||SAGE||Source:||JVC/Journal of Vibration and Control, 2013, Volume 19, Issue 15, Pages 2270-2284||DOI:||10.1177/1077546313501536||Abstract:||One of the most important issues faced in parametric time-domain identification and subsequent experimental/operational modal analysis is the correct estimation of model order, which in turn determines the number of structural vibration modes. The aim of this study is to provide a quantitative and physically meaningful framework for model order assessment that is characterized by global applicability, in the sense of implementation in both state-space and transfer function model representations. To this end and under the assumption of stationary wideband excitation, a novel dispersion analysis scheme is proposed for the quantification of every mode's relative importance to the total stochastic response, which is based on a modal decomposition of the covariance matrix. Subsequently, after defining the modal dispersion matrix, a corresponding metric is introduced and used either as a stand alone tool for model order assessment, or as an extension of existing tools, such as stabilization diagrams. The method is validated through both simulated (NASA Mini-Mast truss) and experimental (suspended steel subframe flexible structure) identification problems, for which a subspace and a prediction-error estimation method are utilized and compared under the proposed quantitative indices. Moreover, performance comparisons with other energy-based metrics are also reported. The results indicate that the proposed method can be effectively used in parametric time-domain structural identification, for both order assessment and comparison of diverse model-based estimation methods.||URI:||http://ktisis.cut.ac.cy/handle/10488/9834||ISSN:||10775463||Rights:||© The Author(s) 2013||Type:||Article|
|Appears in Collections:||Άρθρα/Articles|
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