High-Fidelity Reconstruction of Tunnel Profiles for Deformation Measurement: A 3D Laser Scanning System

  • Gu, Kejie (Tongji University)
  • Liu, Xian (Tongji University)
  • Cao, Ba Trung (Ruhr University Bochum)
  • Liu, Zhen (Ruhr University Bochum)

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Accurate reconstruction of tunnel profiles and deformation measurement constitute a fundamental prerequisite for reliable structural health assessment and condition evaluation[1]. Structural health monitoring (SHM) of tunnels relies on high-precision geometric measurements to ensure the fidelity of reconstructed profiles[2]. Conventional Mobile Laser Scanning (MLS) systems, while efficient, are often affected by motion-induced blurring and cumulative positioning drift caused by vehicle vibration and varying travel speeds, and their deformation-monitoring accuracy in practice is commonly at the millimeter level[3]. To overcome these limitations and achieve sub-millimeter-level precision, this paper presents a specialized tunnel profile measurement system designed to eliminate these kinematic artifacts through a "Move-Stop-Scan" operational strategy.The hardware architecture integrates a high-speed line laser triangulation profiler with a precision rotary drive and an adjustable mechanical arm. In contrast to traditional helical scanning, the proposed system performs a complete profile measurement only when the vehicle is stationary. Data acquisition is precisely synchronized with a high-resolution angular encoder, which triggers the sensor via pulse signals to maintain a consistent circumferential resolution of 0.2 mm across the tunnel surface. The optical configuration is meticulously optimized based on the laser triangulation principle, incorporating the Scheimpflug condition to ensure a sharp focus and high absolute accuracy within the entire radial working range.The reliability and applicability of the system were verified through a full-scale loading test; the results demonstrate high measurement accuracy and reveal correlations among different deformation responses, thereby providing a robust, high-precision data basis for high-fidelity digitalization [2] of underground infrastructure, as well as establishing a solid foundation for SHM-based condition assessment and operation-and-maintenance decision-making.