Tunnel-YOLO: An improved You Only Look Once algorithm for real-time shield tunnel lining leakage detection

Detecting crack leakages in shield tunnels is crucial for ensuring structural safety and extending service life, as traditional detection methods are limited by high subjectivity and low accuracy. To address these limitations, this paper proposes Tunnel-YOLO, an improved object detection algorithm based on You Only Look Once version 8 (YOLOv8). This algorithm replaces standard convolutional blocks with a novel Receptive Field Channel Attention Convolution (RFCAConv) module, which leverages dynamic receptive fields to enhance feature capture at different scales. We also introduce a C2f_SGE module, integrating the Spatial Group-wise Enhance (SGE) attention mechanism into the C2f (CSPNet with 2 convolutions) block to significantly improve feature extraction while suppressing background interference. Furthermore, an Edge Feature Enhancement Detection Head (EFE-Head) incorporates deconvolution layers to enhance fine-grained details for more precise boundary localization. To better accommodate the shape-sensitive detection task, our LeShape-IoU (Intersection over Union) loss function is designed to focus on the shape and scale characteristics of target bounding boxes. Experimental results on a public, real-world dataset demonstrate that Tunnel-YOLO significantly outperforms the baseline, increasing Recall, Precision, and mean Average Precision at 0.5 IoU (mAP50) by 15.7%, 10.3%, and 14.8%, respectively. Comparative analysis with other mainstream algorithms further validates the effectiveness and superiority of the proposed Tunnel-YOLO. • AI-based object detection replaces manual inspection for tunnel leakage detection. • Propose Tunnel-YOLO, an improved YOLOv8 for real-time leakage area detection. • Integrate novel attention mechanisms to handle multi-scale targets and noise. • A novel edge feature enhancement head improves localization of fine details. • Extensive experiments validate the superiority of the proposed Tunnel-YOLO model.