The aim of this paper is to investigate the dynamic behaviour of a steel curved cable-stayed footbridge using an advanced MEMS-based Structural Health Monitoring system. Experimental campaigns were carried out in July and December to characterize the dynamic behaviour of the footbridge subjected to ambient vibrations and human-induced loading actions and to evaluate the effects of temperature shifts on structural modal properties. The monitoring system is composed of a controller and storage unit and several intelligent bus-connected sensing units that can record both the accelerations along two orthogonal axes and the temperature. The main features of this system are the transmission of data in digital form and its high signal-to-noise ratio in the low and medium-low frequency range. The structural dynamic properties are identified through the classic Enhanced Frequency Domain Decomposition (EFDD) method that is based on the diagonalization of the spectral density matrix. A preliminary FE model of the footbridge is built and the numerical results are compared with the experimental ones.
Bassoli, E., Gambarelli, P., Simonini, L., Vincenzi, L., Savoia, M. (2015). Dynamic monitoring of the Pasternak footbridge using MEMS-based sensing system.
Dynamic monitoring of the Pasternak footbridge using MEMS-based sensing system
GAMBARELLI, PAOLA;VINCENZI, LORIS;SAVOIA, MARCO
2015
Abstract
The aim of this paper is to investigate the dynamic behaviour of a steel curved cable-stayed footbridge using an advanced MEMS-based Structural Health Monitoring system. Experimental campaigns were carried out in July and December to characterize the dynamic behaviour of the footbridge subjected to ambient vibrations and human-induced loading actions and to evaluate the effects of temperature shifts on structural modal properties. The monitoring system is composed of a controller and storage unit and several intelligent bus-connected sensing units that can record both the accelerations along two orthogonal axes and the temperature. The main features of this system are the transmission of data in digital form and its high signal-to-noise ratio in the low and medium-low frequency range. The structural dynamic properties are identified through the classic Enhanced Frequency Domain Decomposition (EFDD) method that is based on the diagonalization of the spectral density matrix. A preliminary FE model of the footbridge is built and the numerical results are compared with the experimental ones.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.