线路-YOLO:一种高效的电力线路角度检测算法
Chuanjiang Wang1, Yuqing Chen1, Zecong Wu2
1College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao 266590, China.
Sensors (Basel, Switzerland)
|February 13, 2025
概括
这项研究介绍了Line-YOLO,这是一种改进的电力线倾斜角度检测算法. 与传统方法相比,它提高了准确性和效率,同时减少了与传统方法相比的错误和工作量.
科学领域:
- 计算机视觉 计算机视觉
- 人工智能的人工智能
- 电气工程 电气工程
背景情况:
- 手动电力线倾斜角度检测是劳动密集型的,容易出现错误.
- 现有的自动化方法与可变的电力线形状和阻塞作斗争.
研究的目的:
- 开发一套高效准确的自动化系统,用于电力线倾斜角度检测.
- 改进现有的对象检测模型,用于电力线路检查任务.
主要方法:
- 一个改进的算法,Line-YOLO,基于YOLOv8s-seg被开发.
- 引入可变形卷积式DCNv4,以处理可变电源线形状.
- 集成的BiFPN用于高效的特征融合,以及EMA的注意力用于改进目标识别,特别是在重叠的电力线上.
- 添加了一个小目标检测头来解决小或封闭目标的检测.
主要成果:
- 与基准模型相比,Line-YOLO在mAP@0.5实现了6.2%的改进.
- 将参数数量减少了28.2%,并提高了每秒浮点运算的35.3%.
- 每秒检测到的数增加了14 FPS,证明了效率的提高.
结论:
- 增强的Line-YOLO模型显著提高了电力线倾斜角度任务的检测精度和效率.
- 该算法有效地解决了诸如可变形状,目标重叠和小/隐蔽目标等挑战.
- Line-YOLO为自动化电力线路检查提供了强大而高效的解决方案.
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