Extraction Method of Cavern Surface Deformation Region Based on Alpha Shapes Contour Point Cloud Recognition Algorithm
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School of Earth Sciences and Engineering, Hohai University

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    Abstract:

    Aiming at the problem of extracting cavern surface deformation by three-dimensional laser scanning dense point clouds, a method of cavern surface deformation monitoring based on Multiscale Model-to-Model Cloud Comparison(M3C2) and improved Alpha Shapes algorithm is proposed. Firstly, the two phase surface point cloud data are registered, and the improved Alpha Shapes algorithm is used to identify the outer contour point cloud. After the fine registration of the two phase outer contour point clouds, the M3C2 algorithm is used to calculate the deformation value of each point, and finally the continuous deformation region is extracted by distance clustering. The experimental results show that the proposed method can effectively eliminate the points at the small furrows and the points affected by the mixed pixels. The removal rates of the point cloud in the two phases are 14.17% and 13.52% within 10m of the cavern section to the scanner, respectively, 6.25% and 6.42% within 70m. This method can accurately and efficiently extract the deformation region of the cavern surface with more than 2 times the registration error.

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History
  • Received:May 13,2024
  • Revised:June 19,2024
  • Adopted:June 20,2024
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