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Descripción
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| Experimental modal analysis consists on estimating the modal parameters of a structural/mechanical system (a footbridge in this case) from sensors measurements. The process can be described as: 1) measure the vibrations of the footbridge at different points using accelerometers; 2) estimate a state space model from the multivariate time series of accelerations; 3) compute the modal parameters from the eigenvalues of the state space matrices. This work analyses the application of the bootstrap to compute the standard error of the modal parameters. First, the method proposed in \cite{stoffer1991} is applied. The main problem observed with this approach is that the residuals are autocorrelated, so the cannot be resampled. Then, a sieve bootstrap is applied to the residuals, and these residuals are used to generate the bootstrap replicates. Therefore, the proposed method can be described as a two-step bootstrap. | |
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Internacional
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No |
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Nombre congreso
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Statistical Methods for Big Data (SMBD2018) |
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Tipo de participación
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970 |
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Lugar del congreso
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Madrid |
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Revisores
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Si |
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ISBN o ISSN
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000-00-00-00000-0 |
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DOI
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Fecha inicio congreso
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05/06/2018 |
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Fecha fin congreso
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06/06/2018 |
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Desde la página
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1 |
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Hasta la página
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2 |
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Título de las actas
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Statistical Methods for Big Data (SMBD2018) |