کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8915823 | 1641743 | 2018 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Automated measurements of discontinuity geometric properties from a 3D-point cloud based on a modified region growing algorithm
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
مهندسی ژئوتکنیک و زمین شناسی مهندسی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Automated measurements of discontinuity geometric properties from a 3D-point cloud based on a modified region growing algorithm Automated measurements of discontinuity geometric properties from a 3D-point cloud based on a modified region growing algorithm](/preview/png/8915823.png)
چکیده انگلیسی
An approach was proposed to automatically measure the discontinuity geometric properties from a point cloud acquired using Light Detection and Ranging (LiDAR). The procedure primarily includes the following features: (Assali et al., 2016) Grid data from the point cloud was created to enhance computational efficiency for data processing and retrieval; (Barton & Choubey, 1977) A modified region growing (MRG) algorithm, which is characterized by more efficient grow criterion, was used to recognize discontinuities from the point cloud; (Cao et al., 2017) Four geometric properties from identified discontinuities were calculated based on analytic geometry; (Chen et al., 2016) Influence of threshold T on the identified results was investigated through sensitivity analysis, and threshold T was suggested to be less than the minimum normal difference among all joints and larger than 0°. Two cases (regular polyhedrons and a tunnel in the Rumei hydropower station) were taken as case studies to validate the developed approach, and calculation results have good agreement with real situations.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Geology - Volume 242, 14 August 2018, Pages 44-54
Journal: Engineering Geology - Volume 242, 14 August 2018, Pages 44-54
نویسندگان
Yunfeng Ge, Huiming Tang, Ding Xia, Liangqing Wang, Binbin Zhao, Jenkins Wholda Teaway, Hongzhi Chen, Ting Zhou,