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M. Pöchtrager, G. Styhler-Aydin, M. Döring-Williams, N. Pfeifer:
"Digital Reconstruction of Historic Roof Structures: Developing a Workflow for a Highly Automated Analysis";
Virtual Archaeology Review (VAR), 9 (2018), 19; 13 pages.

Planning on adaptive reuse, maintenance and restoration of historic timber structures requires extensive architectural and structural analysis of the actual condition. Current methods for a modelling of roof constructions consist of several manual steps including the time-consuming dimensional modelling. The continuous development of terrestrial laser scanners increases the accuracy, comfort and speed of the surveying work in roof constructions. Resulting point clouds enable detailed visualisation of the constructions represented by single points or polygonal meshes, but in fact do not contain information about the structural system and the beam elements. The developed workflow contains several processing steps on the point cloud dataset. The most important among them are the normal vector computation, the segmentation of points to extract planar faces, a classification of planar segments to detect the beam side faces and finally the parametric modelling of the beams on the basis of classified segments. This enables a highly automated transition from raw point cloud data to a geometric model containing beams of the structural system. The geometric model, as well as additional information about the structural properties of involved wooden beams and their joints, is necessary input for a further structural modelling of timber constructions. The results of the workflow confirm that the proposed methods work well for beams with rectangular cross-section and minor deformations. Scan shadows and occlusion of beams by additional installations or interlocking beams decreases the modelling performance, but in general a high level of accuracy and completeness is achieved at a high degree of automation.

historical timber structures; LiDAR; point clouds; digital reconstruction; beam frame

http://dx.doi.org/10.4995/var.2018.8855