Damage Detection of Steel Structures

Overview

Steel materials are widely used in the construction industry. Steel structures are subjected to environmental impacts, leading to different types of damage such as cracks, large deformation due to severe loading, or corrosion. In this project, we proposed a 3D vision and point cloud-based framework for damage quantification of steel plate structures in 3D space. This research project aims to utilize state-of-the-art deep learning, computer vision, and point cloud techniques to detect and quantify structural damage of critical steel structures.

Damage detection flowchart

References

[1]. Pan, X., Yang, T. Y. (2023). 3D vision-based out-of-plane displacement quantification for steel plate structures using structure from motion, deep learning and point cloud processing. Computer-aided Civil and Infrastructure Engineering. 38(5), 547-561.

[2]. Pan, X., Vaze, S., Xiao, Y., Tavasoli, S., Yang T.Y. “Structural damage detection of steel corrugated panels using computer vision and deep learning.” Canadian Society for Civil Engineering (CSCE) conference, 2022, Whistler, British Columbia, Canada.