With the advancement of modern surveying and mapping technology,point cloud data has become an indispensable tool in the health monitoring of tunnels.A segmentation and deformation detection method of tun-nels based on measured point cloud data is proposed for large-scale energy transmission tunnels such as the west-east gas pipeline.Firstly,by a segmentation strategy which combines with geometry and density,tunnel structures are accurately extracted from original point cloud data.Secondly,time series and feature detection strategies are used to achieve the accurate recognition of the slight deformation of tunnels.In addition,the machine learning method is introduced to further improve the accuracy and automation degree of deformation detection.Experimental results show that this method has high accuracy and stability in practical engineering applications,providing strong techni-cal support for the safe operation of tunnels.
关键词
点云数据/隧道健康监测/形变检测/机器学习/西气东输
Key words
Point cloud data/Tunnel health monitoring/Deformation detection/Machine learning/West-east gas transmission
维普
万方数据