Joint statistical analysis of multiple measurement setups for the estimation of vibrational modes

Cara Cañas, Francisco Javier; Juan Ruiz, Jesús y Alarcón Álvarez, Enrique (2013). Joint statistical analysis of multiple measurement setups for the estimation of vibrational modes. En: "IOMAC'13 - 5th. International Operational Modal Analysis Conference", 13/05/2013-15/05/2013, Guimaraes (Portugal).

Descripción

Título: Joint statistical analysis of multiple measurement setups for the estimation of vibrational modes
Autor/es:
  • Cara Cañas, Francisco Javier
  • Juan Ruiz, Jesús
  • Alarcón Álvarez, Enrique
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: IOMAC'13 - 5th. International Operational Modal Analysis Conference
Fechas del Evento: 13/05/2013-15/05/2013
Lugar del Evento: Guimaraes (Portugal)
Título del Libro: IOMAC'13 - 5th. International Operational Modal Analysis Conference
Fecha: 2013
Materias:
Palabras Clave Informales: Multi-Setup Operational Modal Analysis, Assembling Mode shapes, Maximum Likelihood Estimation, Expectation Maximization Algorithm
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 large structures in Operational Modal Analysis often requires to process data from multiple non simultaneously recorded setups of sensors. These setups share some sensors in common, the so-called reference sensors that are fixed for all the measurements, while the other sensors are moved from one setup to the next. One possibility is to process the setups separately what result 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 modes, while the natural frequencies and damping ratios are usually averaged. In this paper we present a state space model that can be used to process all setups at once so the global mode shapes are obtained automatically and subsequently only a value for the natural frequency and damping ratio of each mode is computed. We also present how this model can be estimated using maximum likelihood and the Expectation Maximization algorithm. We apply this technique to real data measured at a footbridge.

Más información

ID de Registro: 30114
Identificador DC: http://oa.upm.es/30114/
Identificador OAI: oai:oa.upm.es:30114
URL Oficial: http://www.iomac.dk/
Depositado por: Biblioteca ETSI Industriales
Depositado el: 20 Jun 2014 08:35
Ultima Modificación: 22 Sep 2014 11:47
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