scholarly journals Accurate Virtual Trial Assembly Method of Prefabricated Steel Components Using Terrestrial Laser Scanning

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Yin Zhou ◽  
Daguang Han ◽  
Kaixin Hu ◽  
Guocheng Qin ◽  
Zhongfu Xiang ◽  
...  
Keyword(s):  
Finite Element ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Simulation Method ◽  
Mean Stress ◽  
Registration Accuracy ◽  
Element Analysis ◽  
Registration Method ◽  
Assembly Method

The comprehensive utilization of prefabricated components (PCs) is one of the features of industrial construction. Trial assembly is imperative for PCs used in high-rise buildings and large bridges. Virtual trial assembly (VTA) is a preassembly process for PCs in a virtual environment that can avoid the time-consuming and economic challenges in physical trial assembly. In this study, a general framework for VTA that is performed between a point cloud, a building information model (BIM), and the finite element method is proposed. In obtaining point clouds via terrestrial laser scanning, the registration accuracy of point clouds is the key to building an accurate digital model of PCs. Accordingly, an accurate registration method based on triangular pyramid markers is proposed. This method can enable the general registration accuracy of point clouds to reach the submillimeter scale. Two algorithms for curved members and bolt holes are developed for PCs with bolt assembly to reconstruct a precise BIM that can be used directly in finite element analysis. Furthermore, an efficient simulation method for accurately predicting the elastic deformation and initial stress caused by forced assembly is proposed and verified. The proposed VTA method is verified on a reduced-scale steel pipe arch bridge. Experimental results show that the geometric prediction deviation of VTA is less than 1/1800 of the experimental bridge span, and the mean stress predicted via VTA is 90% of the measured mean stress. In general, this research may help improve the industrialization level of building construction.

scholarly journals Finite element analysis of trees in the wind based on terrestrial laser scanning data

2019 ◽  
Vol 265 ◽  
pp. 137-144 ◽  
Author(s):  
T. Jackson ◽  
A. Shenkin ◽  
A. Wellpott ◽  
K. Calders ◽  
N. Origo ◽  
...  
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Element Analysis

scholarly journals Implementing BIM and Finite Element Analysis in a Structural Integrity Investigation of Curtain Walls

2019 ◽  
Vol 3 (1) ◽  
pp. 27-37 ◽  
Author(s):  
Gouree P. Patil ◽  
Don Chen ◽  
Glenda Mayo ◽  
Jake Smithwick ◽  
Nicole Barclay
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Life Cycle ◽  
Structural Damage ◽  
Laser Scanning ◽  
Structural Integrity ◽  
Point Clouds ◽  
Information Modeling ◽  
Element Analysis ◽  
Curtain Wall

ABSTRACT Evaluating the structural integrity of curtain walls during the life cycle of a building project can assist architects in developing better designs, help contractors establish better installation methods, and allow facility managers make informed maintenance decisions. This paper presents an effort to develop a process which combines three types of technologies: 3D laser scanning, Building Information Modeling (BIM), and Finite Element Analysis (FEA), to evaluate the structural integrity of a curtain wall. In a case study, a 3D laser scanner was used to scan the curtain wall, the resulting set of point clouds was used to create an actual as-built BIM model. This “as-is” BIM model is different than a construction as-built BIM model in that the former model captures existing deformations developed during construction, installation, and maintenance phases. Then further analysis was completed using simulation with FEA using the BIM model to potentially predict any future structural issues. Wind loads on the building façade and their effect on unintentional stresses built into the glass panel were studied. The final results inform of deformities in the curtain wall and show the amount of wind load the structure can support before there is a risk of structural damage. The contribution of this study is that the harmonious three-step technique quickens the entire process of identifying the risks to a building element. An additional use for these common software packages would be beneficial to all the stakeholders involved in the life cycle of the building, especially those concerned with the facilities management and the building life cycle.

scholarly journals An Improvement in the Identification of the Centres of Checkerboard Targets in Point Clouds Using Terrestrial Laser Scanning

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 938 ◽  
Author(s):  
Anna Fryskowska
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Target Identification ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Reference Points ◽  
Global Coordinate System ◽  
Registration Method ◽  
Cloud Parameters ◽  
The Difference

Measurement using terrestrial laser scanning is performed at several stations to measure an entire object. In order to obtain a complete and uniform point cloud, it is necessary to register each and every scan in one local or global coordinate system. One registration method is based on reference points—in this case, checkerboard targets. The aim of this research was to analyse the accuracy of checkerboard target identification and propose an algorithm to improve the accuracy of target centre identification, particularly for low-resolution and low-quality point clouds. The proposed solution is based on the geometric determination of the target centre. This work presents an outline of a new approach, designed by the author, to discuss the influence of the point cloud parameters on the process of checkerboard centre identification and to propose an improvement in target centre identification. The validation of the proposed solutions reveals that the difference between the typical automatic target identification and the proposed method amounts to a maximum of 6 mm for scans of different qualities. The proposed method may serve as an alternative to, or supplement for, checkerboard identification, particularly when the quality of these scans is not sufficient for automatic algorithms.

Robust Markerless Registration of Point Clouds for Terrestrial Laser Scanning-Based Measurement of Bulk Grains Stockpiled in Storehouses

2021 ◽  
Vol 37 (6) ◽  
pp. 1073-1087
Author(s):  
Xingbo Hu ◽  
Leidong Yang ◽  
Fangming Wu ◽  
Yinghong Tian
Keyword(s):  
Computational Efficiency ◽  
Point Cloud ◽  
Laser Scanning ◽  
Ordered Set ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
List Type ◽  
Registration Method ◽  
Geometrical Features ◽  
Symmetric Structures

HighlightsFully automated registration free from artificial markers for multi-scan point clouds aimed for TLS-based measurement of bulk grains in large storehouses.The geometric structure of the large grain storehouse is explored to derive geometrical features as the structurally semantic information for scene understanding.The geometrical features are modeled as a small ordered set and correspondences are established by performing trials for all possible matching pairs of two sets extracted from two different scans.Significant improvements have been achieved in registration accuracy, computational efficiency, and robustness against scenes with symmetric structures as well as the immunity to noises and varying point density.Abstract. Point clouds collected by terrestrial laser scanning (TLS) in the application of bulk grain measurement and quantification contain a vast amount of data, relatively low-textured surfaces and highly symmetric structures. All of these challenges make it a difficult task to automatically register multiple scans from different viewpoints needed to fully cover a large-scale scene. To address the challenges, this article presents a robust automatic marker-free registration method dedicated for multi-scan TLS point cloud data captured in large grain storehouses. The framework of the dedicated method follows the common procedure to split the entire registration into coarse alignment and fine registration, and uses the iterative closest point (ICP) algorithm for the latter. The main contribution of the proposed dedicated method is an efficient way to find a global coarse alignment that is robust across individual scans in a TLS-based bulk grain measurement project. To tackle the correspondence problem, which is at the core of a registration task, the geometric information inherent in grain storehouses is explored in the stage of global coarse alignment. The derived semantic feature points are modeled as a small ordered set and reliable correspondences are established by performing trials for all possible matching pairs of two sets extracted from two different scans. Experimental results show the dedicated method outperforms the existing generic markless registration approaches in terms of accuracy, robustness and computational efficiency. With robustness, efficiency and accuracy, the proposed markless point cloud registration method dedicated for bulk grain measurement can cover a gap between the TLS technology and various granary field applications. Especially, its applicability to the dominant storage structure in Chinese huge grain reserve system implies remarkable efficiency improvements and will facilitate the application of TLS-based measurement in the national grain inventory of China. Keywords: Bulk grain measurement, Feature extraction, Grain storehouse, Markerless registration, Point cloud, Terrestrial laser scanning.

scholarly journals Some Remarks on Registration Techniques of Point Clouds Obtained from Terrestrial Laser Scanning

2021 ◽  
Vol 906 (1) ◽  
pp. 012078
Author(s):  
Zbigniew Muszyński ◽  
Paulina Kujawa
Keyword(s):  
Reference Frame ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Engineering Structures ◽  
Registration Method ◽  
Railway Line ◽  
Local Reference ◽  
High Level

Abstract Terrestrial laser scanning (TLS) is a measurement technique used for many geodetic applications (such as determination of displacement and deformation of building objects or monitoring of engineering structures) as well as for non-geodetic applications (for example in forestry, archeology or geotechnics). Despite the high level of automation, the measurement with a laser scanner and the processing of the results consist of many stages and depend on many factors. The most important factors are: the features of measurement object (size, material, availability), required accuracy, speed of scanning, required scan density, type of reference frame, registration method, planned visualization, and 3D modelling method. In this article, the authors focused on the type of registration technique of point clouds obtained from TLS. The most popular strategies of registration were discussed. The practical application of the selected technique was presented on the example of measurement of the railway gauge of the viaduct. Due to the characteristic object (narrow and long railway line) and considering the local reference frame of point clouds as well as the need of minimization of the measurement time, the hybrid registration method in the nested variant was selected.

scholarly journals Linear-Based Incremental Co-Registration of MLS and Photogrammetric Point Clouds

2021 ◽  
Vol 13 (11) ◽  
pp. 2195
Author(s):  
Shiming Li ◽  
Xuming Ge ◽  
Shengfu Li ◽  
Bo Xu ◽  
Zhendong Wang
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Registration Method ◽  
Cloud Data ◽  
Linear Feature ◽  
Data Registration ◽  
Source Point ◽  
Urban Remote Sensing ◽  
Single Data

Today, mobile laser scanning and oblique photogrammetry are two standard urban remote sensing acquisition methods, and the cross-source point-cloud data obtained using these methods have significant differences and complementarity. Accurate co-registration can make up for the limitations of a single data source, but many existing registration methods face critical challenges. Therefore, in this paper, we propose a systematic incremental registration method that can successfully register MLS and photogrammetric point clouds in the presence of a large number of missing data, large variations in point density, and scale differences. The robustness of this method is due to its elimination of noise in the extracted linear features and its 2D incremental registration strategy. There are three main contributions of our work: (1) the development of an end-to-end automatic cross-source point-cloud registration method; (2) a way to effectively extract the linear feature and restore the scale; and (3) an incremental registration strategy that simplifies the complex registration process. The experimental results show that this method can successfully achieve cross-source data registration, while other methods have difficulty obtaining satisfactory registration results efficiently. Moreover, this method can be extended to more point-cloud sources.

scholarly journals Terrestrial Laser Scanning for Vegetation Analyses with a Special Focus on Savannas

2021 ◽  
Vol 13 (3) ◽  
pp. 507
Author(s):  
Tasiyiwa Priscilla Muumbe ◽  
Jussi Baade ◽  
Jenia Singh ◽  
Christiane Schmullius ◽  
Christian Thau
Keyword(s):  
Remote Sensing ◽  
Vegetation Structure ◽  
Laser Scanning ◽  
Spatial Scales ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Parameter Extraction ◽  
Airborne Lidar ◽  
Special Focus ◽  
Vegetation Parameter

Savannas are heterogeneous ecosystems, composed of varied spatial combinations and proportions of woody and herbaceous vegetation. Most field-based inventory and remote sensing methods fail to account for the lower stratum vegetation (i.e., shrubs and grasses), and are thus underrepresenting the carbon storage potential of savanna ecosystems. For detailed analyses at the local scale, Terrestrial Laser Scanning (TLS) has proven to be a promising remote sensing technology over the past decade. Accordingly, several review articles already exist on the use of TLS for characterizing 3D vegetation structure. However, a gap exists on the spatial concentrations of TLS studies according to biome for accurate vegetation structure estimation. A comprehensive review was conducted through a meta-analysis of 113 relevant research articles using 18 attributes. The review covered a range of aspects, including the global distribution of TLS studies, parameters retrieved from TLS point clouds and retrieval methods. The review also examined the relationship between the TLS retrieval method and the overall accuracy in parameter extraction. To date, TLS has mainly been used to characterize vegetation in temperate, boreal/taiga and tropical forests, with only little emphasis on savannas. TLS studies in the savanna focused on the extraction of very few vegetation parameters (e.g., DBH and height) and did not consider the shrub contribution to the overall Above Ground Biomass (AGB). Future work should therefore focus on developing new and adjusting existing algorithms for vegetation parameter extraction in the savanna biome, improving predictive AGB models through 3D reconstructions of savanna trees and shrubs as well as quantifying AGB change through the application of multi-temporal TLS. The integration of data from various sources and platforms e.g., TLS with airborne LiDAR is recommended for improved vegetation parameter extraction (including AGB) at larger spatial scales. The review highlights the huge potential of TLS for accurate savanna vegetation extraction by discussing TLS opportunities, challenges and potential future research in the savanna biome.

scholarly journals Revealing Changes in the Stem Form and Volume Allocation in Diverse Boreal Forests Using Two-Date Terrestrial Laser Scanning

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 835
Author(s):  
Ville Luoma ◽  
Tuomas Yrttimaa ◽  
Ville Kankare ◽  
Ninni Saarinen ◽  
Jiri Pyörälä ◽  
...  
Keyword(s):  
Tree Growth ◽  
Point Cloud ◽  
Laser Scanning ◽  
Terrestrial Laser Scanning ◽  
Point Clouds ◽  
Stem Volume ◽  
Accurate Information ◽  
Stem Form ◽  
Monitoring Period ◽  
Significant Difference

Tree growth is a multidimensional process that is affected by several factors. There is a continuous demand for improved information on tree growth and the ecological traits controlling it. This study aims at providing new approaches to improve ecological understanding of tree growth by the means of terrestrial laser scanning (TLS). Changes in tree stem form and stem volume allocation were investigated during a five-year monitoring period. In total, a selection of attributes from 736 trees from 37 sample plots representing different forest structures were extracted from taper curves derived from two-date TLS point clouds. The results of this study showed the capability of point cloud-based methods in detecting changes in the stem form and volume allocation. In addition, the results showed a significant difference between different forest structures in how relative stem volume and logwood volume increased during the monitoring period. Along with contributing to providing more accurate information for monitoring purposes in general, the findings of this study showed the ability and many possibilities of point cloud-based method to characterize changes in living organisms in particular, which further promote the feasibility of using point clouds as an observation method also in ecological studies.

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