Objective Clearance detection is an indispensable process throughout the full life cycle of subway shield tunnels, directly impacting subway track laying quality and line operational safety. Total stations, currently the primary means for detecting subway shield tunnel clearance, suffer from deficiencies such as limited monitoring points and relatively low detection efficiency. Therefore, it is necessary to adopt new technologies to further optimize the subway shield tunnel clearance detection method.

Method The existing subway shield tunnel clearance detection methods are elaborated, including the tunnel centerline tangent vector extraction method, the tunnel cross-section extraction method, the cross-section point cloud fitting method, and the cross-section clearance violation determination method. Then, a LiDAR-based subway shield tunnel clearance detection method is proposed, along with the development of a specialized software for post-processing point cloud data to simplify the clearance detection work. This method is applied in a shield tunnel site of Beijing Subway, and the software detection data is compared with the field total station measured data.

Result & Conclusion  The proposed clearance detection method can efficiently and accurately detect tunnel cross-section clearance information, with calculation precision meeting engineering applications. The developed subway tunnel clearance detection software enables clearance detection of tunnel cross-sections and automatic calculation of clearance violation. The variation trend of software detection results is generally consistent with the total station measurement results, and the error between the two can be controlled within 8 mm.