Estimating the modal parameters from multiple measurement setups using a joint state space model

Cara Cañas, Francisco Javier; Juan Ruiz, Jesús y Alarcón Álvarez, Enrique (2014). Estimating the modal parameters from multiple measurement setups using a joint state space model. "Mechanical Systems and Signal Processing", v. 43 (n. 1-2); pp. 171-191. ISSN 0888-3270. https://doi.org/10.1016/j.ymssp.2013.09.012.

Descripción

Título: Estimating the modal parameters from multiple measurement setups using a joint state space model
Autor/es:
  • Cara Cañas, Francisco Javier
  • Juan Ruiz, Jesús
  • Alarcón Álvarez, Enrique
Tipo de Documento: Artículo
Título de Revista/Publicación: Mechanical Systems and Signal Processing
Fecha: 3 Febrero 2014
Volumen: 43
Materias:
Palabras Clave Informales: Assembled mode shapes ; Multi-setup operational modal analysis ; Maximum likelihood estimation ; Expectation Maximization algorithm ; State space model
Escuela: E.T.S.I. Industriales (UPM)
Departamento: Ingeniería de Organización, Administración de Empresas y Estadística
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Computing the modal parameters of structural systems often requires processing data from multiple non-simultaneously recorded setups of sensors. These setups share some sensors in common, the so-called reference sensors, which are fixed for all measurements, while the other sensors change their position from one setup to the next. One possibility is to process the setups separately resulting in different modal parameter estimates for each setup. Then, the reference sensors are used to merge or glue the different parts of the mode shapes to obtain global mode shapes, while the natural frequencies and damping ratios are usually averaged. In this paper we present a new state space model that processes all setups at once. The result is that the global mode shapes are obtained automatically, and only a value for the natural frequency and damping ratio of each mode is estimated. We also investigate the estimation of this model using maximum likelihood and the Expectation Maximization algorithm, and apply this technique to simulated and measured data corresponding to different structures.

Más información

ID de Registro: 23414
Identificador DC: http://oa.upm.es/23414/
Identificador OAI: oai:oa.upm.es:23414
Identificador DOI: 10.1016/j.ymssp.2013.09.012
URL Oficial: http://www.sciencedirect.com/science/article/pii/S0888327013004998
Depositado por: Biblioteca ETSI Industriales
Depositado el: 08 Abr 2014 05:50
Ultima Modificación: 03 Feb 2016 23:56
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