铁道科学与工程学报2024，Vol.21Issue(12)：5252-5263,12.DOI:10.19713/j.cnki.43-1423/u.T20240302
基于MLS点云的多尺度盾构隧道渗水病害检测网络
Multi-scale shield tunnel water leakage detection network based on mobile laser scanning point clouds
摘要
Abstract
In shield tunnels,water leakage often leads to short circuits in electrical systems,equipment corrosion,and structural deterioration.However,existing water leakage technologies are detected with low intelligence.Moreover,the precision and efficiency are insufficient to meet the requirements of shield safety monitoring.Therefore,this paper proposed an intelligent water leakage detection method based on point cloud intensity images.First,mobile laser scanning equipment was used to collect three-dimensional point cloud data in tunnel conditions with low light.In addition,a water leakage dataset was constructed and annotated.Then,a high-performance target detection network was designed to detect multi-scale water leakage regions.This network integrated a reconfigurable contextual information fusion module,which is specifically designed for handling multi-scale water leakage information.Then,a hard example mining loss function was explored for water leakage to enhance the capability to detect multi-scale and challenging targets.Moreover,an improved lightweight header structure was used to reduce the size and complexity of the model.Finally,through training and testing on the water leakage dataset,experimental results showed that the model achieved a high water leakage recognition rate of 93.59%,with an increase of 3.69%in the AP index compared to the original model.Additionally,the improved model reduced computational workload by 47.15%.Ablation experiments and comparative experiments further showed that the effectiveness of the proposed method is better than that of the comparison methods.Overall,this method significantly improved the efficiency and accuracy of detecting water leakage.It can be used for safety monitoring in shield tunnels.关键词
盾构隧道/渗水检测/移动激光扫描/目标检测/YOLOv8Key words
shield tunnel/water leakage detection/mobile laser scanning/object detection/YOLOv8分类
交通工程引用本文复制引用
刘振宇,高贤君,杨元维,王少宁,许磊,于盛妍,寇媛,刘波..基于MLS点云的多尺度盾构隧道渗水病害检测网络[J].铁道科学与工程学报,2024,21(12):5252-5263,12.基金项目
城市轨道交通数字化建设与测评技术国家工程实验室开放课题基金资助项目(2023ZH01) （2023ZH01）
自然资源部环鄱阳湖区域矿山环境监测与治理重点实验室开放基金资助项目(MEMI-2021-2022-08) （MEMI-2021-2022-08）
天津市科技计划项目(23YFYSHZ00190,23YFZCSN00280) （23YFYSHZ00190,23YFZCSN00280）
湖南省自然科学基金项目部门联合基金资助项目(2024JJ8327) （2024JJ8327）
江西省自然科学基金资助项目(20232ACB204032) （20232ACB204032）
