北京交通大学学报2025，Vol.49Issue(3)：44-55,12.DOI:10.11860/j.issn.1673-0291.20240091
基于改进YOLOv5s的钢轨轨端检测算法
An algorithm for detecting the end of railway tracks based on the improved YOLOv5s
摘要
Abstract
In response to the problem that the on-board personnel monitoring the rail end of the steel rail transportation train have difficulty in judging whether the rail has detached from the fastening de-vice in a timely manner,a rail end detection algorithm based on the improved YOLOv5s is proposed.Firstly,the lightweight GhostNet backbone network is adopted to replace the original Cross Stage Par-tial Network(CSPNet),reducing the high requirements of the model for hardware resources;Sec-ondly,BiFomer and Receptive-Field Attention(RFA)attention mechanism are added to weaken the irrelevant background regions while improving the positioning ability of the rail end;Thirdly,the loss function SIoU is used to replace the original CIoU,enhancing the generalization ability of the model,and enabling the model to converge faster.Finally,the algorithm is verified and evaluated from the as-pects of detection accuracy and detection speed,and compared with algorithms such as Single Shot MultiBox Detector(SSD)and YOLOv8.The research results show that the improved detection algo-rithm achieves an average detection accuracy of 91.7％for the rail end detection,with an average de-tection time of 24 ms,which is 5.3％higher than the original YOLOv5s model.The missed detection and false detection situations have been significantly improved.The improved algorithm can achieve precise detection of the rail end in different environments,has good adaptability in adverse environ-ments such as dim lighting,and has a lower floating-point operation per second,which can be de-ployed in the embedded device RK3399 to better meet the real-time detection requirements of the rail end.关键词
计算机视觉/注意力机制/深度学习/YOLOv5s/RK3399Key words
computer vision/attention mechanism/deep learning/YOLOv5s/RK3399分类
信息技术与安全科学引用本文复制引用
耿豪,李绍斌,盛雪清..基于改进YOLOv5s的钢轨轨端检测算法[J].北京交通大学学报,2025,49(3):44-55,12.基金项目
国家自然科学基金(61771041)National Natural Science Foundation of China(61771041) （61771041）
