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Automated Quality Inspection of Formwork Systems Using 3D Point Cloud Data
Ensuring that formwork systems are properly installed is essential for construction safety and quality. They have to comply with specific design requirements and meet strict tolerances regarding the installation of the different members. The current method of quality control during installation mostly relies on manual measuring tools and inspections heavily reliant on the human factor, which could lead to inconsistencies and inaccurate results. This study proposes a way to automate the inspection process and presents a framework within which to measure the spacing of the different members of the formwork system using 3D point cloud data. 3D point cloud data are preprocessed, processed, and analyzed with various techniques, including filtering, downsampling, transforming, fitting, and clustering. The novelty is not only in the integration of the different techniques used but also in the detection and measurement of key members in the formwork system with limited human intervention. The proposed framework was tested on a real construction site. Five cases were investigated to compare the proposed approach to the manual and traditional one. The results indicate that this approach is a promising solution and could potentially be an effective alternative to manual inspections for quality control during the installation of formwork systems.
Automated Quality Inspection of Formwork Systems Using 3D Point Cloud Data
Ensuring that formwork systems are properly installed is essential for construction safety and quality. They have to comply with specific design requirements and meet strict tolerances regarding the installation of the different members. The current method of quality control during installation mostly relies on manual measuring tools and inspections heavily reliant on the human factor, which could lead to inconsistencies and inaccurate results. This study proposes a way to automate the inspection process and presents a framework within which to measure the spacing of the different members of the formwork system using 3D point cloud data. 3D point cloud data are preprocessed, processed, and analyzed with various techniques, including filtering, downsampling, transforming, fitting, and clustering. The novelty is not only in the integration of the different techniques used but also in the detection and measurement of key members in the formwork system with limited human intervention. The proposed framework was tested on a real construction site. Five cases were investigated to compare the proposed approach to the manual and traditional one. The results indicate that this approach is a promising solution and could potentially be an effective alternative to manual inspections for quality control during the installation of formwork systems.
Automated Quality Inspection of Formwork Systems Using 3D Point Cloud Data
Keyi Wu (Autor:in) / Samuel A. Prieto (Autor:in) / Eyob Mengiste (Autor:in) / Borja García de Soto (Autor:in)
2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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