Borja Conde

Automatic Detection and Segmentation of Columns in As-Built Buildings from Point Clouds

Over the past few years, there has been an increasing need for tools that automate the processing of as-built 3D laser scanner data. Given that a fast and active dimensional analysis of constructive components is essential for construction monitoring, this paper is particularly focused on the detection and segmentation of columns in building interiors from incomplete point clouds acquired with a Terrestrial Laser Scanner. The methodology addresses two types of columns: round cross-section and rectangular cross-section. Considering columns as vertical elements, the global strategy for segmentation involves the rasterization of a point cloud onto the XY plane and the implementation of a model-driven approach based on the Hough Transform. The methodology is tested in two real case studies, and experiments are carried out under different levels of data completeness. The results show the robustness of the methodology to the presence of clutter and partial occlusion, typical in building indoors, even though false positives can be obtained if other elements with the same shape and size as columns are present in the raster.

Geometrical Issues on the Structural Analysis of Transmission Electricity Towers Thanks to Laser Scanning Technology and Finite Element Method

This paper presents a multidisciplinary approach to reverse engineering and structural analysis of electricity transmission tower structures through the combination of laser scanning systems and finite element methodology. The use of laser scanning technology allows the development of both drawings and highly accurate three-dimensional geometric models that reliably reproduce geometric reality of towers structures, detecting imperfections, and particularities of their assembly. Due to this, it is possible to analyze and quantify the effect of these imperfections in their structural behavior, taking into account the actual geometry obtained, different structural models, and load hypotheses proposed. The method has been applied in three different types of metal electricity transmission towers with high voltage lines located in Guadalajara (Spain) in order to analyze its structural viability to accommodate future increased loads with respect that which are currently subjected.

Parameterization of Structural Faults in Large Historical Constructions for Further Structural Modelling Thanks to Laser Scanning Technology and Computer Vision Algorithms

Laser scanning technology has evolved significantly in the last decade, particularly, in those applications in terrestrial environments dealing with the documentation and inspection of civil engineering and architectural constructions. Even though there exist mature procedures to convert the so-called LiDAR point clouds in CAD models or even FEM models, the current trends in the technology are related to the automation of these operations. The development of robust automatic procedures for data segmentation and interpretation it is a key aspect so that the technology can definitely be accepted as a basic, accurate, and robust tool for reverse engineering of existing constructions. This paper presents the application of laser scanning technology to the structural evaluation of the Medieval Wall of Guimaraes (Portugal). This laser scanning survey was conducted with the aim of having an accurate and detailed geometrical model of the large masonry construction that includes the existing deformations and structural faults. The parameterization of structural damages was possible thanks to the highly detailed point cloud collected, and its processing using computer vision algorithms. The geometric models obtained could be used for further structural analysis of the entire wall.

Parameter identification of a Round-Robin test box model using a deterministic and probabilistic methodology

In this paper, two different methodologies are applied to the parameter estimation problem of a computational model of a Round-Robin test box. The numerical model is developed using TRNSYS. A global sensitivity analysis is carried out to determine the most important parameters that should be considered in the subsequent calibration procedure. Using the Bayesian (probabilistic) approach, the posterior distribution of the unknown input parameters is estimated via simulation techniques. Using the deterministic approach, executed in GenOpt, the calibration is performed by the minimization of an objective function that measures the differences between model predictions and real measured data. Parameter estimation results obtained with both methodologies are then compared and discussed. A reduction of the Coefficient of Variation of the Root Mean Square Error (CV (RMSE)) after calibration over 40% with both methods has been obtained, being the CV (RMSE) for calibration and validation periods on average 3.21% an...