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http://dx.doi.org/10.18419/opus-14127
Autor(en): | Skalecki, Patric Sesselmann, Maximilian Rechkemmer, Sabrina Britz, Thorsten Großmann, Andreas Garrecht, Harald Sawodny, Oliver |
Titel: | Process evaluation for smart concrete road construction : road surface and thickness evaluation using high-speed LiDAR technology |
Erscheinungsdatum: | 2021 |
Dokumentart: | Zeitschriftenartikel |
Seiten: | 31-47 |
Erschienen in: | Automation 2 (2021), S. 31-47 |
URI: | http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-ds-141465 http://elib.uni-stuttgart.de/handle/11682/14146 http://dx.doi.org/10.18419/opus-14127 |
ISSN: | 2673-4052 |
Zusammenfassung: | The enhancement of new quality criteria in highway construction is a key aspect to improving the construction process and lifetime of road. In particular, mobile laser scanning systems are nowadays able to provide realistic 3D elevation profiles of a road to detect anomalies. In this context, this study utilizes a high-accuracy high-speed mobile mapping vehicle and evaluates a weighted longitudinal profile as an improved measure for evenness analysis. For comparison a classical method with a rolling straight edge was evaluated on the same road section and observed effects are discussed. The second focus is the areal reconstruction of the road thickness. For this purpose, a modern method was developed to spatially synchronize two high-speed laser scans using reference boxes next to the road, to transfer the point clouds into a surface model and to calculate the layer thickness. This procedure was conceptually validated by some pointwise measurements of the layer thickness. With this information, imperfections in the base layer could be detected automatically over a wide area at an early stage and countermeasures might be initiated before constructing the highway. |
Enthalten in den Sammlungen: | 07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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automation-02-00002.pdf | 4,58 MB | Adobe PDF | Öffnen/Anzeigen |
Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons