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A flexible approach for geometric modelling of point clouds obtained from Terrestrial Laser Scanning (TLS) is by means of B-splines. These functions have gained some popularity in the engineering geodesy as they provide a suitable basis for a spatially continuous and parametric deformation analysis. In the predominant studies on geometric modelling of point clouds by B-splines, uncorrelated and equally weighted measurements are assumed. Trying to overcome this, the elementary errors theory is applied for establishing fully populated covariance matrices of TLS observations that consider correlations in the observed point clouds. In this article, a systematic approach for establishing realistic synthetic variance–covariance matrices (SVCMs) is presented and afterward used to model TLS point clouds by B-splines. Additionally, three criteria are selected to analyze the impact of different SVCMs on the functional and stochastic components of the estimation results. Plausible levels for variances and covariances are obtained using a test specimen of several dm—dimension. It is used to identify the most dominant elementary errors under laboratory conditions. Starting values for the variance level are obtained from a TLS calibration. The impact of SVCMs with different structures and different numeric values are comparatively investigated. Main findings of the paper are that for the analyzed object size and distances, the structure of the covariance matrix does not significantly affect the location of the estimated surface control points, but their precision in terms of the corresponding standard deviations. Regarding the latter, properly setting the main diagonal terms of the SVCM is of superordinate importance compared to setting the off-diagonal ones. The investigation of some individual errors revealed that the influence of their standard deviation on the precision of the estimated parameters is primarily dependent on the scanning distance. When the distance stays the same, one-sided influences on the precision of the estimated control points can be observed with an increase in the standard deviations., Deutsche Forschungsgemeinschaft, Austrian Science Fund

This contribution presents a B-spline-based approach of area-wise deformation analysis applied on elements of a double curved wooden tower. The monitored object is the Urbach Tower with a height of 14 m. Terrestrial laser scans from two epochs acquired under real-world conditions are used for approximating two jointly parametrized B-spline surfaces of the tower’s outer shell. The stochastic model of the observations used within the surface approximation is based on elementary error theory and is defined by a synthetic variance-covariance matrix (SVCM). In addition to previous work on this topic, the object’s dimension is extended from a few dm to a few m and the measurement distance ranges from 20 to 60 m. Moreover, environment specific error sources are addressed in the SVCM, revealing the effect of the object’s dimension as well as of additional elementary errors on the estimated B-spline surfaces and the subsequent deformation analysis. Based on constructed points pairs using a grid of surface parameters, rigid body movements of the object under investigation are estimated while at the same time distorted regions of the wooden tower are detected. All results of the deformation analysis are statistically verified using hypothesis tests based on the elementary error model propagated through the processing algorithms of surface estimation and deformation analysis. The results demonstrate that during the modelling and deformation analysis, the measurement noise is reduced and therefore distorted regions are detectable in a statistically correct way.

[EN] The Cluster of Excellence Integrative Computational Design and Construction for Architecture at the University of Stuttgart brings together various disciplines to jointly develop amongst other things a better understanding of processes in the manufacturing and construction domain. One of the cluster’s aims is to create new solutions for the construction of lightweight fibrous structures using coreless winding of lightweight fiber composite systems. For this purpose, a precise geometry and an understanding of the fibers’ behavior during the production process are of major importance. The fibers’ production process is monitored by repeatedly scanning the fibers during different stages of the process using a terrestrial laser scanner. In order to determine the geometry of the fibers’ axes as well as their cross-sections, two different strategies are used. The first strategy focuses on the segmentation of several straight lines between two intersection points. For the comparison of the individual fabrication steps, the positions of the intersection points are contrasted. For the cross-sectional areas of the fibers, orthogonal planes of intersection are then defined and all points within a predefined area are projected onto this plane. Then the area is calculated using a convex hull. In the second strategy, the fibers‘ main axes are represented by best-fitting B-spline curves. The borders of the cross-sections of interest are also approximated by best-fitting B-spline curves, forming the basis for the final determination of the cross-sectional areas. In this case study two epochs are analyzed with a deformation of the size of around 1cm. For both epochs the cross-sections are calculated in cm steps., The research published in this article is supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2120/1 – 390831618. The authors cordially thank the DFG. A part of the research was realized within a one-month research stay of the second author at the University of Stuttgart within the IntCDC incoming programme.

Accepting the ecological necessity of a drastic reduction of resource consumption and greenhouse gas emissions in the building industry, the Institute for Lightweight Structures and Conceptual Design (ILEK) at the University of Stuttgart is developing graded concrete components with integrated concrete hollow spheres. These components weigh a fraction of usual conventional components while exhibiting the same performance. Throughout the production process of a component, the positions of the hollow spheres and the level of the fresh concrete have to be monitored with high accuracy and in close to real-time, so that the quality and structural performance of the component can be guaranteed. In this contribution, effective solutions of multiple sphere detection and concrete surface modeling based on the technology of terrestrial laser scanning (TLS) during the casting process are proposed and realized by the Institute of Engineering Geodesy (IIGS). A complete monitoring concept is presented to acquire the point cloud data fast and with high-quality. The data processing method for multiple sphere segmentation based on the efficient combination of region growing and random sample consensus (RANSAC) exhibits great performance on computational efficiency and robustness. The feasibility and reliability of the proposed methods are verified and evaluated by an experiment monitoring the production of an exemplary graded concrete component. Some suggestions to improve the monitoring performance and relevant future work are given as well.