A multi-level 3D data registration approach for supporting reliable spatial change classification of single-pier bridges

Kalasapudi, Vamsi Sai; Tang, Pingbo; Xiong, Wen; Song, Ying

doi:10.1016/j.aei.2018.06.010

Cited by 12 publications

(5 citation statements)

References 46 publications

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“…As aforementioned, point cloud registration consists of the coarse registration and the fne registration. According to previous research, algorithms for coarse registration roughly align the two point clouds and have already provided good input for fne registration [38]. Hence, this study will focus on the algorithms for fne registration, covering the traditional ICP algorithm and two improved ICP algorithms, i.e., the kd-tree-based ICP algorithm and the feature point-based ICP algorithm.…”

Section: Theoretical Background Of Registration Algorithmsmentioning

confidence: 99%

“…Considering that the previous ICP algorithm used all points for registration, the feature point-based ICP algorithm considered that there were interference points in the point cloud that needed to be removed before registration [38]. It is worth mentioning that these interference points are not noise points that were removed in the earlier point cloud preprocessing, but rather points that have changed position in the point cloud.…”

Section: Traditional Icp Algorithmmentioning

confidence: 99%

“…Terefore, the deformation values using the traditional ICP algorithm and kd-tree-based ICP algorithm in Table 4 are the rigid body deformation results of the bridge tower calculated by these two algorithms. On the other hand, the feature point-based ICP algorithm, compared to the feature points in the source point cloud, the feature points in the target point cloud are only rigidly deformed by the overall deformation of the bridge but not internally deformed by external loads [38]. Te overall bridge deformation is interpreted as a stress-free change in the relative position between the bridge and the environment.…”

Section: Transformation Matrix and Measured Bridgementioning

confidence: 99%

“…Te overall rotation and translation of several single-pier highway bridges were identifed by the ICP registration algorithm [37], and the compression and torsion states of the main girders were obtained. On this basis, Kalasapudi et al [38] proposed an improved ICP algorithm that used certain rules to eliminate the points in the bridge point cloud that undergo position changes, and obtained a more reasonable transformation matrix with deformation recognition results. Te transformation relations were obtained by these ICP algorithms and their variants by registering old and new point sets and fnally acquiring the deformation of the structures [9].…”

Section: Introductionmentioning

confidence: 99%

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Point Cloud Registration Methods for Long-Span Bridge Spatial Deformation Monitoring Using Terrestrial Laser Scanning

Zhang

Zhu

Xiong

et al. 2023

Structural Control and Health Monitoring

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In recent years, efforts have been devoted to utilizing terrestrial laser scanning for bridge spatial performance inspection, but they are still restricted to small or medium-span bridges, like some historical heritages. Due to the large-scale dimensional features of long-span bridges, applications of 3D point cloud techniques still remain challenging, such as the extra-long scan range and extreme-small incidence angle when scanning a bridge with a span over 1000 m. Moreover, rare attempts can be found for the performance evaluation of point cloud registration methods for long-span bridges as well, which is a critical basis for further spatial deformation recognition on the point cloud data. Hence, in this study, a cross-evaluation of three iterative closest point (ICP) registration methods is conducted for long-span suspension bridges, namely, traditional ICP, kd-tree-based ICP, and feature point-based ICP algorithms. We conducted field laser scanning on the Ma’anshan Yangtze Bridge, an 1880 m long suspension bridge located in China. The results show that the feature point-based ICP algorithm outperforms the other two in terms of convergence rate and execution time for a single iteration due to the smaller number of registration points compared to the other two algorithms. Moreover, it also gives more precise values in terms of bridge tower spatial deformation identification. Meanwhile, due to efficient data organization, the kd-tree-based ICP algorithm takes less time for a single iteration than the traditional ICP algorithm. Finally, two suggestions for algorithm improvement in terms of efficiency optimization and accuracy improvement of long-span bridge deformation analysis are proposed based on the assessment results.

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Section: Theoretical Background Of Registration Algorithmsmentioning

confidence: 99%

Section: Traditional Icp Algorithmmentioning

confidence: 99%

Section: Transformation Matrix and Measured Bridgementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Point Cloud Registration Methods for Long-Span Bridge Spatial Deformation Monitoring Using Terrestrial Laser Scanning

Zhang

Zhu

Xiong

et al. 2023

Structural Control and Health Monitoring

Self Cite

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show abstract

“…Deformation measurement is focused on changes in the relative position of a structure, which requires the collection scanning data at a certain interval to maintain periodic monitoring of the structural response by comparing data at different time points. Various case studies have been carried out on the monitoring of engineering structures, including buildings [ 104 , 145 ], dams [ 113 , 122 , 126 , 130 ], bridges [ 59 , 100 , 105 , 106 , 108 , 109 , 110 , 116 , 118 , 119 , 121 , 123 , 124 , 128 , 137 , 144 ], tunnels [ 57 , 80 , 103 , 107 , 114 , 115 , 117 , 125 , 127 , 129 , 131 , 132 , 134 , 135 , 136 , 139 , 140 ], stations [ 99 , 143 ], foundation pits [ 186 ], pipe racks [ 52 ], towers [ 101 ], and many others. In addition, another main direction of studies for deformation measurement is to perform structural health monitoring of infrastructures that are in service for a long time, especially for masonry [ 99 , 1...…”

Section: Research Topics Related To Tls In the Aec Industrymentioning

confidence: 99%

Application of Terrestrial Laser Scanning (TLS) in the Architecture, Engineering and Construction (AEC) Industry

Yuan

Yang

et al. 2021

Sensors

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As a revolutionary technology, terrestrial laser scanning (TLS) is attracting increasing interest in the fields of architecture, engineering and construction (AEC), with outstanding advantages, such as highly automated, non-contact operation and efficient large-scale sampling capability. TLS has extended a new approach to capturing extremely comprehensive data of the construction environment, providing detailed information for further analysis. This paper presents a systematic review based on scientometric and qualitative analysis to summarize the progress and the current status of the topic and to point out promising research efforts. To begin with, a brief understanding of TLS is provided. Following the selection of relevant papers through a literature search, a scientometric analysis of papers is carried out. Then, major applications are categorized and presented, including (1) 3D model reconstruction, (2) object recognition, (3) deformation measurement, (4) quality assessment, and (5) progress tracking. For widespread adoption and effective use of TLS, essential problems impacting working effects in application are summarized as follows: workflow, data quality, scan planning, and data processing. Finally, future research directions are suggested, including: (1) cost control of hardware and software, (2) improvement of data processing capability, (3) automatic scan planning, (4) integration of digital technologies, (5) adoption of artificial intelligence.

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Automated measurement method for cable shapes based on laser scanners and cameras

Wang,

Li,

et al. 2024

J Civil Struct Health Monit

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A multi-level 3D data registration approach for supporting reliable spatial change classification of single-pier bridges

Cited by 12 publications

References 46 publications

Point Cloud Registration Methods for Long-Span Bridge Spatial Deformation Monitoring Using Terrestrial Laser Scanning

Point Cloud Registration Methods for Long-Span Bridge Spatial Deformation Monitoring Using Terrestrial Laser Scanning

Application of Terrestrial Laser Scanning (TLS) in the Architecture, Engineering and Construction (AEC) Industry

Automated measurement method for cable shapes based on laser scanners and cameras

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