基于智能视觉的铁路大桥人员入侵防护系统设计研究  

Intelligent vision based personnel intrusion prevention system for railway bridge

作　　者：潘东亮 PAN Dongliang(Technology Information Department,CHN ENERGY Baoshen Railway Group Limited Liability Company,Baotou 014010,China)

机构地区：[1]国能包神铁路集团有限责任公司科技信息部,包头014010

出　　处：《铁路计算机应用》2023年第9期48-53,共6页Railway Computer Application

基　　金：国家能源集团科技项目(GJNY-20-242)。

摘　　要：铁路桥梁监测是保障铁路运输安全的重要手段。为提升现有监测系统对铁路大桥人员入侵的检测能力,设计了基于智能视觉的铁路大桥人员入侵防护系统,该系统由视频平台、智能视觉平台及业务管理平台组成。采用YOLOv5目标检测模型进行人员入侵检测;同时,采用多种图像数据增强技术,扩增训练数据集,进一步提升目标检测模型的泛化能力和场景适应能力。在包神铁路集团有限公司万南站区黄河大桥对该系统进行了部署和测试。测试结果表明,该系统对人员入侵检测的准确率为95.3%,检测实时性为2 ms;人员入侵检测的准确率与实时性均满足实际应用要求。Railway bridge monitoring is an important means to ensure transportation safety.To enhance the detection capability of existing monitoring systems for railway bridge personnel intrusion,this paper designed a personnel intrusion prevention system for railway bridge that included a video platform,an intelligent visual platform,and a business management platform.The paper adopted the YOLOv5 object detection model for personnel intrusion detection,and adopted multiple image data enhancement technologies to expand the training dataset,further improve the generalization ability and scene adaptation ability of the object detection model.The system was deployed and tested at the Yellow River Bridge in the Wannan Station area of Baoshen Railway Group Limited Liability Company.The experimental results show that the detection accuracy of the system for personnel intrusion is 95.3%,and the realtime detection performance is 2 ms.The accuracy and real-time performance of personnel intrusion detection meet the practical application requirements.

关 键 词：铁路大桥 人员入侵防护系统 智能视觉 目标检测模型 光学相机 

分 类 号：U24[交通运输工程—道路与铁道工程]