Modal contribution and state space order selection in operational modal analysis

Cara Cañas, Francisco Javier; Juan Ruiz, Jesús; Alarcón Álvarez, Enrique; Reynders, Edwin y 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.

Descripción

Título: Modal contribution and state space order selection in operational modal analysis
Autor/es:
  • Cara Cañas, Francisco Javier
  • Juan Ruiz, Jesús
  • Alarcón Álvarez, Enrique
  • Reynders, Edwin
  • De Roeck, Guido
Tipo de Documento: Artículo
Título de Revista/Publicación: Mechanical Systems and Signal Processing
Fecha: 20 Julio 2013
Volumen: 38
Materias:
Palabras Clave Informales: Structural dynamics; Operational modal analysis; Stochastic system identification; Kalman filtering; State space model order; Stabilization diagram
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

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.

Más información

ID de Registro: 15310
Identificador DC: http://oa.upm.es/15310/
Identificador OAI: oai:oa.upm.es:15310
Identificador DOI: 10.1016/j.ymssp.2013.03.001
URL Oficial: http://www.sciencedirect.com/science/article/pii/S0888327013001015
Depositado por: Biblioteca ETSI Industriales
Depositado el: 10 Jun 2013 13:36
Ultima Modificación: 21 Abr 2016 15:22
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