Determining the trend of geometrical changes of a hydrotechnical object based on data in the form of LiDAR point clouds
Monitoring the technical condition of hydrotechnical facilities is crucial for ensuring their safe usage. This process typically involves tracking environmental variables (e.g., concrete damming levels, temperatures, piezometer readings) as well as geometric and physical variables (deformation, crac...
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| Format: | Article |
| Language: | English |
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Polish Academy of Sciences
2024-03-01
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| Series: | Archives of Civil Engineering |
| Subjects: | |
| Online Access: | https://journals.pan.pl/Content/130779/ACE_2024_01_17.pdf |
| _version_ | 1797234847754747904 |
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| author | Maria Kowalska Janina Zaczek-Peplinska Łukasz Piasta |
| author_facet | Maria Kowalska Janina Zaczek-Peplinska Łukasz Piasta |
| author_sort | Maria Kowalska |
| collection | DOAJ |
| description | Monitoring the technical condition of hydrotechnical facilities is crucial for ensuring their safe usage. This process typically involves tracking environmental variables (e.g., concrete damming levels, temperatures, piezometer readings) as well as geometric and physical variables (deformation, cracking, filtration, pore pressure, etc.), whose long-term trends provide valuable information for facility managers. Research on the methods of analyzing geodetic monitoring data (manual and automatic) and sensor data is vital for assessing the technical condition and safety of facilities, particularly when utilizing new measurement technologies. Emerging technologies for obtaining data on the changes in the surface of objects employ laser scanning techniques (such as LiDAR, Light Detection, and Ranging) from various heights: terrestrial, unmanned aerial vehicles (UAVs, drones), and satellites using sensors that record geospatial and multispectral data. This article introduces an algorithm to determine geometric change trends using terrestrial laser scanning data for both concrete and earth surfaces. In the consecutive steps of the algorithm, normal vectors were utilized to analyze changes, calculate local surface deflection angles, and determine object alterations. These normal vectors were derived by fitting local planes to the point cloud using the least squares method. In most applications, surface strain and deformation analyses based on laser scanning point clouds primarily involve direct comparisons using the Cloud to Cloud (C2C) method, resulting in complex, difficult-to-interpret deformation maps. In contrast, preliminary trend analysis using local normal vectors allows for rapid threat detection. This approach significantly reduces calculations, with detailed point cloud interpretation commencing only after detecting a change on the object indicated by normal vectors in the form of an increasing deflection trend. Referred to as the cluster algorithm by the authors of this paper, this method can be applied to monitor both concrete and earth objects, with examples of analyses for different object types presented in the article. |
| first_indexed | 2024-04-24T16:38:34Z |
| format | Article |
| id | doaj.art-941582dfd0924ad9a2097580fcb9cdab |
| institution | Directory Open Access Journal |
| issn | 1230-2945 2300-3103 |
| language | English |
| last_indexed | 2024-04-24T16:38:34Z |
| publishDate | 2024-03-01 |
| publisher | Polish Academy of Sciences |
| record_format | Article |
| series | Archives of Civil Engineering |
| spelling | doaj.art-941582dfd0924ad9a2097580fcb9cdab2024-03-29T12:12:25ZengPolish Academy of SciencesArchives of Civil Engineering1230-29452300-31032024-03-01No 1305323https://doi.org/10.24425/ace.2024.148913Determining the trend of geometrical changes of a hydrotechnical object based on data in the form of LiDAR point cloudsMaria Kowalska0https://orcid.org/0000-0002-4434-7829Janina Zaczek-Peplinska1https://orcid.org/0000-0003-4875-4250Łukasz Piasta2Warsaw University of Technology, Faculty of Geodesy and Cartography, pl. Politechniki 1, 00-661 Warsaw, PolandWarsaw University of Technology, Faculty of Geodesy and Cartography, pl. Politechniki 1, 00-661 Warsaw, PolandWarsaw University of Technology, Faculty of Geodesy and Cartography, pl. Politechniki 1, 00-661 Warsaw, PolandMonitoring the technical condition of hydrotechnical facilities is crucial for ensuring their safe usage. This process typically involves tracking environmental variables (e.g., concrete damming levels, temperatures, piezometer readings) as well as geometric and physical variables (deformation, cracking, filtration, pore pressure, etc.), whose long-term trends provide valuable information for facility managers. Research on the methods of analyzing geodetic monitoring data (manual and automatic) and sensor data is vital for assessing the technical condition and safety of facilities, particularly when utilizing new measurement technologies. Emerging technologies for obtaining data on the changes in the surface of objects employ laser scanning techniques (such as LiDAR, Light Detection, and Ranging) from various heights: terrestrial, unmanned aerial vehicles (UAVs, drones), and satellites using sensors that record geospatial and multispectral data. This article introduces an algorithm to determine geometric change trends using terrestrial laser scanning data for both concrete and earth surfaces. In the consecutive steps of the algorithm, normal vectors were utilized to analyze changes, calculate local surface deflection angles, and determine object alterations. These normal vectors were derived by fitting local planes to the point cloud using the least squares method. In most applications, surface strain and deformation analyses based on laser scanning point clouds primarily involve direct comparisons using the Cloud to Cloud (C2C) method, resulting in complex, difficult-to-interpret deformation maps. In contrast, preliminary trend analysis using local normal vectors allows for rapid threat detection. This approach significantly reduces calculations, with detailed point cloud interpretation commencing only after detecting a change on the object indicated by normal vectors in the form of an increasing deflection trend. Referred to as the cluster algorithm by the authors of this paper, this method can be applied to monitor both concrete and earth objects, with examples of analyses for different object types presented in the article.https://journals.pan.pl/Content/130779/ACE_2024_01_17.pdflidarnormal vectorspoint cloudsterrestrial laser scanningdeformations of hydrotechnical structurescluster algorithm |
| spellingShingle | Maria Kowalska Janina Zaczek-Peplinska Łukasz Piasta Determining the trend of geometrical changes of a hydrotechnical object based on data in the form of LiDAR point clouds Archives of Civil Engineering lidar normal vectors point clouds terrestrial laser scanning deformations of hydrotechnical structures cluster algorithm |
| title | Determining the trend of geometrical changes of a hydrotechnical object based on data in the form of LiDAR point clouds |
| title_full | Determining the trend of geometrical changes of a hydrotechnical object based on data in the form of LiDAR point clouds |
| title_fullStr | Determining the trend of geometrical changes of a hydrotechnical object based on data in the form of LiDAR point clouds |
| title_full_unstemmed | Determining the trend of geometrical changes of a hydrotechnical object based on data in the form of LiDAR point clouds |
| title_short | Determining the trend of geometrical changes of a hydrotechnical object based on data in the form of LiDAR point clouds |
| title_sort | determining the trend of geometrical changes of a hydrotechnical object based on data in the form of lidar point clouds |
| topic | lidar normal vectors point clouds terrestrial laser scanning deformations of hydrotechnical structures cluster algorithm |
| url | https://journals.pan.pl/Content/130779/ACE_2024_01_17.pdf |
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