Bulletin of Surveying and Mapping ›› 2021, Vol. 0 ›› Issue (10): 54-59.doi: 10.13474/j.cnki.11-2246.2021.305

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3D laser scanning point cloud analysis method for dam deformation monitoring

YANG Chuanxun1,2,3,4,5, YANG Ji3,4,5, LI Yong3,4,5, HAN Liusheng6, CHEN Shuisen3,4,5   

  1. 1. Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Guangdong Remote Sensing and GIS Application Laboratory, Guangzhou 510070, China;
    4. Guangdong Public Laboratory of Geospatial Information Technology and Application, Guangzhou 510070, China;
    5. Guangzhou Institute of Geography, Guangzhou 510070, China;
    6. Shandong University of Technology, Zibo 255000, China
  • Received:2020-10-19 Revised:2021-07-28 Published:2021-11-13

Abstract: Deformation monitoring is an important part in dam safety monitoring. With the development of 3D laser point cloud technology, it is a trend to use this kind of tech in dam deformation monitoring, but the current algorithm constraints and data processing uncertainty errors greatly affect the monitoring accuracy. Based on this research, a point cloud data registration algorithm based on normal distribution, improved original progressive encryption triangulation filter algorithm, and point-to-face variable comparison analysis mode are used to monitor dam-shaped variables, and source program development is realized. Monitor point cloud data processing, comparative analysis, and modeling processing.The results show that:①The improved algorithm has high efficiency and excellent precision, and is suitable for dam point cloud data processing and comparative analysis. ②The developed point cloud data integration processing software is simple and easy to use, and can accurately reflect the deformation of the dam. ③Huanglongdai dam is stable, there is no safety hazard.

Key words: reservoir dam, deformation monitoring, 3D laser scanning, point cloud data registration, progressive encryption triangulation filtering

CLC Number: