Shield Tunnel Convergence Diameter Detection Based on Self-Driven Mobile Laser Scanning

Abstract

The convergence diameter of shield tunnels is detected by ellipse fitting or local curve fitting to cross-section points. However, the tunnel section, which is extruded by an external force, has an irregular elliptical shape, and the waist of the tunnel is often blocked by accessories, resulting in data loss. This study proposes a convergence diameter and radial dislocation detection method based on block-level fitting. The proposed method solves the accuracy degradation caused by the model error and point cloud incompletion. First, the noise points in the tunnel section point cloud are removed using the least trimmed squares method. Second, the tunnel transverse seam is then located using the image edge detection algorithm. Third, the endpoint of the convergence diameter is determined by making a specific segment the center and shifting the detector from the center to the pinpoint. Finally, the convergence diameter and radial dislocation are detected by the endpoints of the segments. The experimental results showed that the absolute detection accuracy of this method was better than 3 mm, and the repeated detection accuracy was better than 2 mm. This result is consistent with prior total station measurements, which are more suitable for practical engineering applications.