Digital models are essential to quantifying the behavior of structural systems. In many cases, the creation of these models involves manual measurements taken in the field, followed by a manual creation of this model using these measurements. Both of these steps are time consuming and prohibitively expensive, leading to a lack of utilization of accurate models. We propose a framework built on the processing of 3D laser scanning data to partially automate the creation of these models. We focus on steel structures, as they represent a gap in current research into this field. Previous research has focused on segmentation of the point cloud data in order to extract relevant geometries. These approaches cannot easily be extended to steel structures, so we propose a novel method of processing this data with the goal of creating a full finite element model from the information extracted. Our approach sidesteps the need for segmentation by directly extracting the centerlines of structural elements. We begin by taking "slices" of the point cloud in the three principal directions. Each of these slices is flattened into an image, which allows us to take advantage of powerful image processing techniques. Within these images we use 2d convolution as a template match to isolate structural cross sections. This gives us the centroids of cross sections in the image space, which we can map back to the point cloud space as points along the centerline of the element. By fitting lines in 3d space to these points, we can determine the equations for the centerline of each element. This information could be easily passed into a finite element modeling software where the cross sections are manually defined for each line element. / Modern buildings require a digital counterpart to the physical structure for accurate analysis. Historically, these digital counterparts would be created by hand using the measurements that the building was intended to be built to. Often this is not accurate enough and the as-built system must be measured on site to capture deviations from the original plans. In these cases, a large amount of time must be invested to send personnel out into the field and take large amounts of measurements of the structure. Additionally, these "hand measurements" are prone to user error. We propose a novel method of gathering these field measurements quickly and accurately by using a technique called "laser scanning". These laser scans essentially take a 3D snapshot of the site, which contains all the geometric information of visible elements. While it is difficult to locate items such as steel beams in the 3D data, the cross sections of these structural elements are easily defined in 2D. Our method involves taking 2D slices of this 3D scan which allows us to locate the cross sections of the structural members by searching for template cross-sectional shapes. Once the cross sections have been isolated, their centers can be mapped back from the 2D slice to the 3D space as points along the centerlines of the structural elements. These centerlines represent one of the most time consuming requirements to building digital models of modern buildings, so this method could drastically reduce the total modeling time required by automating this particular step.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/111343 |
| Date | 28 January 2021 |
| Creators | Smith, Alan Glynn |
| Contributors | Civil Engineering |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Page generated in 0.002 seconds