3D Laser Scanning Research Articles

The Selection of Leveler Parameters Using FEM Simulation.

The aim of this research was to select parameters for the roll pre-leveler to provide sheet metal waviness reduction after unwinding from the coil. Straightening parameters were selected based on the results of numerical simulations with the use of an FEM-based computer program. The material used for research was a hot-rolled sheet metal of grade S235JR + AR with a thickness of 3 mm and width of 1500 mm after unwinding from the coil. A mathematical model was developed to determine straightening roll arrangements in the pre-leveler. It enabled roll arrangement selection and a straightening scheme to be elaborated. The model's innovative feature was conducting straightening numerical simulations for the real sheet metal geometric models obtained as a result of 3D laser scanning, which increased the accuracy of the numerical calculations.

Semi-automatic Identification of Tunnel Discontinuity Based on 3D Laser Scanning

Semi-automatic Identification of Tunnel Discontinuity Based on 3D Laser Scanning

Method for Quantitative Assessment of Olecranon Fossa Using 3D Hand-held Laser Scanner in the Field of Forensic Anthropology

The study is based on a creation of virtual model of olecranon fossa through 3D visualization and its usage as a sex discriminant. The study was focused on an assessment of 135 complete humeri from 47 females and 88 males. The surface of olecranon fossa was captured in a 3D image, using a Hand-held Laser Scanner (FastSCAN). The result was a 3D shape comprising two tetrahedrons with a common apex and a common lateral face. This 3D model was determined by five landmarks: the most superior point of the olecranon fossa, the most lateral point of the olecranon fossa seen on the posterior surface, the most medial point of the olecranon fossa, the point on the inferior edge of the olecranon fossa, directly in the middle, and the deepest point into the fossa. Therefore, the volume of the virtual model was equal to the total of the volumes of these two tetrahedrons. The results were processed with SPSS 17.0 using Discriminant Function Analysis. The percentage of cases classified correctly is 92.5% according to the sex determination. This study demonstrates a 3D method which can be used successfully for sex determination, especially in case of highly fragmented bones that impede traditional anthropometric analyses.

Accelerated Augmented Reality Holographic 4k Video Projections Based on Lidar Point Clouds for Automotive Head‐Up Displays

AbstractIdentifying road obstacles hidden from the driver's field of view can ensure road safety in transportation. Current driver assistance systems such as 2D head‐up displays are limited to the projection area on the windshield of the car. An augmented reality holographic point cloud video projection system is developed to display objects aligned with real‐life objects in size and distance within the driver's field of view. Light Detection and Ranging (LiDAR) point cloud data collected with a 3D laser scanner is transformed into layered 3D replay field objects consisting of 400 k points. GPU‐accelerated computing generated real‐time holograms 16.6 times faster than the CPU processing time. The holographic projections are obtained with a Spatial Light Modulator (SLM) (3840×2160 px) and virtual Fresnel lenses, which enlarged the driver's eye box to 25 mm × 36 mm. Real‐time scanned road obstacles from different perspectives provide the driver a full view of risk factors such as generated depth in 3D mode and the ability to project any scanned object from different angles in 360°. The 3D holographic projection technology allows for maintaining the driver's focus on the road instead of the windshield and enables assistance by projecting road obstacles hidden from the driver's field of view.

Numerical analysis and design of concrete-filled wire arc additively manufactured steel tube under axial compression

Numerical investigation of the mechanical behaviour of concrete-filled wire arc additively manufactured (WAAM) steel tube under axial compression is presented in this paper. Typical structural performances of concrete-filled WAAM steel tube are extensively analyzed based on the experimental results firstly. FE models are established based on 3D models obtained by 3D laser scan technology, whilst the material anisotropy of WAAM steel tube is taken into account. The sensitivity study on the finite element (FE) model parameters is developed to assess their influence on the simulation results. The established FE models are verified against the test results demonstrating their effectiveness in predicting the structural behaviour of the concrete-filled WAAM steel tube. The composite action between the WAAM steel tube and inner concrete is analyzed through the validated FE models, indicating that it should be emphasized within the strain range from 0.003 to 0.01. The influences of the concrete and steel strengths are evaluated to investigate the confinement effect, showing that the concrete and steel strength exhibit a negative and positive impact on the confinement effect, respectively, and a positive correlation between the steel strength and biaxial stresses of the WAAM steel tube can be obtained. Finally, the design method of concrete-filled WAAM steel tube under axial compression, which considers the effect of the geometric undulations and material anisotropy of the WAAM steel tube, is proposed based on the theory of confining effect. The comparison results indicate that the proposed method can predict the axial compressive strengths of the concrete-filled WAAM steel tubes with reasonable accuracy.

Predicting energy consumption of mosque buildings during the operation stage using deep learning approach

The energy consumption resulting from the construction sector is increasing rapidly. Different building types have different energy consumption schemes, especially during their operational stage. Among these types of buildings, mosques are considered one of the intermittent building types that suffer from huge energy wastage. That’s why there is a need to monitor their operational performance through retrofitting or changing their operational scheme to enhance their operational performance and examine the effect of different alterations on the annual energy consumption. However, using traditional methods and simulation models to examine the impact of different alterations on the annual energy consumption of the mosque is considered difficult and time-consuming. Using machine learning and deep learning models, energy prediction models facilitated energy consumption predictions for improving building energy utilization. Therefore, this paper proposes an efficient approach for predicting mosques’ energy consumption using a deep learning approach. Convolution Neural Network (CNN) deep learning model is developed to predict the annual energy consumption of mosque buildings based on various operational Scenarios. 3D Laser scanning and a detailed energy analysis model with various simulation results are used to generate the mosque’s simulated energy consumption dataset. Different operational variables, such as the operational schedule, division of the mosque into zones, utilization of dimmers, presence of cooling system and the setting point, and the power consumption of the lighting system and appliances, have been utilized to estimate the annual energy consumption for the mosque to formulate the database. Using the mosque’s simulated energy consumption dataset, the CNN model was trained and tested to obtain the best model configuration with regard to the defined performance metrics. Besides, the performance of the developed model has been compared with the Support Vector Regression (SVR) model. The developed model has achieved results of 4.5% and 0.98 for the MAPE and R2, respectively. The results revealed the developed CNN model's effectiveness for predicting energy consumption for mosque buildings. This model will help compare different operational strategies for mosque buildings and determine energy consumption and energy-efficient options based on different operational characteristics.

Determination of quantity and volume of Carya cathayensis Sarg by line laser scanning combined with the point cloud fusion algorithm

Optical 3D measurement technology plays a vital role in diverse industries, particularly with the advancements in line laser scanning 3D imaging. In this paper, we propose a line laser scanning-based investigation for detecting Carya cathayensis Sarg. The Carya cathayensis Sarg specimens are scanned using a line laser to achieve three-dimensional reconstruction, enabling the calculation of their volume and quantity based on the acquired point cloud map. Through binocular acquisition and subsequent point cloud alignment and fusion, the error in the three-dimensional reconstruction is significantly reduced. The point cloud map facilitates the automatic identification of the number of scanned areas of Carya cathayensis Sarg areas and accurate volume calculations, with an error control of approximately 0.6% when compared to the actual volume. The application of this research in agriculture allows farmers to classify fruit sizes and optimize their selection, thus facilitating intelligent agricultural practices.

Experimental investigation of fixed-ended hot-rolled austenitic stainless-steel unequal-leg angles under compression

Structural stainless steel is gaining traction in the structural engineering field, however, there is currently limited published data on the performance of stainless steel unequal-leg single-angle compression members. This limitation of published data is reflected in the recently released AISC 370: Specification for Structural Stainless Steel Buildings which is limited in scope to equal-leg cross sections. Furthermore, the Specification requires the consideration of flexural–torsional buckling for single angles which is in contrast to the original design guidelines from AISC published in 2013, which mirrored the carbon steel specifications and did not required checking for flexural–torsional buckling for single angles. This paper reports a comprehensive experimental study on the behavior of hot-rolled austenitic stainless steel unequal-leg angle columns. A series of unequal-leg angles with cross-sectional dimensions of 76.2 × 50.8 × 6.35 mm (3″× 2″× 1/4″) and lengths ranging from 250 mm (10″) to 3760 mm (148″) were tested in compression. The ultimate loads were recorded in addition to displacements, twists, and failure modes through the use of strain gauges and an optical tracking system. The material properties were obtained through a series of tensile coupon tests, and the member geometric imperfections were measured through a non-contact 3D laser scanning technique. In addition, residual stress distributions were measured by the sectioning method. The results obtained from this experimental investigation indicated: (1) that torsional buckling is dominant in the shorter lengths and minor-axis flexural buckling in the longer lengths, with a transition occurring gradually in the middle lengths; (2) that the measured material properties are significantly higher than nominal values, and that this had a significant effect on the capacity predicted by the design provisions; (3) flexural buckling design provisions provide a better estimation than flexural–torsional buckling design provisions, although both are conservative.

PointSGRADE: Sparse learning with graph representation for anomaly detection by using unstructured 3D point cloud data

Surface anomaly detection by using 3D point cloud data has recently received significant attention. To completely measure the common free-form surfaces without loss of details, advanced 3D scanning technologies, such as 3D laser scanners, can be applied and will produce an unstructured point cloud. However, this irregular data structure poses challenges to anomaly detection, in that the existing methods based on regular data, e.g., 2D image, cannot be directly applied. This article proposes a sparse learning framework with a graph representation of the unstructured point cloud for anomaly detection (PointSGRADE). Specifically, the free-form surface is assumed to be smooth. Then, the associated point cloud can be represented as a graph. Subsequently, considering the sparse anomalies, we propose a sparse learning framework and formulate the anomaly detection problem as a penalized optimization problem, which is further solved by a computationally efficient majorization-minimization framework. Case studies demonstrate the accuracy and robustness of the proposed method. This article proposes a novel methodology for sparse anomaly detection on smooth free-form surfaces represented by unstructured point cloud, which is critical for quality inspection in manufacturing and other application areas.

RESEARCH PROGRESS IN THE SPLICING AND RESTORATION OF ARTIFACT FRAGMENTS BASED ON POINT CLOUD

Abstract. Due to environmental reasons, most of the artifacts are fragmented, and the surface information of the artifacts is also blurred. The traditional method of repairing artifacts mainly relies on archaeologists to manually repair them, using fragment features to compare each fragment one by one, this method will cause secondary damage to the fragments. Based on computer technology, virtual restoration of artifacts fragments can obtain the latest unearthed data of artifacts quickly, preserve digital information of artifacts, achieve permanent preservation, and provide prior knowledge for subsequent artifacts restoration. Point cloud data is widely used in artifacts virtual restoration technology due to its good depth of information. This paper takes ceramics, bronzes, Terra-cotta Warriors, and other individual artifacts fragments as the main research object, and the point cloud data obtained by 3D laser scanner as the main research data. It comprehensively classifies and summarizes the work of computer artifacts splicing in recent years.

Mechanical behavior of austenitic stainless steels produced by wire arc additive manufacturing

Wire arc additive manufacturing (WAAM) is an innovative technology with the potential to drive the transformation and upgrading of metallic manufacturing industry and construction sector. The advantages of WAAM technology in rapid manufacturing, design freedom, and energy saving have attracted attentions in the construction field. This research study focuses on investigating the microstructural and mechanical behavior of austenitic stainless steels produced by wire arc additive manufacturing through test programs. The stainless steel plates were first additively manufactured using cold metal transfer technology with three types of feedstock wires (ER304, ER308L, ER316L). Tensile coupon specimens and microstructural observation samples were extracted from the WAAM plates. The electron backscatter diffraction (EBSD) experiments were conducted to identify and analyze the microstructures of the WAAM austenitic stainless steels. Five test orientations, namely θ = 0˚, 30˚, 45˚, 60˚, 90˚ relative to the printing layer direction, were designed to investigate the mechanical properties anisotropy. Two types of specimen surface condition (milled type and as-built type) were considered to assess the impact of geometric undulation. The geometric features of the as-built specimens were obtained using 3D laser scanning. A total of 60 tensile tests with the aid of digital image correlation (DIC) system were conducted to obtain the stress–strain responses of the WAAM austenitic stainless steels. The mechanical properties anisotropy of the WAAM austenitic stainless steels was analyzed in detail.

Experimental Study of a Reconstruction Method for Rock Joints in Sandstone Based on 3D Laser Scanning and 3D Engraving Techniques

Experimental Study of a Reconstruction Method for Rock Joints in Sandstone Based on 3D Laser Scanning and 3D Engraving Techniques

Accuracy improvement of multi-view 3D laser scanning measurements based on point cloud error correction and global calibration optimization.

Multi-camera laser scanning measurement is emerging as a pivotal element in three-dimensional (3D) optical measurements. It reduces occlusion and enables the gathering of more 3D data. However, it also increases the difficulty of system algorithms in obtaining high measurement accuracy. To improve the measurement accuracy, there is an urgent need to address global calibration and error correction issues caused by the employment of multi-view systems. An accuracy improvement method for multi-view 3D laser scanning measurements based on point cloud error correction and global calibration optimization is then proposed. First, a planar asymmetric circular grid target is designed to calibrate the cameras, laser planes, and initial global transformation matrices of the multi-view 3D laser scanning probe simultaneously. The influence of the position of the laser plane on the measurement error is analyzed and what we believe to be novel mathematical error influencing factors are then modelled for point accuracy. Furthermore, a believed to be novel error model based on the backpropagation (BP) neural network is established for the regression analysis of the mathematical error influencing factors and measurement deviations for each point based on the standard sphere plate measurement. The final measurement is optimized by the correction of point cloud for each camera of the multi-view system and the global calibration optimization based on the error model. The proposed method is reliable and easy to implement, since it only requires a standard sphere plate and a planar target. Several experiments show that the method can effectively improve the measurement accuracy of multi-view 3D laser scanning probe through point cloud error correction and calibration optimization.

Features of building a digital 3D model of the location of transportation infrastructure objects according to the results of measurements by a mobile laser scanner

Problem. Fast and high-quality development of project solutions for transport infrastructure objects and other linear artificial structures is based on the application of automated design systems. Modern automated design systems use digital 2D and 3D terrain models as input data. The development of digital terrain modeling is motivated by both the development of automated design systems and the development of specialized geodesic equipment. Functional capabilities of modern geodetic equipment in combination with systems for automated processing of geodetic measurement results make it possible to significantly reduce the time of measurement and processing of results and significantly improve the quality of the obtained results. Goal. The goal is to analyze the features of building a digital 3D model of the terrain of linear structures based on the results of measurements by a mobile laser scanner. Methodology. The technical parameters and functional capabilities of the Trimble MX2 mobile laser 3D scanner were analyzed. The Trimble MX2 mobile laser scanner is a high-speed and productive scanning system designed for installation in a vehicle. Results. The Trimble MX2 mobile laser 3D scanner allows you to perform laser scanning of the road surface and the surrounding area and create output data for building a digital terrain model. A digital terrain model using this technology can be created without stopping traffic flow. The Trimble MX2 mobile laser 3D scanner is mounted on the base of a passenger car and requires the involvement of one driver and one surveyor operator. The main elements of the system – an inertial sensor, GNSS receivers and scanning heads allow obtaining a cloud of points with high positioning accuracy. The system is managed through the operator's console in the car interior. With the help of systems for automated processing of measurement results, the cloud of points is transformed into a geospatial model of the area, which allows you to obtain a digital model of the area many times faster than using traditional measurement methods. Originality. Thanks to the available Trimble MX2 GNSS receivers in the scanning system and with the help of the Trident Imaging Hub software complex, the obtained measurement results are linked to the desired coordinate system and the scanning system route is visualized, which enables to link all the obtained results with absolutely clear positioning on the terrain. Practical value. With the use of the Trimble MX2 scanning system, road surveys of Ukraine are already being carried out, which allows to quickly and qualitatively develop capital repair and reconstruction projects and to determine the necessary measures for the proper operational maintenance of road sections.

Effect of roughness on shear behavior of interface between cemented paste backfill and rock

The interaction between cemented paste backfill (CPB) and rock at their interface plays a crucial role in the stability of underground backfill structures. Considering the interface roughness could have a significant influence on the shear behavior and mechanical properties of the interface, a series of laboratory direct shear tests were carried out on the CPB-rock interface with various roughnesses. The results indicates that the interface roughness and normal stresses have a remarkable effect on the interfacial shear behavior, with typical stress-shear displacement curves that could be classified into three types depending on the peak and post-peak characteristics. Compared to the smooth interface, the shear strength increases with increasing roughness, owing to the enhancing interlocking effect, which is confirmed by digital image correlation (DIC) in micro views. In addition, the shear contraction observed at the smooth interface changes to shear dilatation at the rough interface, which is caused by wider distribution and higher adhesion of CPB asperities, as observes by using 3D laser scanning technology. Furthermore, a theoretical model for the shear strength, taking into account the influence of interface roughness, is developed to assess its effect on shear strength. The experimental results and the theoretical model presented in this paper will contribute to better understand the interaction mechanism and predict the shear strength of the interface.

Assessing the precision of machine tools through various measurement systems

Nowadays, machine tools have to meet high precision requirements when it comes to manufacturing parts that have to correspond exactly to the specified geometries. Achieving high precision and accuracy when machining parts is a growing challenge, especially as machine tool operating hours increase. This increasing challenge emphasizes the need for regular verification of machine tool accuracy. In this study, the accuracy of a three-axis milling center was investigated, analyzing different measurement systems suitable for evaluating the precision of machine tools. The main objective was to evaluate the feasibility of using faster and less expensive inspection methods and measurement systems without compromising the reliability of the evaluation process. The research included an investigation of two different measurement systems developed for the acquisition of machine tool accuracy data: a coordinate measuring machine equipped with a contact sensor and a 3D laser scanner. The aim of this comparative analysis is to identify optimal approaches to machine tool accuracy assessment that balance speed and affordability while ensuring the reliability and trustworthiness of the test results obtained.

Optimization method of 3D reconstruction of metal cultural relics based on 3D laser scanning data reduction

AbstractThe extraction effect and feature matching are poor in the three‐dimensional reconstruction of metal cultural relics, which leads to a poor reconstruction effect. Therefore, an optimization method of three‐dimensional reconstruction of metal cultural relics based on 3D laser scanning data reduction is proposed. The overall technical design route of the method is shown as follows. Based on this model, the 3D laser scanning method is used to collect 3D images of metal artefacts, combined with colour space and 2D entropy detection methods to pre‐process 3D images, and feature matching of point clouds is carried out to extract and optimize the significant value of superpixels, and a 3D reconstructed visual model is constructed. Affine transformation is used to obtain the affine invariant moment of the structural light parameters of the visual feature lines of metal cultural relics. The light stability adjustment of the three‐dimensional reconstruction of metal cultural relics is realized by using the linear structural light adjustment method in the HSV colour space. The rigid and non‐rigid registration methods are introduced to match the point cloud. The product quantization algorithm is used to linearize the error function, and the block feature detection and matching model of spatial image is obtained. The noise number is judged by the threshold value, and the three‐dimensional reconstruction technology is combined to realize the three‐dimensional reconstruction of metal relics. The simulation results show that this method has good visual expression ability, high feature recognition rate, and improves the three‐dimensional reconstruction ability of metal relics.

Simulation and Analysis of Arc-drop Deformation of High-voltage Cables with Three-dimensional Laser Scanning Point Cloud

In order to investigate the influence of environmental factors on the deformation problems occurring in high voltage cables, this paper proposes a method for analyzing the deformation of high voltage cables based on 3D laser scanning. Firstly high voltage cable point cloud data is acquired. Secondly, a single power line is segmented using a density-based clustering method, and a mathematical model of the high-voltage cable is established using the least squares method. Then the high-voltage cable is downscaled from three-dimensional points to two-dimensional points to do the fitting of parabola on the plane. Finally compare the horizontal displacement and vertical displacement of the lowest overhanging point of the high-voltage cable with the weather to affect its deformation causes. The experimental results show that: the parabolic approximate fitting equation of the high voltage cable can accurately express the shape of the cable, and the R value of the equation is around 0.999. The vertical displacement of the high-voltage cable in the high-temperature and high humidity environment changes significantly, up to 0.556 m. Horizontal displacement is significantly affected by the wind, the wind in the 7mph horizontal displacement change is the largest, the average displacement change of 0.197m.

Morphological damage and strength deterioration of red sandstone under freeze–thaw cycles

Insight into the growth of internal microstructure and surface morphology is critical for understanding the robustness of red sandstone artifacts in frigid environments. Since freeze–thaw (F-T) cycles can exacerbate the surface deterioration of water-bearing sandstone, a series of investigation on fresh and weathered water-bearing sandstone samples with different F-T cycle numbers (i.e. 0–100) is performed in this study, including three-dimensional (3D) laser scanning, scanning electron microscope (SEM) and computed tomography (CT) scanning tests, thermal property tests, Brazilian tests, and multi-field numerical simulations. Our results demonstrate that with increasing F-T cycles, the surface fractal dimension and specific surface area of red sandstone samples increase, and the pore size distribution inside rocks shifts from ultrananopores (10–100 nm) to micro-pores (0.1–100 μm) and ultramicropores (100 μm+). Spatially, the pores generated by the F-T cycles are more prominent near the surfaces of rock samples. Numerical simulation indicates that the uneven pore distribution leads to surface degradation. After 100 F-T cycles, the intergranular (IG) cement of the samples cracks, and the IG fractures are widened; eventually, due to the structural integrity weakening, the tensile strength is drastically reduced by over half. The thermal properties of the water-saturated sandstone can be improved during the F-T cycles, and a strong coefficient of determination of 0.98 exists between the fractal dimensions of sandstone surface and the tensile strength. When assessing the mechanical properties of stone artifacts under F-T cycles, the morphological damage of red sandstone should first be investigated when in situ sampling is inappropriate.

Particle morphology characterization of waste-tyre-stabilized rock aggregates via computational geometric modellings

This study offers a comprehensive understanding of the most important geometrical concepts for concave shape particles with very low sphericity. Study of concave hulls in three-dimensional space is performed with an emphasis on accurate and asymptotically fast algorithms. Based on that a three-dimensional concave hull algorithm is designed to generate the actual shape of irregular particles through a set of 3D surface coordinate data points captured by 3D handy laser scanner and photogrammetry. The algorithm is utilized for a wide range of large-scale waste tyre and rock aggregates to assess several fundamental theoretical hypotheses related to geometric parameters, including surface texture with concavity/convexity, concave hull volume, perimeters of projected area, and concavity computation that have not been tested before for highly irregular concave shape particles. As a result, the morphological characteristics of the waste-tyre-stabilized rock aggregate mixtures are analysed for mining operations. We also provide the details on how the application of the resulting particle morphology is employed in cloning particles with wide range of concavity distribution. The paper identifies the accuracy by implementing the proposed 3D concave hull algorithm for morphology analysis of concave particles and comparing the morphology analysis results against those of Finite Element Method (FEM), polar representation approach (PRA), and experimental data.