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  Methodology and analysis for the automatic tunnel deformation detection based on 3D LiDAR point cloud

  The tunnel deformation monitoring methodology based on 3D LiDAR (Light Detection and Ranging) data shows broad application prospects in recent years due to the high- quality of acquired massive data. The proposed methodology provides a clear processing flow and comprehensive analysis result with adequate accuracy mainly by three parts: data acquisition, data processing and result analysis. Optimal scan parameters are derived in data acquisition to ensure the accuracy of scanned data. Then the acquired data will be processed automatically in data processing to get clean point cloud of every single tunnel segment without obvious noise from whole raw tunnel point cloud. Finally, the radial deformation graphs and nephogram are fitted and illustrated by result analysis. The efficient approach has been implemented in the tunnel of Shanghai Metro Line 11 and achieved satisfactory results with adequate accuracy.

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