Automatic Extraction of Tunnel Lining Cross-Sections from Terrestrial Laser Scanning Point Clouds

Area of Science:

• Geotechnical Engineering
• Civil Engineering
• Geomatics Engineering

Background:

• Tunnel lining cross-sections are crucial for analyzing tunnel deformation.
• Existing methods for extracting these cross-sections from point clouds can be unreliable.
• Accurate modeling of tunnel linings is essential for structural health monitoring.

Purpose of the Study:

• To develop an automatic method for extracting bare-lining cross-sections from terrestrial laser scanning (TLS) point clouds.
• To improve the accuracy and reliability of cross-sectional modeling for tunnel linings.
• To provide a robust approach for analyzing tunnel deformations.

Main Methods:

• Utilized a 2D projection strategy and angle criterion for tunnel boundary point detection.
• Employed total least squares and Rodrigues' rotation formula for precise cross-sectional plane adjustment.
• Developed a morphological erosion-inspired filtering algorithm to remove non-lining points.

Main Results:

• The proposed method successfully extracted bare-lining cross-sections from railway tunnel data.
• Achieved high accuracy and more reliable cross-sectional modeling compared to existing methods.
• Evaluated Type I and Type II errors of the filtering algorithm, providing parameter selection guidance.

Conclusions:

• The developed automatic method provides an accurate and reliable solution for extracting tunnel lining cross-sections from TLS data.
• This technique enhances the analysis of tunnel deformations and supports structural health monitoring.
• The filtering algorithm's error evaluation offers practical insights for parameter tuning.