Abstract

This paper presents the use of a moving vehicle to identify the bridge mode shapes and detect possible damage in the presence of bridge surface roughness. The method utilises the contact point responses at the contact between the wheel and bridge surface, which can be obtained from the vehicle responses and has a direct relation with the bridge responses and surface roughness. A double-pass mass-addition technique is proposed to obtain the contact point response difference using a test vehicle installed with sensors. Then the bridge frequencies can be identified from its spectrum, while the mode shapes can be further obtained by signal filtering and Hilbert transform. Simulation results show that the adverse effect of surface roughness on the contact point acceleration difference is largely reduced. The first three frequencies and mode shapes can be extracted with satisfactory accuracy. Multiple damage locations can be identified by performing wavelet transform on the contact point displacement difference and applying coordinate modal assurance criterion to the mode shapes constructed. The factors that may affect the performance of the proposed method are also investigated, including the distribution of added mass, measurement noise, speed of the test vehicle and co-existing traffic. Experimental validation is conducted on a simply supported aluminium channel beam with artificial roughness carrying a moving model vehicle. The results show that the proposed methodology for bridge identification works in the presence of road surface roughness.

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