Location and rapid detection method of water leakage in subway tunnels based on mobile laser scanning
Water leakage is one of the most important diseases in subway tunnels and can also cause other structural diseases.It is of great significance to carry out research on detection methods of water leakage diseases in subway tunnels.This paper focu-ses on the problem of water leakage in subway tunnels and proposes a water leakage location and detection method based on mobile laser scanning point cloud data.First,combined with the mobile laser scanning detection method,research on the pre-cise positioning method of tunnels was carried out.Then,the YOLOv7 model was improved,and the ConvNeXt network and CBAM module were introduced to enable the model to better capture multi-scale,multi-abstraction level features and enhance attention to the key features of seepage water.The GIoU Loss function was used to make the model can better handle incom-plete leaky water boxes.It uses the Soft-NMS weighted average method when predicting to retain more bounding boxes,there-by improving detection accuracy.The efficiency and robustness of the method in this paper are verified by combining the shield method and mine method tunnel leakage data sets constructed with laser scanning data obtained in Chongqing metro.The abla-tion test shows that compared with the baseline model,the method in this paper has achieved significant performance improve-ments on different data sets.In the shield method data set,the precision rate P is increased by 8.1％,and the recall rate R is increased by 4％.In the mining law data set,the precision rate P increased by 8.6％,and the recall rate R increased by 6.8％.At the same time,compared with the mainstream target detection algorithms faster RCNN(Swin),faster RCNN(ConvNeXt),and YOLOv8,this method shows advantages in both accuracy and speed.Finally,this paper shows the location and detection results of water leakage in some tunnels to verify the practicability of this method.
laser point cloudtunnel localizationshield methodmine methodleakage detectionattention mechanism
NETL
NSTL
万方数据
