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基于人工智能技术的铁路棚车顶锈蚀孔洞检测系统设计与实现

Artificial intelligence-based corrosion and hole detection system for railway box car roofs

  • 摘要: 为提高铁路棚车运输安全,设计了基于人工智能的铁路棚车顶锈蚀孔洞检测系统,阐述了该系统的总体架构与功能,实现了站场作业场景下车顶锈蚀孔洞的精准识别与实时预警;通过人工智能大模型协同、可视化展示等关键技术,实现了棚车顶锈蚀孔洞的高效识别与检测结果友好呈现。实验结果表明,与传统人工检测相比,该系统单帧检测速度提高了6倍,可实现棚车巡检全覆盖、无漏检,为铁路棚车运输安全提供了智能化技术支撑。

     

    Abstract: This paper designed an artificial intelligence-based corrosion and hole detection system for railway box car roofs to improve the transportation safety of railway box cars. It presented the overall architecture and functions of the system and achieved accurate identification and real-time early warning of box car roof corrosion and holes in station yard operation scenarios. Using key technologies such as artificial intelligence large model collaboration and visual display, this paper realized efficient detection of box car roof corrosion and holes as well as friendly presentation of detection results. Experimental results show that, compared with traditional manual inspection, the system improves the single-frame detection speed by six times, and achieves full coverage and zero miss in box car inspection, and provides intelligent technical support for the transportation safety of railway box cars.

     

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