MULTI-SENSORY DATA FUSION FOR MÉTRO INSPECTION

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The main objective of this research project is to investigate the feasibility of utilizing remote sensingequipment to facilitate the inspection of Métro concrete structures for Société de Transport de Montréal (STM).In order to achieve this objective, multi-sensory data sources will be explored. Specifically, the profiles fromthe ground penetrating radar system are analyzed to obtain the structure interior deterioration. Also, the thermaland color images are processed to detect the structure exterior deterioration. Both interior and exteriordeterioration conditions are projected to the 3D point cloud from laser scanning to produce a three-dimensional(3D) structure condition map with the detailed and accurate deterioration information. This way, the STMengineers could rely on such condition maps to make an appropriate maintenance strategy. The proposedmethod in this research project will be implemented in Matlab and evaluated in the field trials of inspectingMétro concrete structures in the city of Montreal. The research is expected to reduce the time, cost, and effortrequired in the current process of manually inspecting Métro concrete structures. As a result, the Métroengineers could make wise and informed maintenance decisions to keep the Métro network healthy in serviceto the public, before they are structurally deficient or functionally obsolete.