基于无人机航拍的绝缘子掉串实时检测研究
TM855; 由无人机代替人工进行电力绝缘子巡检具有重要意义,针对无人机的上位机算力和存储资源有限的问题,提出一种适用于绝缘子掉串故障检测的实时目标检测改进算法.以YOLOv5s检测网络为基础,将颈部结构中路径聚合网络替换为双向特征金字塔网络,以提升特征融合能力;使用DIoU优化损失函数,对模型进行γ系数的通道剪枝和微调,总体上提升检测网络的精度、速度和部署能力;在网络输出处进行图像增强以提升算法可用性.在特殊扩增的绝缘子故障数据集下测试,相较于原始的YOLOv5s算法,改进算法在精度平均值上提升了 3.91％,速度提升了 25.6％,模型体积下降了 59.1％....
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| Published in | 上海交通大学学报 Vol. 56; no. 8; pp. 994 - 1003 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | Chinese |
| Published |
上海电机学院电气学院,上海201306%国网华东电力试验研究院有限公司,上海200437
2022
复旦大学类脑智能科学与技术研究院,上海200433 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1006-2467 |
| DOI | 10.16183/j.cnki.jsjtu.2021.416 |
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| Abstract | TM855; 由无人机代替人工进行电力绝缘子巡检具有重要意义,针对无人机的上位机算力和存储资源有限的问题,提出一种适用于绝缘子掉串故障检测的实时目标检测改进算法.以YOLOv5s检测网络为基础,将颈部结构中路径聚合网络替换为双向特征金字塔网络,以提升特征融合能力;使用DIoU优化损失函数,对模型进行γ系数的通道剪枝和微调,总体上提升检测网络的精度、速度和部署能力;在网络输出处进行图像增强以提升算法可用性.在特殊扩增的绝缘子故障数据集下测试,相较于原始的YOLOv5s算法,改进算法在精度平均值上提升了 3.91％,速度提升了 25.6％,模型体积下降了 59.1％. |
|---|---|
| AbstractList | TM855; 由无人机代替人工进行电力绝缘子巡检具有重要意义,针对无人机的上位机算力和存储资源有限的问题,提出一种适用于绝缘子掉串故障检测的实时目标检测改进算法.以YOLOv5s检测网络为基础,将颈部结构中路径聚合网络替换为双向特征金字塔网络,以提升特征融合能力;使用DIoU优化损失函数,对模型进行γ系数的通道剪枝和微调,总体上提升检测网络的精度、速度和部署能力;在网络输出处进行图像增强以提升算法可用性.在特殊扩增的绝缘子故障数据集下测试,相较于原始的YOLOv5s算法,改进算法在精度平均值上提升了 3.91％,速度提升了 25.6％,模型体积下降了 59.1％. |
| Author | 李登攀 任晓明 颜楠楠 |
| AuthorAffiliation | 上海电机学院电气学院,上海201306%国网华东电力试验研究院有限公司,上海200437;复旦大学类脑智能科学与技术研究院,上海200433 |
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| Author_FL | LI Dengpan YAN Nannan REN Xiaoming |
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| Keywords | γ系数剪枝微调 DIoU损失函数 无人机 图像增强 绝缘子掉串 双向特征金字塔网络结构 |
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| Title | 基于无人机航拍的绝缘子掉串实时检测研究 |
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