Measurement of Tunnel Clearance Convergence Using Mobile Laser Detection Technology

Yue, Zeyu; Sun, Hao; Zhong, Rugang; Ma, Huali; Zhi-niu, XU; Elliott, Francis

doi:10.1080/07038992.2021.1897554

Cited by 6 publications

(9 citation statements)

References 25 publications

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“…In this study, a calculation method for the chord length and net height of the arch crown was developed, and the accuracy of the method was verified by comparing the results against the actual measurements of a 2000 m-long tunnel. The average roundtrip deviation of the chord length was 1.7 mm and that of the net height of the arch crown was 1.4 mm, which are equivalent to the calculation accuracies in [34]. However, only a 200 m-long tunnel was used for verification in [34].…”

Section: Discussionmentioning

confidence: 86%

“…Regarding deformation detection of the mining method tunnel, in the previous study [34], the chord length and net height of the arch crown were calculated, and the results were verified for a 200 m-long tunnel. The average deviation between the chord length and net height of the arch crown in the roundtrip measurement was 1.3 mm.…”

Section: Discussionmentioning

confidence: 89%

“…Moreover, the acquisition of design data, measurement of track centerline coordinates, and fusion of multi-sensors enhance the difficulty in conducting field operations and increase the cost investment. In [34], mine tunnel positioning was performed by manually selecting points on the gray scale image, which increased the complexity and reduced the efficiency of the offsite work.…”

Section: Discussionmentioning

confidence: 99%

“…The deformation analysis of a mining tunnel is still mainly based on the fixed-point detection of deformation using the traditional total station method. Yue et al [34] proposed a mining tunnel deformation detection method in combination with mobile laser scanning data. The section was located using the gray image, and the chord length, vault net height, and catenary guide height of the section were calculated.…”

Section: Introductionmentioning

confidence: 99%

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Deformation Detection of Mining Tunnel Based on Automatic Target Recognition

Sun

Zhong

et al. 2023

Remote Sensing

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Mining tunnels have irregular and diverse cross-sectional shapes. Structural deformation detection using mobile laser measurement has some problems, such as the inconvenient positioning of the deformation, difficulties in unifying the multiphase data, and difficulties in solving the section parameters. To address these problems, this paper proposes a mining tunnel deformation detection method based on automatic target recognition. Firstly, a mobile tunnel laser detection scheme combined with the target layout is designed. Secondly, a preview image of the tunnel lining is generated using the mobile laser point cloud data, and the index relationship between the image and point cloud is established. The target recognition accuracy of the You Only Look Once version 4 (YOLOv4) model is optimized by integrating the prediction confidence threshold, target spatial position, and target gray scale rule. Based on target recognition and positioning, the chord length and vault net height of the mining tunnel are calculated using gross error elimination and curve fitting. Finally, the engineering application of the model and algorithm is realized using ML.NET. The research method was verified using the field measurement data of the mining tunnel. The target recognition accuracy reached 100%, and the repeated deviations of the chord length and net height of the arch crown were 1.7 mm and 1.4 mm, respectively, which established the effectiveness and high accuracy of the research method.

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Section: Discussionmentioning

confidence: 86%

Section: Discussionmentioning

confidence: 89%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Deformation Detection of Mining Tunnel Based on Automatic Target Recognition

Sun

Zhong

et al. 2023

Remote Sensing

Self Cite

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“…Therefore, each system has different advantages and is suitable for certain projects. ALS and MLS can scan large areas quickly and survey areas with limited accessibility, while TLS allows for more detailed point clouds with relatively high precision and low cost [ 230 , 231 , 232 , 233 , 234 ].…”

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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