Ambient modal identification, also known as Operational Modal Analysis (OMA), aims to identify the modal properties of a structure based on vibration data collected when the structure is under its operating conditions, i.e., no initial excitation or known artificial excitation. This procedure for testing and/or monitoring historic buildings, is particularly attractive for civil engineers concerned with the safety of complex historic structures. However, since the external force is not recorded, the identification methods have to be more sophisticated and based on stochastic mechanics. In this context, this contribution will introduce an innovative ambient identification method based on applying the Hilbert Transform, to obtain the analytical representation of the system response in terms of the correlation function. In particular, it is worth stressing that the analytical signal is a complex representation of a time domain signal: the real part is the time domain signal itself, while the imaginary part is its Hilbert transform. A 3DOF numerical example will be presented to show the accuracy of the proposed procedure, and comparisons with data from other methods assess the reliability of the approach.

Masnata, C., Bilello, C., Di Matteo, A., Dunn, I., Pirrotta, A. (2020). An innovative ambient identification method. In A.P. Antonio Carcaterra (a cura di), Proceedings of XXIV AIMETA Conference 2019 (pp. 1608-1624) [10.1007/978-3-030-41057-5_130].

An innovative ambient identification method

Masnata, C.;Bilello, C.;Di Matteo, A.
;
Dunn, I.;Pirrotta, A
2020-01-01

Abstract

Ambient modal identification, also known as Operational Modal Analysis (OMA), aims to identify the modal properties of a structure based on vibration data collected when the structure is under its operating conditions, i.e., no initial excitation or known artificial excitation. This procedure for testing and/or monitoring historic buildings, is particularly attractive for civil engineers concerned with the safety of complex historic structures. However, since the external force is not recorded, the identification methods have to be more sophisticated and based on stochastic mechanics. In this context, this contribution will introduce an innovative ambient identification method based on applying the Hilbert Transform, to obtain the analytical representation of the system response in terms of the correlation function. In particular, it is worth stressing that the analytical signal is a complex representation of a time domain signal: the real part is the time domain signal itself, while the imaginary part is its Hilbert transform. A 3DOF numerical example will be presented to show the accuracy of the proposed procedure, and comparisons with data from other methods assess the reliability of the approach.
Settore ICAR/08 - Scienza Delle Costruzioni
Masnata, C., Bilello, C., Di Matteo, A., Dunn, I., Pirrotta, A. (2020). An innovative ambient identification method. In A.P. Antonio Carcaterra (a cura di), Proceedings of XXIV AIMETA Conference 2019 (pp. 1608-1624) [10.1007/978-3-030-41057-5_130].
File in questo prodotto:
File Dimensione Formato  
AN INNOVATIVE AMBIENT IDENTIFICATION METHOD.pdf

Solo gestori archvio

Tipologia: Post-print
Dimensione 2.19 MB
Formato Adobe PDF
2.19 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/401499
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact