Geometric shape measurement and its application in bridge construction based on UAV and terrestrial laser scanner

Han, Yitian; Feng, Dongming; Wu, Weiwei; Yu, Xingyu; Wu, Gang; Liu, Jixiang

doi:10.1016/j.autcon.2023.104880

Cited by 13 publications

(5 citation statements)

References 18 publications

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“…The analysis examines factors such as point cloud model, specific application, data acquisition device, image resolution, image processing software, and post-processing errors. Han et al [38] are noteworthy for their use of automatic bridge alignment extraction using point cloud data acquired with UAVs and TLS. They also used the FPS algorithm in conjunction with high-resolution images (5184 × 3888), resulting in a minimum error of 0.105 cm.…”

Section: Discussionmentioning

confidence: 99%

Estimation of the Physical Progress of Work Using UAV and BIM in Construction Projects

Palomino Ojeda,

Quiñones Huatangari,

Cayatopa Calderon

et al. 2024

Civ Eng J

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The delay in the physical progress of construction creates additional costs, missed deadlines, and quality issues. The research aimed to estimate the physical progress of the project by using unmanned aerial vehicles (UAVs) and building information modeling (BIM). The methodology comprised capturing 848 high-resolution images of the Civil Engineering Laboratory construction site at the National University of Jaen, Cajamarca, Peru, using the Phantom 4 RTK drone. The photographs were processed using Agisoft 2.0.1 software, resulting in a point cloud. This was then imported into ReCap Pro 2023 software, which was used to assess the quality of the points. The Revit 2023 software was subsequently utilized to establish the phase parameters, linking the BIM model with the point cloud, filtering the model, and eventually exporting it to the Power BI 2023 software. The work's estimated progress utilizing the proposed methodology was 42.82%, which was not statistically significant compared to the Public Works Information System (INFOBRAS) of 43.14%. This allows for the automation of customary processes, the identification of crucial issues, and prompt decision-making. The study's originality lies in the suggestion of integrating aerial imagery with drones and BIM modeling for the real-time and precise estimation of work progression. This method provides a precise and effective substitute for traditional techniques for gauging the tangible advancement of projects. Doi: 10.28991/CEJ-2024-010-02-02 Full Text: PDF

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Section: Discussionmentioning

confidence: 99%

Estimation of the Physical Progress of Work Using UAV and BIM in Construction Projects

Palomino Ojeda,

Quiñones Huatangari,

Cayatopa Calderon

et al. 2024

Civ Eng J

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“…Its outstanding performance stretches to the fields of unmanned driving [16] and forest monitoring [17], and it has applications in modeling and mapping, such as bridge deformation monitoring [18][19][20], tunnel safety monitoring [21], and wind turbine monitoring [22][23][24]. High-resolution lidar is often chosen for monitoring bridge deformation [18][19][20], that is, the three-dimensional laser scanner is capable of acquiring point cloud data of high-density objects, though the cost of it is high. In 2017, Ivan Nikolov et al [22] employed RPLIDAR and a 9-DOF Inertial Measurement Unit (IMU) for positioning and mapping.…”

Section: Introductionmentioning

confidence: 99%

Lidar-Based Spatial Large Deflection Measurement System for Wind Turbine Blades

Hu,

Zhu,

Zhou

et al. 2024

Optics

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With the advancement of China’s wind power industry, research into full-scale structural testing of wind turbine blades, including static testing and fatigue testing, has shown increasing significance. Static testing measures the deflection at fixed points, using pull-wire sensors in industrial practice. However, the demerits of this method involve single dimension, excessive deviation, costly experiment, and complex installment. Given the advantages that lidar provides, correspondingly, high data density, precision, and convenience, we proposed a simple and efficient spatial large deflection measurement system for wind turbine blades with multi lidars. For point clouds collected from lidar scanners, registration based on point primitives and geometric primitives, dynamic radius DBSCAN clustering, spatial line clustering, and line integrals are applied to calculate the 3D coordinates of measured points on the blade. Experimentally validated, the proposed method demonstrates its effectiveness in serving as a viable alternative to the traditional pull-wire sensor measurement approach. In the minimum oscillation direction test, the measurement error is controlled within 3% compared to the theoretical value. Simultaneously, in the maximum swing direction test, the 3D coordinates of the measured point remain consistent with the changing trend observed under small deformation. These results confirm the feasibility of the system and its potentials to be generalized.

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“…Additionally, UAVs have been involved in numerous civil engineering applications for structural health inspections. They have been used for detecting bridge cracks [27], identifying dynamic parameters of bridge components [28], measuring geometry shapes of bridge components [29], and the 3D reconstruction of bridges [30]. The utilization of UAVs under certain weather conditions can improve efficiency and ensure the safety of the inspection personnel compared to manual inspections [31].…”

Section: Introductionmentioning

confidence: 99%

A Novel Debonding Damage Identification Approach of Hidden Frame-Supported Glass Curtain Walls Based on UAV-LDV System

Zheng,

Guo,

Zhi

et al. 2024

Applied Sciences

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This study introduces a novel Unmanned Aerial Vehicle-mounted (UAV-mounted) Laser Doppler Vibrometer (LDV) system for detecting debonding damage in Hidden Frame-Supported Glass Curtain Walls (HFSGCW). The established system enables UAVs to transport the LDV to high altitudes for operation. The vibration signals acquired by the UAV-LDV system are decomposed into different energy bands by wavelet packet analysis, and then the occurrence and location of the damage are identified by the Sum of Squared Differences (SSD) of the wavelet packet bands’ energy. This paper investigates the potential factors affecting the performance of the Unmanned Aerial Vehicle-Laser Doppler Vibrometer (UAV-LDV) system, including the arrangement of measuring points, measuring distance, noise level, and wind speed through the first-order natural frequency, the normalized frequency response functions, and the SSD indicator. Experimental and simulation results confirm the effectiveness of the UAV-LDV system, highlighting its advantages over traditional methods by offering remote, non-contact, and efficient debonding detection. This method not only indicates the presence of the damage, as traditional indicators do, but also pinpoints the exact location of it, ensuring safety and cost-effectiveness in high-rise inspections. The proposed method and indicator offer advantages in terms of convenience, visualization, and efficiency. The study discusses the impact of measurement point arrangement, measuring distance, noise levels, and wind speed on the system’s performance. The findings demonstrate that while the UAV-LDV system introduces new capabilities in rapid and reliable structural damage assessment, operational challenges such as wind and noise levels significantly influence its accuracy.

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Geometric shape measurement and its application in bridge construction based on UAV and terrestrial laser scanner

Cited by 13 publications

References 18 publications

Estimation of the Physical Progress of Work Using UAV and BIM in Construction Projects

Estimation of the Physical Progress of Work Using UAV and BIM in Construction Projects

Lidar-Based Spatial Large Deflection Measurement System for Wind Turbine Blades

A Novel Debonding Damage Identification Approach of Hidden Frame-Supported Glass Curtain Walls Based on UAV-LDV System

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