摘要
道路边坡在运行期容易产生道路滑坡等表观病险,对道路的正常运维产生不良影响。三维激光扫描技术具有范围广、无接触的特点,采用三维激光扫描技术获取边坡病险点云数据已经成为新兴的道路病害检测手段。通过系统的室内试验模拟道路边坡滑坡工况,研究了滑坡点云数据的三维特征,提出了适用于道路滑坡病险特征的点云特征识别的方法,并基于室内模型试验数据验证了方法的可行性,该方法简单便捷,坡长度识别准确率超过95%。
Road slopes are susceptible to road landslides and other apparent hazards during the operation period.The use of 3D laser scanning technology to obtain point cloud data of slope hazards has become an emerging means of road disease detection.In this paper,the three-dimensional features of landslide point cloud data are studied by simulating the landslide conditions of road slopes through an indoor model test,and a method of point cloud feature recognition applicable to the characteristics of road landslides is proposed,and the feasibility of the method is verified by using the data from the indoor model test.
作者
刘泰鑫
周立志
王子煜
鲁冠宏
牛沛
Liu Taixin;Zhou Lizhi;Wang Ziyu;Lu Guanhong;Niu Pei(Shandong University School of Qilu Transportations,Jinan Shandong 250002,China)
出处
《山西建筑》
2024年第12期127-130,共4页
Shanxi Architecture
基金
山东省自然科学基金青年基金(No.ZR2021QE279)。
关键词
滑坡
点云分割
特征识别
激光点云
landslide
point cloud segmentation
feature recognition
laser point cloud
