Titolo | Displacement based approach for a robust operational modal analysis |
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Tipo di pubblicazione | Presentazione a Congresso |
Anno di Pubblicazione | 2011 |
Autori | De Canio, Gerardo, Andersen P., Roselli Ivan, Mongelli M., and Esposito E. |
Conference Name | Conference Proceedings of the Society for Experimental Mechanics Series |
Conference Location | Jacksonville, FL |
ISBN Number | 9781441995063 |
Parole chiave | Absolute displacement, Analysis tools, CAD drawings, Computer aided design, Data processing, Data-driven, Design and calculation, Dynamic displacements, Dynamic mechanical analysis, Dynamic tests, Experimental data, Fast test, FE model, High resolution, Induced vibrations, Modal analysis, Modal parameters, Monitoring techniques, Movement detection, Numerical and experimental study, Operational modal analysis, real time, Robust estimation, Seismic design, Shaking table experiment, Stochastic subspace identification, Structural dynamics, Testing, Three dimensional, Time domain, Time domain analysis, Time history, Vibration analysis, Vibration data |
Abstract | Robust estimation of the dynamic modal parameters of structures during shaking table experiments is done by means of efficient time domain data-driven Crystal Clear Stochastic Subspace Identification (CC-SSI) of vibration data recorded by a new, innovative, high resolution 3-D optical movement detection and analysis tool tracking the dynamic displacement of several selected points of the structures during the dynamic tests of natural (earthquake) and artificial (mechanical) induced vibrations. The measure of the displacements is a crucial task for the numerical and experimental studies in structural dynamics, especially within the displacement based approach in seismic design and calculations. The innovative monitoring technique measures 3 axial absolute displacements with easy and fast test set-up, high accuracy and the possibility to link the 3D-motion time histories of the tracked markers with CAD drawings of the structure and validate the FE models in real time experimental data assimilation. |
URL | https://www.scopus.com/inward/record.uri?eid=2-s2.0-79958124712&partnerID=40&md5=d12941ad9b19d1799c0eeb327cf998b1 |
Citation Key | DeCanio2011187 |