基于轻量级改进RT-DETR边缘部署算法的绝缘子缺陷检测  

Insulator Defect Detection Based on Lightweight Improved RT-DETR Edge Deployment Algorithm

作　　者：姜香菊[1] 王瑞彤 马彦鸿 Jiang Xiangju;Wang Ruitong;Ma Yanhong(School of Automation and Electrical Engineering Lanzhou Jiaotong University,Lanzhou 730070 China;School of Mechanical Engineering Lanzhou Jiaotong University,Lanzhou 730070 China;Gansu Province Special Equipment Inspection and Testing Institute,Lanzhou 730070,China)

机构地区：[1]兰州交通大学自动化与电气工程学院,兰州730070 [2]兰州交通大学机电工程学院,兰州730070 [3]甘肃省特种设备检验检测研究院,兰州730050

出　　处：《电工技术学报》2025年第3期842-854,共13页Transactions of China Electrotechnical Society

基　　金：甘肃省自然科学基金资助项目(23JRRA868)。

摘　　要：随着新型电力系统的不断发展建设,输电线路绝缘子状态智能化巡检成为必然趋势。为方便“云-边-端协同架构”进行边缘部署,该文提出一种轻量级RT-DETR目标检测算法。首先,采用RT-DETR作为基线算法降低优化难度,提高鲁棒性;其次,选择轻量级EMO作为算法特征提取主干,充分学习绝缘子目标的长距离特征交互及缺陷小目标的局部特征交互,并提出基于轻量级注意力的尺度内特征交互模块和轻量级跨尺度特征融合模块设计轻量级高效混合编码器;再次,在轻量级高效混合编码器中引入定位信息补充分支、使用DIoU损失函数结合迁移学习训练技巧,缓解轻量化造成的算法精度下降问题;最后,构建多天气条件绝缘子数据集进行训练验证。实验结果表明,相较于基线算法,所提算法检测精度达到97.2%,只损失0.7个百分点,而参数量和计算量分别下降67.8%和71.2%,检测速度提升2.5倍,满足多天气条件下的输电线路绝缘子状态巡检准确率及边缘部署轻量化要求。With the continuous advancement of the new generation power system construction and the continuous development of artificial intelligence technology,it has become an inevitable development trend to use intelligent methods to inspect the insulator condition of transmission lines."Cloud-edge-end collaborative architecture"has the characteristics of cloud service center and edge computing equipment,and is suitable for insulator condition inspection,which can improve the inspection efficiency of insulators and avoid the risk of manual inspection.However,the computing power of edge devices in"cloud-edge-end collaborative architecture"is relatively poor.In order to facilitate its algorithm deployment,a lightweight rel-time detection transformer(RTDETR)target detection algorithm is proposed to meet the requirements of edge devices for deploying lightweight algorithms,and at the same time,to ensure that the algorithm performance can meet the accuracy requirements of transmission line insulator condition inspection tasks.Firstly,RT-DETR is used as the baseline algorithm to reduce the difficulty of optimization and improve the robustness.Then,in order to reduce the parameters and calculation of the algorithm,the lightweight efficient model(EMO)is selected as the feature extraction backbone of the algorithm,and the long-distance feature interaction of insulator targets and the local feature interaction of defective small targets are fully learned.At the same time,a lightweight and efficient hybrid encoder is designed based on the lightweight attention-based intrascale feature interaction module and lightweight cross-scale feature fusion module,which further lightens the algorithm.Finally,because the lightweight improvement will lead to a certain degree of algorithm performance degradation,the location information supplementary branch is introduced into the lightweight and efficient hybrid encoder to alleviate the problem of the loss of positioning information of defective small targets in deep features.Because the structure

关 键 词：绝缘子缺陷检测 RT-DETR算法 轻量化 边缘部署 目标检测算法 

分 类 号：TM755[电气工程—电力系统及自动化] TP389[自动化与计算机技术—计算机系统结构]