Comparative Validation of Laser Scanning and Traditional Measurement Methods for Tunnel Convergence
Journal Title: Urban Mass Transit - Year 2025, Vol 28, Issue 3
Abstract
［Objective］ Although traditional single-point measurement methods offer high accuracy in metro tunnel monitoring, their high labor, material, and financial costs limit economic benefit maximization, difficult to meet the monitoring needs of modern metro tunnels. Therefore, it is crucial to develop a new method that satisfies the need for rapid measurement while ensuring accuracy. ［Method］ Using the convergence monitoring project of Shanghai rail transit as a case study, a comparative verification method is proposed. The high-accuracy advantage of manual total station single-point measurements is used to reversely validate the measurement accuracy of automated 3D laser scanners. On one hand, the specific accuracy of a particular laser scanner model under specific conditions can be determined; on the other hand, the feasibility of 3D laser scanning technology for metro tunnel deformation monitoring is further verified. Meanwhile, the point cloud data obtained by the 3D laser scanner, after processing, can generate tunnel unfolded maps, useful for analyzing tunnel issues such as water leakage. This bidirectional comparative validation could effectively balance the limitations of 3D laser scanning technology and traditional measurement methods. Though the 3D laser scanning technology provides continuous tunnel point cloud information, its single-point measurement accuracy is still inferior to traditional methods. Combining both methods can further improve the reliability of the data. ［Result & Conclusion］ Validation tests based on data from Shanghai Rail Transit Line 8 and Line 15 demonstrate that under the condition of a resolution of 1/8 and a quality mode of 3X, the FARO S70 laser scanner presents the average deviation of 4.24% in accuracy, with a minimum reliability of 93.63%, meeting the requirements for metro deformation monitoring.
Authors and Affiliations
Guojin HU, Caichu XIA, Shihao NI, Ting WU, Hangtian LI
Keywords
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- EP ID EP760139
- DOI 10.16037/j.1007-869x.2025.03.019
- Views 16
- Downloads 0
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