DETECTION OF DAMAGES AND ENGINEER'S EVALUATION IN IMAGES OF THE WHOLE BRIDGE PIER

Abstract

To improve the efficiency of bridge inspection, the automatic damage detection from images is expected. In previous study, we used close-up images of damage for learning data of automatic detection, but in actual bridge inspection, the damage detection is carried out for the image in which presence and position of the damage are unknown. In this study, we constructed an automatic damage detection model using deep learning and detected multiple damages on the whole bridge pier image. The detection result of the damage were displayed, layer by layer, on the bridge image. And we interviewed the bridge engineer to determine the damage. As the result, the positional relationship of the damages could be grasped at a glance by displaying the damage detection result on a whole bridge pier image. And switching of layers and on / off of the display of layers were effective for the damage determination.