Fast Intrusion Detection in High Voltage Zone of Electric Power Operations Based on YOLO and Homography Transformation Algorithm

Ting Xie, Wenxun Zhang
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Abstract

The high voltage zone of electric power is a typical high-risk work area. It is harm to the safety of operators and maintainers especially in the case of leakage and arcing. It is especially important for the electrical power safety to track the worker’s inspection, monitor the operation behavior and follow the current position. The complicated environment limited the application of monitoring instruments. This paper proposes an operator positioning method in high voltage zone based on the CNN method. Firstly, a homography transformation algorithm is used to transfer the 2D and 3D scenes to enhance detection accuracy. Secondly, a graph sequence detecting method based on YOLO is used on the purpose of fast detection. Finally, a trajectory prediction and tracking method is proposed for the early warning. The onsite testing results show the precision and speed of proposed method compared with existing method.
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基于YOLO和单应性变换算法的电力运行高压区快速入侵检测
电力高压区是典型的高危作业区域。特别是在发生漏电和电弧的情况下,对操作人员和维护人员的安全造成危害。跟踪工人的检查情况,监控操作行为,跟踪当前位置,对电力安全尤为重要。复杂的环境限制了监测仪器的应用。本文提出了一种基于CNN方法的高压区操作员定位方法。首先,采用单应变换算法对二维场景和三维场景进行转换,提高检测精度;其次,为了快速检测,采用了基于YOLO的图序列检测方法。最后,提出了一种用于预警的轨迹预测与跟踪方法。现场测试结果表明,与现有方法相比,该方法精度高、速度快。
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