Automation Strategies for the Photogrammetric Reconstruction of Pipelines
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
A responsible use of energy resources is currently more important than ever. For the effective insulation of industrial plants, a three-camera measurement system was, therefore, developed. With this system, the as-built geometry of pipelines can be captured, which is the basis for the production of a precisely fitting and effective insulation. In addition, the digital twin can also be used for Building Information Modelling, e.g. for planning purposes or maintenance work. In contrast to the classical approach of processing the images by calculating a point cloud, the reconstruction is performed directly on the basis of the object edges in the image. For the optimisation of the, initially purely geometrically calculated components, an adjustment approach is used. In addition to the image information, this approach takes into account standardised parameters (such as the diameter) as well as the positional relationships between the components and thus eliminates discontinuities at the transitions. Furthermore, different automation approaches were developed to facilitate the evaluation of the images and the manual object recognition in the images for the user. For straight pipes, the selection of the object edges in one image is sufficient in most cases to calculate the 3D cylinder. Based on the normalised diameter, the missing depth can be derived approximately. Elbows can be localised on the basis of coplanar neighbouring elements. The other elbow parameters can be determined by matching the back projection with the image edges. The same applies to flanges. For merging multiple viewpoints, a transformation approach is used which works with homologous components instead of control points and minimises the orthogonal distances between the component axes in the datasets.
Details
Original language | English |
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Pages (from-to) | 313-334 |
Number of pages | 22 |
Journal | PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science |
Volume | 91 |
Issue number | 4 |
Publication status | Published - Aug 2023 |
Peer-reviewed | Yes |
Keywords
ASJC Scopus subject areas
Keywords
- BIM, Computer vision, Cylinder detection, Industrial plant, Pipes, Transformation