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Transmissibility based OMA for time-varying loading conditions

Boekbijdrage - Boekhoofdstuk Conferentiebijdrage

Periodical loads, such as waves and rotating machinery, are a problem for operational modal analysis (OMA). In OMA only the vibrations of a structure of interest are measured and little to nothing is known about the loads causing these vibrations. Therefore, it is often assumed that all dynamics in the measured data are linked to the system of interest.
A novel approach to this problem is the research into time-varying transmissibilities for OMA, recently pub- lished in MSSP. In that contribution it was shown how to use time-varying single-reference transmissibilities to estimate the modal parameters from a single dataset without being influenced by the periodical loads. However, transmissibilities are only independent of the input spectra, and therefor the periodical loads, when the number of references equals the number of uncorrelated loads. This property limits the applicability of a single-reference approach to systems excited by a single distributed load.
The solution is to use multi-reference transmissibilities for OMA a.k.a. pTOMA. With pTOMA the estimated modal parameters can again be independent of the input spectra. The main goal of this paper is to expand the estimation of time-varying transmissibilities to multi-reference transmissibilities. And to use these time- varying multi-reference transmissibilities for pTOMA. This paper will recapitulate the time-varying version of single reference TOMA. We will introduce the time-varying version of multi-reference TOMA (pTOMA). The newly introduced algorithm will be demonstrated and discussed trough a lab experiment.
Boek: PROCEEDINGS OF ISMA2014 INCLUDING USD2014
Series: Proceedings of ISMA
Pagina's: 3369-3382
Aantal pagina's: 14
Jaar van publicatie:2014
Trefwoorden:Operational Modal Analysis, Transmissibility functions, Time-varying, pTOMA, TOMA
  • ORCID: /0000-0001-7041-9948/work/84645885
  • ORCID: /0000-0003-4068-8818/work/83012943
  • WoS Id: 000352201004013
  • Scopus Id: 84913580216