ISSN 1004-4140
CN 11-3017/P
Volume 31 Issue 2
Mar.  2022
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Abstract
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WANG D X, ZHANG X X, CHEN W X, et al. Comprehensive disease identification and 3D geological modeling of rock mass based on elastic wave CT and GPR[J]. CT Theory and Applications, 2022, 31(2): 149-162. DOI: 10.15953/j.1004-4140.2022.31.02.02. (in Chinese).
Citation: WANG D X, ZHANG X X, CHEN W X, et al. Comprehensive disease identification and 3D geological modeling of rock mass based on elastic wave CT and GPR[J]. CT Theory and Applications, 2022, 31(2): 149-162. DOI: 10.15953/j.1004-4140.2022.31.02.02. (in Chinese).
shu

Comprehensive Disease Identification and 3D Geological Modeling of Rock Mass Based on Elastic Wave CT and GPR

  • 1.

    Xuzhou Urban Rail Transit Co., Ltd, Xuzhou 221018, China

  • 2.

    The State Key Laboratory for Geomechanics and Deep Underground Engineering/School of mechanics and civil engineering, CUMT, Xuzhou 221116, China

  • 3.

    School of resources and Earth Sciences, CUMT, Xuzhou 221116, China

More Information
  • Received Date: August 25, 2021
  • Available Online: November 17, 2021
  • Published Date: March 31, 2022
    Graphical Abstract
    • Abstract
  • Taking the rock slope of the subway deep foundation pit as the research object, elastic wave CT is used to preliminarily judge the type and spatial distribution of rock mass diseases in foundation pit, which is then verified by geological radar. Furtherly the a watershed algorithm is adopted to analyze the wave velocity distribution obtained by elastic wave CT in order to extract the detailed sound velocity change at the rock cave and delineate its range. On this basis, based on the coordinate information of elastic wave CT three-dimensional spatial wave velocity database, combined with the spatial coordinate information obtained by watershed algorithm, the modeling database is constructed, after imported into GOCAD software, the three-dimensional geological visualization model is established after processing and analysis. The rock mass disease model established in this paper is highly consistent with geological drilling, peephole imaging and field observation. The proposed rock disease identification method and modeling technology can not only provide an important reference for rock mass support but also provide a basis for water disaster prevention of urban underground engineering.
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    • References (16)
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