GU Hairong,LUO Jia,GAO Ziyu,et al. 3D model reconstruction of large-diameter rescue well based on depth camera[J]. Coal Geology & Exploration,2023,51(5):188−197. DOI: 10.12363/issn.1001-1986.22.10.0765
Citation: GU Hairong,LUO Jia,GAO Ziyu,et al. 3D model reconstruction of large-diameter rescue well based on depth camera[J]. Coal Geology & Exploration,2023,51(5):188−197. DOI: 10.12363/issn.1001-1986.22.10.0765

3D model reconstruction of large-diameter rescue well based on depth camera

  • Large-diameter borehole rescue is an effective emergency rescue method for mine disasters. Through the large-diameter rescue well that is constructed to the place where the trapped personnel is located, the trapped personnel can be lifted safely and reliably to the ground by a hoisting capsule. The structural parameters of a large-diameter rescue well and their changes have significant impact on the passing performance of the hoisting capsule. The real-time acquisition of the structural parameters of large-diameter rescue well is the basis of scientific operation and decision-making of large-diameter borehole rescue. In order to satisfy the requirements for monitoring of the structural parameters of large-diameter rescue well, the structural parameter detection and 3D model reconstruction system of large-diameter rescue well was developed based on the Interl RealSense D435i depth camera in the principle of binocular structured light and ROS operation system. To solve the problem that the texture of large-diameter rescue well is smooth and not noticeable, the SIFT, SURF and ORB algorithms were compared and analyzed in terms of the borehole image feature point extraction effect of large-diameter rescue well. Besides, the pose of depth camera was estimated with the ICP-PNP algorithm, and the key frames were screened according to the motion errors between adjacent frames, so as to optimize the 3D point cloud model. Finally, the 3D remodeling test of the large-diameter rescue well was carried out based on the simulation test platform of the lifting process in the large-diameter rescue well. The research results show that: The SURF algorithm has better effect on feature point extraction in the same time when the wellbore texture is not noticeable. The 3D model of large-diameter rescue well can be constructed stably by screening the key frame images according to the motion errors between adjacent frames. The cross-section sampling was performed on the 3D point cloud model of the large-diameter rescue well, showing that the error is within 2% from the actual wellbore radius. In addition, the sampled section of the 3D point cloud model of the large-diameter rescue well was fitted to the circle with the least square circle method, which indicates the error between the fitted circle and the actual wellbore radius is less than 0.4%. The reconstructed 3D model of large-diameter rescue well could accurately reflect the structural parameters of the actual large-diameter rescue well and guarantee the scientific operation and decision-making of surface emergency rescue lifting.
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