Analysis Image-Based Automated 3D Crack Detection for Post-disaster Bridge Assessment in Flyover Mall Boemi Kedaton

Abstract

Recovery efforts following a disaster can be slow and painstaking work, and potentially put responders in harm's way. A system which helps identify defects in critical building elements (e.g., concrete columns) before responders must enter a structure can save lives. In this paper we propose a system, centered around an image based three-dimensional (3D) reconstruction method and a new 3D crack detection algorithm. The image-based method is capable of detecting and analyzing surface damages in 3D. We also demonstrate how the robotics can be used to gather the images from which the reconstruction is created, further reducing the risk to responders. In this regard, image-based 3D reconstructions represent a convenient method of creating 3D models because most robotic platforms can carry a lightweight camera payload. Additionally, the proposed 3D crack detection algorithm also provides the advantage of being able to operate on 3D mesh models regardless of their data collection source. Our experimental results show that 3D crack detection algorithm performs well constructions, successfully identifying cracks, reconstructing 3D profiles, and measuring geometrical characteristics on damaged elements and not finding any cracks on intact ones.

Behavior of a steel structure railway bridge under dynamic loadings

“…measurement data obtained from the bridge structure is necessary for structural assessment and maintenance procedure [30]. The results of this study confirm that the steel railway bridge has sufficient capability to support heavier dynamic moving loads.…”