Potential damage detection of bridge deck based on single phase point cloud

Xianglei Liu; Tianke Su

doi:10.1117/12.2625664

9 December 2021 Potential damage detection of bridge deck based on single phase point cloud

Xianglei Liu, Tianke Su

Proceedings Volume 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021); 121290X (2021) https://doi.org/10.1117/12.2625664
Event: 2021 International Conference on Environmental Remote Sensing and Big Data, 2021, Wuhan, China

Abstract

In view of the city small and medium-sized bridge potential damage area detection efficiency is not high shortcomings, using the ground three-dimensional Laser Scanner (TLS) point cloud data, determine the potential damage area of small and medium-sized span bridge, and accurately detect the key damage location of small and medium-sized span bridge. In this paper, a set of accurate potential damage detection process is proposed, and the process is applied to the Beisha Bridge in Beijing city for potential damage detection analysis. It is divided into three steps :(1) quantification of bridge deck damage by applying the range-gradient algorithm model; (2) feasibility of detecting potential damage of bridge deck by gaussian curvature of point cloud data is analyzed in detail, and the model is constructed; (3) abnormal areas of bridge deck change are identified by taking the experimental data of beizan bridge as an example. The experimental results show that the proposed Gaussian curvature damage identification method is consistent with the displacements and gradients method, which can be applied to the analysis of potential damage mechanism of Bridges.

Citation Download Citation

Xianglei Liu and Tianke Su "Potential damage detection of bridge deck based on single phase point cloud", Proc. SPIE 12129, International Conference on Environmental Remote Sensing and Big Data (ERSBD 2021), 121290X (9 December 2021); https://doi.org/10.1117/12.2625664

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KEYWORDS

Bridges

Clouds

3D scanning

Damage detection

Laser scanners

3D acquisition

Safety

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