SCI-YOLO11:基于YOLO11的传输线绝缘体的改进缺陷检测算法
Junyan Wang1, Yuqian Wang2, Xun Li1
1Xijing University, Xi'an, Shaanxi, China.
PloS one
|October 29, 2025
概括
这项研究介绍了SCI-YOLO11,这是一个改进的算法,用于检测输电线路上的绝缘体缺陷. 新方法提高了小物体检测的准确性和稳定性,这对电力系统安全至关重要.
科学领域:
- 电气工程 电气工程
- 计算机视觉 计算机视觉
- 人工智能的人工智能
背景情况:
- 在输电线路中检测绝缘体缺陷对于电力系统安全至关重要.
- 由于复杂的背景和不一致的注释,小物体检测具有挑战性.
- 现有的方法在识别微妙缺陷时,在准确性和效率方面扎.
研究的目的:
- 提出一个优化的物体检测算法,SCI-YOLO11,用于改进绝缘体缺陷检测.
- 增强特征提取,注意力机制和损失功能,以提高性能.
- 为了解决目前检测小,低分辨率缺陷的方法的局限性.
主要方法:
- 在脊柱中用SPDConv模块取代传统的卷曲,以增强小目标特征捕获.
- 整合了SE注意力机制,以改善绝缘体缺陷的特征可分辨性.
- 整合了Wise-IoU-V3损失功能,以减轻标注质量不一致的问题.
主要成果:
- 与基线模型相比,SCI-YOLO11在MAP@0.5中取得了3.2%的改善.
- 精度和回忆率分别增加了2.6%和3.7%.
- 参数数量减少了6%,浮点操作减少了7.9%,这表明了轻量级的设计.
结论:
- SCI-YOLO11显著提高了绝缘体缺陷的检测准确度,稳定性和效率.
- 优化的框架为现实世界输电线路检查提供了实用解决方案.
- 这一进步有助于更安全,更可靠的电力系统运行.
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