Automated Deformation Monitoring for Urban Subway Tunnelling Risk Assessment: A Case Study from the Wuhan Metro Line 12

Abstract

Monitoring deformation is of critical importance for tunnel boring projects. This importance is further amplified for the metro construction project that involves boring beneath or near susceptible civil infrastructures. Here, we present a case study that uses a robotic total station to perform automated deformation monitoring inside a tunnel during excavation. Further, enabled with the Internet of Things technology, the monitoring data are streamlined through wireless internet access points and processed by a remote control center. A complete suite of software is deployed that can: (1) automatically process monitoring data; (2) set differentiated triggering thresholds corresponding to hazardous incidents of varying levels; (3) store data for subsequent analysis, which includes data visualization, overall risk level quantification, and predictive modelling. Built upon this automated system, a triage of risk response protocol is established that performs reactive treatment according to the levels of reported hazards. A de-risk process, involving third party review, is also established. Overall, this report demonstrates our effort in monitoring the tunnel’s deformation with an automated system to save cost and reduce human-induced errors. This report can be a useful reference for other engineers performing metro tunneling tasks.

Keywords

urban underground tunnelling / Yangtze River terrace / deformation monitoring / robotic total station / automation / engineering geology

References

[1] Bai X D, Cheng W C, Li G. A Comparative Study of Different Machine Learning Algorithms in Predicting EPB Shield Behaviour: A Case Study at the Xi’an Metro, China. Acta Geotechnica, 2021, 161240614080.

[2] Beer G. Technology Innovation in Underground Construction, 2009, New York: CRC Press

[3] Belyi A, Karapetov E, Efimenko Y. Structural Health and Geotechnical Monitoring during Transport Objects Construction and Maintenance (Saint-Petersburg Example). Procedia Engineering, 2017, 189: 145-151.

[4] Bennett P J, Soga K, Wassell I, et al. Wireless Sensor Networks for Underground Railway Applications: Case Studies in Prague and London. Smart Structures and Systems, 2010, 6: 619-639.

[5] Cheng W-C, Li G, Liu N, et al. Recent Massive Incidents for Subway Construction in Soft Alluvial Deposits of Taiwan: A Review. Tunnelling and Underground Space Technology, 2020, 96: 103178.

[6] Choi H H, Cho H N, Seo J W. Risk Assessment Methodology for Underground Construction Projects. Journal of Construction Engineering and Management, 2004, 1302258272.

[7] Dai C, Li W L, Wang D, et al. Active Landslide Detection Based on Sentinel-1 Data and InSAR Technology in Zhouqu County, Gansu Province, Northwest China. Journal of Earth Science, 2021, 32510921103.

[8] Ehrhart M, Lienhart W. Object Tracking with Robotic Total Stations: Current Technologies and Improvements Based on Image Data. Journal of Applied Geodesy, 2017, 113131142.

[9] Fang Q, Zhang D L, Wong L N Y. Environmental Risk Management for a Cross Interchange Subway Station Construction in China. Tunnelling and Underground Space Technology, 2011, 266750763.

[10] González C, Sagaseta C. Patterns of Soil Deformations around Tunnels. Application to the Extension of Madrid Metro. Computers and Geotechnics, 2001, 286/7445468.

[11] Guo C, Xu Q, Dong X J, et al. Geohazard Recognition and Inventory Mapping Using Airborne LiDAR Data in Complex Mountainous Areas. Journal of Earth Science, 2021, 32510791091.

[12] He G Z, Yang J. Deformation Monitoring for Subway Tunnels Based on TLS. Advanced Materials Research, 2013, 864/865/866/867: 2744-2749.

[13] Hencher S R. The Glendoe Tunnel Collapse in Scotland. Rock Mechanics and Rock Engineering, 2019, 521040334055.

[14] Huang M Q, Ninić J, Zhang Q B. BIM, Machine Learning and Computer Vision Techniques in Underground Construction: Current Status and Future Perspectives. Tunnelling and Underground Space Technology, 2021, 108: 103677.

[15] Jiang N, Li H B, Hu Y X, et al. A Monitoring Method Integrating Terrestrial Laser Scanning and Unmanned Aerial Vehicles for Different Landslide Deformation Patterns. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021, 14: 10242-10255.

[16] Jiao Y Y, Ye W T, Shen L Y, et al. How Does the New Generation of Information Technology Support the Urban Transparent Geology?. Journal of Earth Science, 2023, 3441312.

[17] Jin Z S, Yan Z H, Fu H R, et al. Machine Learning-Based Identification of Segment Joint Failure in Underground Tunnels. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2023, 381225420220170.

[18] Kaartinen E, Dunphy K, Sadhu A. LiDAR-Based Structural Health Monitoring: Applications in Civil Infrastructure Systems. Sensors, 2022, 22124610.

[19] Kavvadas M J. Monitoring Ground Deformation in Tunnelling: Current Practice in Transportation Tunnels. Engineering Geology, 2005, 791/293113.

[20] Kontogianni V A, Stiros S C. Induced Deformation during Tunnel Excavation: Evidence from Geodetic Monitoring. Engineering Geology, 2005, 791/2115126.

[21] Kovačević M S, Bačić M, Gavin K, et al. Assessment of Long-Term Deformation of a Tunnel in Soft Rock by Utilizing Particle Swarm Optimized Neural Network. Tunnelling and Underground Space Technology, 2021, 110: 103838.

[22] Lai J X, Qiu J L, Feng Z H, et al. Prediction of Soil Deformation in Tunnelling Using Artificial Neural Networks. Computational Intelligence and Neuroscience, 2016, 2016: 6708183.

[23] Li C, Lu X P, Zhu N N, et al. Continuously Extracting Section and Deformation Analysis for Subway Tunnel Based on LIDAR Points. Acta Geodaetica et Cartographica Sinica, 2015, 44910561062(in Chinese with English Abstract)

[24] Li H L, Xu G, Gui X, et al. An FBG Displacement Sensor in Deformation Monitoring of Subway Floating Slab. IEEE Sensors Journal, 2021, 21329632971.

[25] Li J, Wan Y, Gao X. A New Approach for Subway Tunnel Deformation Monitoring: High-Resolution Terrestrial Laser Scanning. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012, XXXIX-B5: 223-228.

[26] Li S J, Zhao H B, Ru Z L. Deformation Prediction of Tunnel Surrounding Rock Mass Using CPSO-SVM Model. Journal of Central South University, 2012, 191133113319.

[27] Li Y Y, Jin X G, Lyu Z T, et al. Deformation and Mechanical Characteristics of Tunnel Lining in Tunnel Intersection between Subway Station Tunnel and Construction Tunnel. Tunnelling and Underground Space Technology, 2016, 56: 22-33.

[28] Liu C, Liu Y H, Chen Y H, et al. A State-of-the-Practice Review of Three-Dimensional Laser Scanning Technology for Tunnel Distress Monitoring. Journal of Performance of Constructed Facilities, 2023, 37203123001.

[29] Lo K, Ramsay J. The Effect of Construction on Existing Subway Tunnels—A Case Study from Toronto. Tunnelling and Underground Space Technology, 1991, 63287297.

[30] Lueprasert P, Jongpradist P, Jongpradist P, et al. Numerical Investigation of Tunnel Deformation Due to Adjacent Loaded Pile and Pile-Soil-Tunnel Interaction. Tunnelling and Underground Space Technology, 2017, 70: 166-181.

[31] Luo Y B, Chen J X, Xi W Z, et al. Analysis of Tunnel Displacement Accuracy with Total Station. Measurement, 2016, 83: 29-37.

[32] Palazzo D, Friedmann R, Nadal C, et al. Dynamic Monitoring of Structures Using a Robotic Total Station. Proceedings of the Shaping the Change XXIII FIG Congress, October 8–13, 2006, 2006

[33] Protopapadakis E, Stentoumis C, Doulamis N, et al. Autonomous Robotic Inspection in Tunnels. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016, III-5: 167-174.

[34] Qiu Z R, Li H P, Hu W C, et al. Real-Time Tunnel Deformation Monitoring Technology Based on Laser and Machine Vision. Applied Sciences, 2018, 8122579.

[35] Scherer M, Lerma J L. From the Conventional Total Station to the Prospective Image Assisted Photogrammetric Scanning Total Station: Comprehensive Review. Journal of Surveying Engineering, 2009, 1354173178.

[36] Shi C H, Cao C Y, Lei M F, et al. Effects of Lateral Unloading on the Mechanical and Deformation Performance of Shield Tunnel Segment Joints. Tunnelling and Underground Space Technology, 2016, 51: 175-188.

[37] Singh B, Kumar R, Singh V P. Reinforcement Learning in Robotic Applications: A Comprehensive Survey. Artificial Intelligence Review, 2022, 552945990.

[38] Su Y, Su Y H, Zhao M H, et al. Tunnel Stability Analysis in Weak Rocks Using the Convergence Confinement Method. Rock Mechanics and Rock Engineering, 2021, 542559582.

[39] Tian X X, Song Z P, Zhang Y W. Monitoring and Reinforcement of Landslide Induced by Tunnel Excavation: A Case Study from Xiamaixi Tunnel. Tunnelling and Underground Space Technology, 2021, 110: 103796.

[40] Wang H Q, Feng G C, Xu B, et al. Deriving Spatio-Temporal Development of Ground Subsidence Due to Subway Construction and Operation in Delta Regions with PS-InSAR Data: A Case Study in Guangzhou, China. Remote Sensing, 2017, 9101004.

[41] Wang L X, Xu S S, Qiu J L, et al. Automatic Monitoring System in Underground Engineering Construction: Review and Prospect. Advances in Civil Engineering, 2020, 2020: 3697253.

[42] Wang R, Yang M S, Dong J, et al. Investigating Deformation along Metro Lines in Coastal Cities Considering Different Structures with InSAR and SBM Analyses. International Journal of Applied Earth Observation and Geoinformation, 2022, 115: 103099.

[43] Wang X, Shi B, Wei G Q, et al. Monitoring the Behavior of Segment Joints in a Shield Tunnel Using Distributed Fiber Optic Sensors. Structural Control and Health Monitoring, 2018, 251e2056.

[44] Xie X Y, Lu X Z. Development of a 3D Modeling Algorithm for Tunnel Deformation Monitoring Based on Terrestrial Laser Scanning. Underground Space, 2017, 211629.

[45] Xue X L, Zhang R X, Zhang X L, et al. Environmental and Social Challenges for Urban Subway Construction: An Empirical Study in China. International Journal of Project Management, 2015, 333576588.

[46] Yang S, Zhou K, Qiu D, et al. 3D Deformation Monitoring of Subway Tunnel. Geotechnical Aspects of Underground Construction in Soft Ground, 2008, Boca Raton: CRC Press

[47] Zhang G H, Jiao Y Y, Chen L B, et al. Analytical Model for Assessing Collapse Risk during Mountain Tunnel Construction. Canadian Geotechnical Journal, 2016, 532326342.

[48] Zhang Z G, Pan Y T, Zhang M X, et al. Complex Variable Analytical Prediction for Ground Deformation and Lining Responses Due to Shield Tunneling Considering Groundwater Level Variation in Clays. Computers and Geotechnics, 2020, 120: 103443.

[49] Zhao C Y, Lei M F, Jia C J, et al. Asymmetric Large Deformation of Tunnel Induced by Groundwater in Carbonaceous Shale. Bulletin of Engineering Geology and the Environment, 2022, 817260.

[50] Zhou J G, Xiao H L, Jiang W W, et al. Automatic Subway Tunnel Displacement Monitoring Using Robotic Total Station. Measurement, 2020, 151: 107251.

[51] Zhou X P, Sun M. Study on Accuracy Measure of Trigonometric Leveling. Applied Mechanics and Materials, 2013, 329: 373-377.

[52] Zhu F G, Xu D S, Tan R S, et al. Development of Optic-Electric Hybrid Sensors for the Real-Time Intelligent Monitoring of Subway Tunnels. Journal of Sensors, 2021, 2021: 8871893.

[53] Zhu H H, Wang D Y, Shi B, et al. Performance Monitoring of a Curved Shield Tunnel during Adjacent Excavations Using a Fiber Optic Nervous Sensing System. Tunnelling and Underground Space Technology, 2022, 124: 104483.

Rights & permissions

China University of Geosciences (Wuhan) and Springer-Verlag GmbH Germany, Part of Springer Nature