计算机工程与应用2025，Vol.61Issue(6)：118-127,10.DOI:10.3778/j.issn.1002-8331.2408-0319
Leakage-YOLO:隧道场景下裂缝漏水的实时目标检测算法
Leakage-YOLO:Real-Time Object Detection Algorithm for Crack and Leakage in Tunnel Scenarios
摘要
Abstract
The detection of cracks and water leakage in tunnel shield linings is essential for ensuring the structural safety and extending the service life of tunnels.With the advancement of object detection technologies,advanced techniques have been increasingly applied to the automatic detection of cracks and leakage areas in tunnel shield linings to improve detection efficiency and precision.Therefore,to further improve the precision of detecting these areas and to achieve real-time detection,the Leakage-YOLO algorithm is proposed,based on YOLOv8.The algorithm introduces a regional spot-light attention(RSA)module into the detection neck,which better integrates global and local feature information,thereby enhancing the ability to extract key regional features.This effectively addresses the challenge of extracting significant features in crack and leakage areas.Additionally,by modifying the detection head,a novel SE-Head structure is proposed,further enhancing the ability to extract detailed edge features,effectively improving the precision of crack and leakage area localization.Experimental results on public datasets in real-world scenarios demonstrate that the improved algorithm out-performs the original algorithm with increases of 4.7,4.9,and 6.7 percentage points in AP,AP0.5,and AP0.75,respectively.Compared with other mainstream algorithms,the effectiveness and superiority of the Leakage-YOLO are further verified.关键词
隧道盾构裂缝漏水检测/Leakage-YOLO/注意力机制/关键区域特征Key words
tunnel shield crack and leakage detection/Leakage-YOLO/attention mechanism/key region feature分类
计算机与自动化引用本文复制引用
陈灿森,刘巍..Leakage-YOLO:隧道场景下裂缝漏水的实时目标检测算法[J].计算机工程与应用,2025,61(6):118-127,10.基金项目
国家自然科学基金面上项目(62073125). （62073125）
