Large-scale deformation monitoring using mobile laser scanning and tailored point cloud processing

Auteurs

• Slaven Kalenjuk

Paramètres

• Géologie et Minéralogie

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This dissertation introduces a novel method for deformation analysis of retaining structures using mobile laser scanning (MLS). By employing a commercial MLS system mounted on a vehicle, infrastructure can be captured without disrupting traffic flow. Tailored algorithms enable automated, efficient, and repeatable analysis of MLS data. The approach aims to detect damage among numerous structures on a large scale. The point cloud processing algorithms are designed to accommodate various structural types and surface properties. They describe complex deformation patterns through the rigid-body motion of numerous small parts, which may represent meaningful objects or point subsets formed by spatial clustering. These methods generate groups of thousands of points, facilitating precise estimates of tilt and displacements. The thesis also presents innovative techniques to eliminate systematic discrepancies between two MLS point clouds, allowing for accurate registration over stable reference surfaces and determining the uncertainty of MLS point clouds. These aspects are vital for effective deformation monitoring. Additionally, a practical guideline for implementing the proposed methodology is provided, catering to the needs of infrastructure operators and service providers. This aims to prevent monopolies while ensuring the quality of deformation analysis, regardless of the service provider involved.

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• Année de publication: 2023