Intelligent Detection of Water Leakage in Railway Tunnel Based on YOLOv8
The water leakage of railroad tunnel will affect the structural stability and operational safety of the tunnel,and the automated detection of water leakage defect needs to be solved urgently.The traditional manual inspection method is lower in automation and detection efficiency,and is prone to errors and omissions,which cannot meet the demand of rapid detection of large-scale tunnels.To solve this problem,a YOLOv8 network-based intelligent water leakage detection method for railroad tunnels is proposed,and the model training and parameter tuning are carried out in a self-constructed water leakage dataset of railroad tunnels.The experimental results show that the YOLOv8-n network has the best overall performance among the different versions of the model experiments.In the com-parison experiments of different models,the F1 score and AP of the YOLOv8 model are 81.28%and 81.38%,respectively,which are 6.85%and 6.89%,9.40%and 8.19%,12.19%and 10.57%high-er compared to the YOLOv7,YOLOv5,and SSD models,respectively.The comprehensive analysis shows that the YOLOv8 model has the best overall performance and is suitable for water leakage de-tection task in railroad tunnel projects.
railway tunneltunnel water leakagedeep learningtarget detection
万方数据
维普
