Abstract
Parametric identification of bridges using instrumented vehicles can be challenging, mainly due to the reduced length of the time series associated with the bridge span under test. This research discusses the practicability of a time-domain identification method based on the use of an instrumented vehicle. The highest cross-correlation between the bridge response from an elementary analytical model and the experimental one, acquired by a moving force-balance accelerometer, yields the unknown model parameter. The effect of vehicle-bridge interaction is removed by proper filtering of the signals. Specifically, the authors estimate the elastic moduli of seven prestressed concrete bridges and compare a subset of the results to the outcomes of static load tests carried out on the same bridges. There is a good correlation between the elastic moduli from the instrumented vehicle and those from static load tests: the method grasps the approximate value of the elastic modulus of concrete. Still, the data do not return an excellent match due to the bias in the estimation of the deflection shape—the paper remarks on the issues faced during the experimental tests and proposes possible enhancements of these procedures.
Highlights
Static load tests are the chief method to assess the bending stiffness of bridges and monitor their integrity
The managing bodies may handle a vast number of infrastructures, and they cannot carry out periodic static load tests on all of them. erefore, the current methods followed for prioritizing the interventions are derived from routine visual inspections by expert bodies
Is paper extends the procedure proposed by Aloisio et al [33] to drive-by inspections with force-balance accelerometers (FBAs). e originality of this research lies in the elastic modulus identification based on the correlation between the experimental displacement response, obtained by integrating the signal acquired by FBAs, and the simulated one, derived from an elementary analytical model. e authors chose force-balance sensors because they have a low noise level and very high dynamics, and they can measure very low-frequency signals up to the DC component
Summary
Universitadegli Studi dell’Aquila, via Giovanni Gronchi 18, 67100 L’Aquila, Italy. Received 31 May 2021; Revised 23 June 2021; Accepted 28 July 2021; Published 5 August 2021. Parametric identification of bridges using instrumented vehicles can be challenging, mainly due to the reduced length of the time series associated with the bridge span under test. Is research discusses the practicability of a time-domain identification method based on the use of an instrumented vehicle. E highest cross-correlation between the bridge response from an elementary analytical model and the experimental one, acquired by a moving force-balance accelerometer, yields the unknown model parameter. The authors estimate the elastic moduli of seven prestressed concrete bridges and compare a subset of the results to the outcomes of static load tests carried out on the same bridges. Ere is a good correlation between the elastic moduli from the instrumented vehicle and those from static load tests: the method grasps the approximate value of the elastic modulus of concrete. The data do not return an excellent match due to the bias in the estimation of the deflection shape—the paper remarks on the issues faced during the experimental tests and proposes possible enhancements of these procedures
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