摘要
玻璃绝缘子作为输电线路中的关键组件,其缺陷直接影响电力系统的可靠性。针对其缺陷对比度低、多尺度等问题,本文提出了一种基于改进RT-DETR的轻量化玻璃绝缘子缺陷检测算法。该方法首先引入轻量化骨干网络RE-FasterNet,通过创新性的部分重复卷积以及高效多尺度注意力机制提升特征提取效率和对小目标、低对比度缺陷的检测能力;其次在特征融合阶段,提出一种部分重复跨阶段特征融合模块,进一步提升网络对多尺度缺陷的检测能力;最后,在小目标检测头中嵌入注意力尺度序列融合框架,显著提升网络对微小缺陷的空间特征提取能力。实验结果表明:所提算法平均准确率相较于基准模型提升了2.8%,模型大小下降了23.6%,计算量下降了13.1%。在玻璃绝缘子自动化缺陷检测领域,具有较强的实用性和推广价值。
Glass insulators are critical components in transmission lines,and their defects can significantly impact the reliability of power systems.This paper proposes an improved defect detection algorithm for lightweight glass insulators based on enhanced RT-DETR,addressing issues related to low contrast and multi-scale defects.First,we introduce the lightweight backbone network RE-FasterNet,which enhances feature extraction efficiency and improves the detection of small targets and low-contrast defects through innovative partial duplication and an efficient multi-scale attention mechanism.Second,during the feature fusion stage,a partially repeated cross-stage feature fusion module is proposed to further enhance the detection capability for multi-scale defects.Finally,an attention scale sequence fusion framework is integrated into the small target detection head,significantly improving the network′s spatial feature extraction ability for small defects.Experimental results demonstrate that the proposed algorithm increases the mean average precision by 2.8%,reduces the model size by 23.6%,and decreases computational requirements by 13.1%compared to the benchmark model.In the domain of automatic defect detection for glass insulators,this approach exhibits strong practicality and broad applicability.
作者
张靖雯
孙坚
徐红伟
许素安
付紫平
Zhang Jingwen;Sun Jian;Xu Hongwei;Xu Su′an;Fu Ziping(College of Mechanical and Electrical Engineering,China Jiliang University,Hangzhou 310018,China)
出处
《电子测量技术》
北大核心
2025年第14期96-105,共10页
Electronic Measurement Technology
基金
浙江省基础公益研究计划项目(LZ24F030007)资助。
