{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T13:54:29Z","timestamp":1762005269095,"version":"build-2065373602"},"reference-count":40,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,21]],"date-time":"2020-09-21T00:00:00Z","timestamp":1600646400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Subway structure safety detection is an important method to ensure the safe operation of trains. Efficient, high-precision, and automatic tunnel clearance detection is the key to ensure safe operations. This study introduces a mobile tunnel scanning system that integrates a scanner, an inertial measurement unit (IMU), and a rail car. Global Navigation Satellite System (GNSS) time and system hardware calibration are used to synchronize time and space information of the system; the attitude and speed are corrected using the control points from the tunnel to improve the accuracy of absolute positioning. The section coordinate system is converted using the control points and system calibration parameters to complete the tunnel clearance inspection, and the distance between the nearest point of the section and the clear height of the vault is given. Taking Fengxi Road\u2019s Bashan tunnel section of Chongqing Metro Line 5 as an example, the overall system accuracy was tested. The accuracy of chord line measurements was within 1 mm, the internal coincidence accuracy of repeated measurements of the vault clear height was 1.1 mm, the internal coincidence accuracy of repeated measurements of the closest gauge point was 4.8 mm, and the system calibration accuracy was approximately 2 mm. Compared with the existing scheme, the system combines absolute measurement and relative measurement mode to judge the structural safety of tunnel section from multiple angles, high precision, and high efficiency.<\/jats:p>","DOI":"10.3390\/s20185400","type":"journal-article","created":{"date-parts":[[2020,9,21]],"date-time":"2020-09-21T08:18:01Z","timestamp":1600676281000},"page":"5400","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Deformation Detection Method of Mine Tunnel Based on Mobile Detection System"],"prefix":"10.3390","volume":"20","author":[{"given":"Jian","family":"Sun","sequence":"first","affiliation":[{"name":"Beijing Advanced Innovation Center for Imaging Theory and Technology, Key Laboratory of 3D Information Acquisition and Application, MOE, College of Resource Environment and Tourism, Academy for Multidisciplinary Studies, Capital Normal University, Beijing 100048, China"},{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haili","family":"Sun","sequence":"additional","affiliation":[{"name":"Beijing Advanced Innovation Center for Imaging Theory and Technology, Key Laboratory of 3D Information Acquisition and Application, MOE, College of Resource Environment and Tourism, Academy for Multidisciplinary Studies, Capital Normal University, Beijing 100048, China"},{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruofei","family":"Zhong","sequence":"additional","affiliation":[{"name":"Beijing Advanced Innovation Center for Imaging Theory and Technology, Key Laboratory of 3D Information Acquisition and Application, MOE, College of Resource Environment and Tourism, Academy for Multidisciplinary Studies, Capital Normal University, Beijing 100048, China"},{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yulong","family":"Han","sequence":"additional","affiliation":[{"name":"Beijing Advanced Innovation Center for Imaging Theory and Technology, Key Laboratory of 3D Information Acquisition and Application, MOE, College of Resource Environment and Tourism, Academy for Multidisciplinary Studies, Capital Normal University, Beijing 100048, China"},{"name":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,21]]},"reference":[{"key":"ref_1","unstructured":"China Association of Metros (2020, July 16). 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