基于机器视觉的滑坡体夜间不间断监测技术研究
Research on night-time uninterrupted monitoring technology for landslides based on machine vision
林泊锟 1李登华 2丁勇 1李元梦1
作者信息
- 1. 南京理工大学理学院,南京 210094
- 2. 南京水利科学研究院,南京 210024;水利部水库大坝安全重点实验室,南京 210024
- 折叠
摘要
为了提升对滑坡体险情的实时感知能力,提出了一种基于机器视觉的滑坡体夜间不间断监测技术,该技术通过提取夜间滑坡体特征物的位移,来监测滑坡体的局部变形情况:首先利用二值化方法提取滑坡体特征点阵;然后利用不同点阵的特征三角形对像素坐标系进行变换,实现特征点的匹配,并计算像素位移;最后基于单目测距原理将像素移动距离转换为实际距离,进而实现边坡的夜间不间断监测.试验结果表明,该技术在保持较高精度的同时,能够在夜间持续对滑坡体进行监测,可运用于实际工程中.
Abstract
A machine vision-based night-time uninterrupted monitoring technique for landslides is suggested in order to increase the capability of real-time detection of landslide dangers.By extracting the local displacement of landslide features at night,this method tracks the regional displacement of landslides.Firstly,the binarization method is used to extract the landslide feature point array;then,the feature triangles of different point arrays are used to trans-form the image coordinate system to achieve the matching of points and calculate the pixel displacement.Finally,the conversion of the pixel moving distance into the accurate distance using the principle of monocular distance measure-ment to realize slope night monitoring.The outdoor test results show that this technology can continuously monitor land-slides at night while maintaining high precision and can be applied in actual engineering.
关键词
滑坡体/夜间监测/特征物/位移Key words
landslide mass/night monitoring/features/displacement引用本文复制引用
基金项目
国家重点研发计划资助项目(2022YFC3005502)
国家自然科学基金资助项目(51979174)
国家自然科学基金联合基金(U2040221)
出版年
2024
NETL
NSTL
万方数据