Abstract
Based on virtual simulations of vehicle–bridge interactions, the possibility of detecting stiffness reduction damages in bridges through vehicle responses was tested in two dimensional (2D) and three dimensional (3D) settings. Short-Time Fourier Transformation (STFT) was used to process vehicles’ acceleration data obtained through the 2D and 3D virtual simulations. The energy band variation of the vehicle acceleration time history was found strongly related to damage parameters. More importantly, the vehicle’s initial entering conditions are critical in obtaining correct vehicle responses through the vehicle bridge interaction models. The offset distance needed before executing the vehicle–bridge interaction (VBI) modeling was obtained through different road profile roughness levels. Through the above breakthroughs in VBI modeling, the presented study provides a new and integrated method for drive-by bridge inspection.
Highlights
Background and Literature ReviewCitation: Yang, M.; Liu, C
After the road roughness was superimposed onto the bridge deck, a test of damage detection was conducted through the 3D vehicle–bridge interaction (VBI) model with embedded damages
Based on the series of 2D and 3D virtual VBI simulations conducted in this study, the following conclusions are derived:
Summary
More bridge frequencies and their mode shape squares can be extracted from the residual responses In another Kong research [12], he used the two-vehicle models to test the residual response method. Much research was conducted recently to look at ways of making the drive-by inspection more practical [13,14,15] Uddin and his collaborators [16,17,18] researched wavelet entropy and the Hilbert transform method of the vehicle acceleration history to improve the bridge frequency extraction accuracy at normal vehicle operational speeds. Smalia and his collaborators [19,20] adopted numerical modeling and Kalman filter method to.
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