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蔡檬屿, 郭旭, 王浩帆, 李良平, 张瀚文. 基于深度学习的铁路辅助巡检系统[J]. 铁路计算机应用, 2020, 29(9): 12-15.
引用本文: 蔡檬屿, 郭旭, 王浩帆, 李良平, 张瀚文. 基于深度学习的铁路辅助巡检系统[J]. 铁路计算机应用, 2020, 29(9): 12-15.
CAI Mengyu, GUO Xu, WANG Haofan, LI Liangping, ZHANG Hanwen. Aided inspection system of railway based on deep learning[J]. Railway Computer Application, 2020, 29(9): 12-15.
Citation: CAI Mengyu, GUO Xu, WANG Haofan, LI Liangping, ZHANG Hanwen. Aided inspection system of railway based on deep learning[J]. Railway Computer Application, 2020, 29(9): 12-15.

基于深度学习的铁路辅助巡检系统

Aided inspection system of railway based on deep learning

  • 摘要: 针对人工巡检方式错漏多、强度大、成本高的问题,设计基于深度学习和虚拟现实(VR)远程控制技术的铁路辅助巡检系统。该巡检系统结合开源数据集和定制数据集,采用深度学习算法,能可靠地识别异物位置与类别;采用服务器推流技术与终端进行数据交互,实现对远程设备的控制;客户段端采用VR+手机App技术,达到沉浸式视觉效果。多次实际测试结果表明:该系统实用性强,经济性好,准确率高,为铁路部门巡检体系提供良好的借鉴方案。

     

    Abstract: To address the problems of too many errors and omissions, high labor intensity and high cost in manual inspection, an aided inspection system for railway based on deep learning and VR remote control technology is designed. With the combination of open source datasets and customized datasets, the inspection system can identify the position and category of foreign objects reliably by adopting deep learning algorithms and uses server push stream technology to interact with the terminals to achieve control over remote devices. And VR + mobile App technology is used on the client to achieve immersive visual effects. The results of actual tests prove that the system is practical, economical, and accurate, providing a good solution as reference for the inspection system of railway.

     

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