In this paper, dynamic properties and results of the identification process on the Manhattan Bridge are described. Accelerations during ambient vibrations have been recorded using an advanced MEMSbased system,whose main features are the transmission of the data in digital formand the possibility of performing some system analyses directly on-board of the sensors, transmitting synthetic data only to the main computer. 28 MEMS accelerometers have been used and 4 different experimental setups adopted. Several modes of the main span are identified, with natural frequencies in the range 0.2-1.0 Hz. A FE model updating procedure is also performed by means of an improved Evolutionary Algorithm. After the updating procedure, numerical modal frequencies and mode shapes match well the experimental data. This work is part of a research that aims at investigating how real-time monitoring systems can be used to detect the occurrence of fatigue phenomena induced by vibrations and distortion modes in existing steel bridges. © 2013 Taylor & Francis Group, London.
Savoia M., Vincenzi L., Bassoli E., Gambarelli P., Betti R., Testa R. (2013). Identification of the Manhattan bridge dynamic properties for fatigue Assessment. George Deodatis, Bruce R. Ellingwood, Dan M. Frangopol.
Identification of the Manhattan bridge dynamic properties for fatigue Assessment
SAVOIA, MARCO;
2013
Abstract
In this paper, dynamic properties and results of the identification process on the Manhattan Bridge are described. Accelerations during ambient vibrations have been recorded using an advanced MEMSbased system,whose main features are the transmission of the data in digital formand the possibility of performing some system analyses directly on-board of the sensors, transmitting synthetic data only to the main computer. 28 MEMS accelerometers have been used and 4 different experimental setups adopted. Several modes of the main span are identified, with natural frequencies in the range 0.2-1.0 Hz. A FE model updating procedure is also performed by means of an improved Evolutionary Algorithm. After the updating procedure, numerical modal frequencies and mode shapes match well the experimental data. This work is part of a research that aims at investigating how real-time monitoring systems can be used to detect the occurrence of fatigue phenomena induced by vibrations and distortion modes in existing steel bridges. © 2013 Taylor & Francis Group, London.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
