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INTELLIGENT DAM MANAGEMENT SYSTEM BASED ON DIGITAL TWIN

机译:基于数字双单的智能大坝管理系统

摘要

The present invention relates to a dam safety management system, and more specifically, to a digital twin-based intelligent dam safety management system that can significantly improve speed, accuracy, and efficiency through technological advancement of dam infrastructure safety inspection and facility management. will be. To this end, the present invention builds a 3D dam modeling based on an image captured by at least one of a drone and a photographing means for a dam in which a measuring means is installed in a facility, and subdivides the 3D dam modeling for each management area unit, 3D a digital twin generation module for displaying at least one of facility information and measurement information of a measurement means on the dam modeling; The flight path information is stored for each management area unit and the image taken by a drone equipped with a thermal imaging camera is mapped to the 3D dam modeling, and the 3D dam modeling before and after the mapping is compared and expressed while leaking or leaking the dam through the thermal image orthographic image. a 3D modeling mapping module that enables confirmation of white changes; and a concrete crack identification module for determining concrete cracks by analyzing the dam concrete structure image taken by the drone in a deep learning method.
机译:本发明涉及大坝安全管理系统,更具体地,涉及一种数字双胞胎智能大坝安全管理系统,可以通过大坝基础设施安全检测和设施管理的技术进步,显着提高速度,准确性和效率。将会。为此,本发明基于由无人机和拍摄装置捕获的图像来构建3D坝建模,其中用于将测量装置安装在设施中的大坝,并且为每个阻塞装置进行细分3D水坝建模管理区域单元,3D数字双代模块,用于显示水坝建模上的测量装置的至少一个设施信息和测量信息;飞行路径信息存储为每个管理区域单元,并且由配备有热成像相机的无人机拍摄的图像映射到3D坝建模,并在泄漏或泄漏之前和在映射之前和之后进行3D水坝建模大坝通过热图像正交图像。 3D建模映射模块,可实现白色变化;和一个混凝土裂缝识别模块,用于通过分析无人机在深度学习方法中拍摄的坝混凝土结构图像来确定混凝土裂缝。

著录项

  • 公开/公告号KR20210115245A

    专利类型

  • 公开/公告日2021-09-27

    原文格式PDF

  • 申请/专利权人 이용;

    申请/专利号KR20200030739

  • 发明设计人 이용;

    申请日2020-03-12

  • 分类号G06Q50/10;B64C39/02;B64D47/08;G02B27/01;G06K9/62;G06N20;G06N3/08;G06Q10/04;G06T17/10;G06T7;H04N5/33;

  • 国家 KR

  • 入库时间 2022-08-24 21:17:57

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