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Statistical asymptotic error on modal parameters in combined deterministic–stochastic identification algorithm

Authors
Journal
Mechanical Systems and Signal Processing
0888-3270
Publisher
Elsevier
Publication Date
Volume
19
Issue
4
Identifiers
DOI: 10.1016/j.ymssp.2004.11.001
Keywords
  • Modal Analysis
  • Identification
  • Subspace Methods
  • Statistics
  • Confidence Interval

Abstract

Abstract This paper deals with the estimation of the statistical dispersion of the modal parameters of a structure, frequencies and damping ratios obtained from subspace identification. The main objective is to apply, after some useful modifications, the theory of the covariance estimates of the poles to simulation and experimental cases and evaluate its performances in a real situation. A formulation of the asymptotic distribution of the dynamic matrix estimates given in literature is slightly modified to be directly interpretable in terms of accelerations. The method is extended to the modal parameters of a structure, which are non-linear functions of these estimates. The accuracy of the method is first analysed in simulation on the case of a spring–mass–damper system. Finally, the theory is applied to a real test case consisting of a reduced model of a two-floor building submitted to random excitation.

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