摘要
针对现有土石坝渗漏检测方法常面临的设备布置繁琐与数据分析复杂等问题,提出一种基于无人机红外热成像技术的土石坝渗漏巡检方法,并结合自适应阈值分割和图像形态学处理等技术,构建一套智能化的基于红外图像的渗漏区域识别方法。为验证该方法的可行性,以金华市某水库为试验点,进行实际工程的渗漏巡检和识别,并使用并行电法予以验证。结果表明,该方法能够自动并准确地识别渗漏区域,能显著提升渗漏检测的效率和适应性,为土石坝渗漏巡检与识别问题提供一种可行的技术方法。
In response to the challenges often encountered in current rockfill dam leakage detection methods,such as intricate equipment setup and complex data analysis,this paper proposed a method based on UAV and infrared thermographic imaging.The method combines techniques such as adaptive threshold segmentation and image morphological processing to intelligently identify leakage areas based on infrared images.To validate the feasibility of the method,field leakage inspection and identification were conducted at a reservoir in Jinhua City,using the parallel electric method as a corroborative tool.The findings suggest that our proposed methodology can autonomously and accurately identify leakage zones,substantially enhancing the efficiency and adaptability of leakage detection.This offers a feasible solution to the challenges of leakage inspection and identification in rockfill dams.
作者
张锏
王浩军
刘旷
周华飞
ZHANG Jian;WANG Haojun;LIU Kuang;ZHOU Huafei(Zhejiang Design Institute of Water Conservancy&Hydro-Electric Power Co,Ltd.,Hangzhou 310002,Zhejiang,China;Zhejiang University of Technology,Hangzhou 310000,Zhejiang,China)
出处
《浙江水利科技》
2024年第2期60-66,共7页
Zhejiang Hydrotechnics
关键词
土石坝
渗漏
无人机遥感技术
红外热成像
图像处理
rockfill dam
leakage
unmanned aerial vehicle
infrared thermal imaging
image processing
