Modal contribution and state space order selection in operational modal analysis

Cara Cañas, Francisco Javier and Juan Ruiz, Jesús and Alarcón Álvarez, Enrique and Reynders, Edwin and De Roeck, Guido (2013). Modal contribution and state space order selection in operational modal analysis. "Mechanical Systems and Signal Processing", v. 38 (n. 2); pp. 276-298. ISSN 0888-3270. https://doi.org/10.1016/j.ymssp.2013.03.001.

Description

Title: Modal contribution and state space order selection in operational modal analysis
Author/s:
  • Cara Cañas, Francisco Javier
  • Juan Ruiz, Jesús
  • Alarcón Álvarez, Enrique
  • Reynders, Edwin
  • De Roeck, Guido
Item Type: Article
Título de Revista/Publicación: Mechanical Systems and Signal Processing
Date: 20 July 2013
Volume: 38
Subjects:
Freetext Keywords: Structural dynamics; Operational modal analysis; Stochastic system identification; Kalman filtering; State space model order; Stabilization diagram
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

The estimation of modal parameters of a structure from ambient measurements has attracted the attention of many researchers in the last years. The procedure is now well established and the use of state space models, stochastic system identification methods and stabilization diagrams allows to identify the modes of the structure. In this paper the contribution of each identified mode to the measured vibration is discussed. This modal contribution is computed using the Kalman filter and it is an indicator of the importance of the modes. Also the variation of the modal contribution with the order of the model is studied. This analysis suggests selecting the order for the state space model as the order that includes the modes with higher contribution. The order obtained using this method is compared to those obtained using other well known methods, like Akaike criteria for time series or the singular values of the weighted projection matrix in the Stochastic Subspace Identification method. Finally, both simulated and measured vibration data are used to show the practicability of the derived technique. Finally, it is important to remark that the method can be used with any identification method working in the state space model.

More information

Item ID: 15310
DC Identifier: http://oa.upm.es/15310/
OAI Identifier: oai:oa.upm.es:15310
DOI: 10.1016/j.ymssp.2013.03.001
Official URL: http://www.sciencedirect.com/science/article/pii/S0888327013001015
Deposited by: Biblioteca ETSI Industriales
Deposited on: 10 Jun 2013 13:36
Last Modified: 21 Apr 2016 15:22
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