Operational modal analysis for estimating the dynamic properties of a stadium structure during a football game
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In this paper, the ambient vibrations at the roof of a football stadium were recorded during a football game and the data set was also split in shorter segments corresponding to certain events before, during and after the game to investigate the influence of varying operational conditions on the dynamic properties.Abstract:
During a football game, the ambient vibrations at the roof of a football stadium were recorded. A very large data set consisting of 4 hours of data, sampled at 80 Hz, is available. By a data reduction procedure, the complete data set could be analysed at once in a very short time. The data set was also split in shorter segments corresponding to certain events before, during and after the game to investigate the influence of varying operational conditions on the dynamic properties.read more
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References
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Book
Subspace Identification for Linear Systems: Theory - Implementation - Applications
Peter Van Overschee,Bart De Moor +1 more
TL;DR: This book focuses on the theory, implementation and applications of subspace identification algorithms for linear time-invariant finitedimensional dynamical systems, which allow for a fast, straightforward and accurate determination of linear multivariable models from measured inputoutput data.
Journal ArticleDOI
Reference-based stochastic subspace identification for output-only modal analysis
Bart Peeters,Guido De Roeck +1 more
TL;DR: In this paper, a novel approach of stochastic subspace identification is presented that incorporates the idea of the reference sensors already in the identification step: the row space of future outputs is projected into the rowspace of past reference outputs.
Modal Identification from Ambient Responses Using Frequency Domain Decomposition
TL;DR: In this paper, a decomposition of the spectral density function matrix is introduced for modal identification from ambient responses, i.e. in the case where the modal parameters must be estimated without knowing the input of the system.
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