Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Boostraping state space models in experimental modal analysis of a footbridge
Year:2018
Research Areas
  • Statistics,
  • Civil engineering
Information
Abstract
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.
International
No
Congress
Statistical Methods for Big Data (SMBD2018)
970
Place
Madrid
Reviewers
Si
ISBN/ISSN
000-00-00-00000-0
Start Date
05/06/2018
End Date
06/06/2018
From page
1
To page
2
Statistical Methods for Big Data (SMBD2018)
Participants
  • Autor: Francisco Javier Cara Cañas (UPM)
  • Autor: Jesus Juan Ruiz (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Estadística computacional y Modelado estocástico
  • Departamento: Ingeniería de Organización, Administración de Empresas y Estadística
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