MODELLING A CELL TOWER USING SFM: AUTOMATED DETECTION OF STRUCTURAL ELEMENTS FROM SKELETON EXTRACTION ON A POINT CLOUD

Abstract

The surveying and management of telecommunication towers poses a series of engineering challenges. Not only they must be regularly inspected for the purpose of checking for issues that require maintenance interventions, but they are often sub-let by their owners to communication companies, requiring a survey of the many (several thousand per company) installed appliances to check that they respect the established contracts. This requires a surveying methodology that is fast and possibly automated. Photogrammetric techniques using UAV-mounted cameras seem to offer a solution that is both suitable and economical. Our research team was asked to evaluate whether, from the information acquired by small drones it was possible to obtain geometric information on the structure, with what degree of accuracy and what level of detail. The workflow of this process is naturally articulated in three steps: the acquisition, the construction of the point cloud, and the extraction of geometries. The case study is a tower carrying antennas owned by several operators and placed in the industrial district of Cagliari. The article examines the problems found in modelling such structures using point clouds derived from the Structure-from-Motion technique, in order to obtain a model of nodes and beams suitable for the reconstruction of the structure’s geometric elements, and possibly for a finite elements analysis or for populating GIS and BIM, either automatically or with minimal user intervention. In order to achieve this, we have used voxelization and skeleton extraction algorithms to obtain a 3D graph of the structure. The analysis of the results was carried out by varying the parameters relating to the voxel size, which defines the resolution, and the density of the points contained inside each voxel.