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

Cara Cañas, Francisco Javier and Juan Ruiz, Jesús and 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.

Description

Title: Estimating the modal parameters from multiple measurement setups using a joint state space model
Author/s:
  • Cara Cañas, Francisco Javier
  • Juan Ruiz, Jesús
  • Alarcón Álvarez, Enrique
Item Type: Article
Título de Revista/Publicación: Mechanical Systems and Signal Processing
Date: 3 February 2014
ISSN: 0888-3270
Volume: 43
Subjects:
Freetext Keywords: Assembled mode shapes ; Multi-setup operational modal analysis ; Maximum likelihood estimation ; Expectation Maximization algorithm ; State space model
Faculty: E.T.S.I. Industriales (UPM)
Department: Ingeniería de Organización, Administración de Empresas y Estadística
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

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.

More information

Item ID: 23414
DC Identifier: http://oa.upm.es/23414/
OAI Identifier: oai:oa.upm.es:23414
DOI: 10.1016/j.ymssp.2013.09.012
Official URL: http://www.sciencedirect.com/science/article/pii/S0888327013004998
Deposited by: Biblioteca ETSI Industriales
Deposited on: 08 Apr 2014 05:50
Last Modified: 03 Feb 2016 23:56
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