Deflection condition monitoring of a steel bridge via remote sensing techniques

Abstract

The monitoring task of bridges are obtaining consideration due to their importance to the community. And to perform the overall structural health monitoring task various type of sensors have been adopted over the last few decades. Herein, a simple steel bridge has been considered to perform tests using remote sensing techniques, like video streaming via camera, high dynamic reflector-less distance measurements, and digitalized total station measurements. The bridge has been tested in a resting position (e.g. preventing the self-weight sagging using clamps) and in a released condition after removing the clamps. Both the static and dynamic loads are applied to the bridge and the following loading scenarios are tested: (i) no-load case, (ii) manual impulse, (iii) putting extra masses on the bridge, and (iv) under various dynamic loads. The tests data have been post-processed and analysed by employing MATLAB. The observed displacement results of aforementioned scenarios are evaluated and presented herein. In a nutshell, the obtained results show the changes of the displacements throughout the bridge for the aforementioned loading conditions. The test results of different sensors scenario have been investigated and the results are inter-compared. It can be summarized that remote sensing techniques are effective as the pre-warning can be deliver and identified before any change (e.g. man-made or natural) takes place. This study not only assist to visualize the variation of the deformation contour but also the video streaming of whole structure, as a result, the overall condition monitoring task becomes straightforward.