基于级联网络和轻量级关注机制的复杂场景下绝缘体缺陷检测

IF 3.3 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Peer-To-Peer Networking and Applications Pub Date : 2024-04-20 DOI:10.1007/s12083-024-01682-2
Yang Ning, Li Xiang, Jing Hongyuan, Shang Xinna, Shen Ping, Chen Aidong
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引用次数: 0

摘要

电力系统是关系到国家现代经济、安全和社会发展的重要基础设施。本文利用配备目标检测方法的无人飞行器的先进技术,探讨输电塔绝缘体故障检测所面临的挑战。我们提出了一种基于 YOLOv5(只看一次)的绝缘体缺陷检测新方法,旨在缓解与高漏检率相关的问题。由于绝缘子故障较小,加上无人机机载能力的限制,很难进行全面检测。首先,对训练数据进行聚类分析,得到 9 种较好的绝缘体检测预设锚点,提高了模型识别目标位置的准确性。其次,利用基础模型检测绝缘子区域,并将检测结果输入子模型检测故障位置,从而形成级联模型,充分发挥两个模型的优势,解决漏检率高的问题。最后,在 YOLOv5 中加入了轻量级关注模块,将通道关注模块和空间关注模块相结合,提高了基础模型对绝缘体区域的关注度,抑制了复杂背景特征。实验结果表明,与原始模型相比,所提方法的绝缘体检测平均精度提高了 6.9%,故障定位的漏检率降低了 30%。本文提出的方法显著提高了绝缘子检测性能。它不仅能有效提高检测精度,还能使漏检率降低,满足复杂环境下绝缘子缺陷检测和故障预警应用的要求,这证明它在实际应用中,尤其是在电力行业领域具有广泛的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Insulator defect detection in complex scenarios based on cascaded networks with lightweight attention mechanism

The power system stands as a crucial infrastructure pivotal to the country’s modern economic, security and social development. This paper addresses challenges in insulator fault detection on power transmission towers, leveraging the advancements in unmanned aerial vehicles equipped with target detection methods. We propose a novel method for insulator defect detection based on YOLOv5 (You Only Look Once), aiming to mitigate the issues associated with high missed detection rates. Small insulator faults and the limitation of unmanned aerial vehicle on-board capacity make it difficult to detect comprehensively. Firstly, the cluster analysis was carried out on the training data to obtain 9 kinds of better preset anchors for insulator detection, which improved the accuracy of the model to identify the location of targets. Secondly, the base-model is used to detect the insulator region, and the detection results are input into the sub-model to detect the location of faults, so as to form a cascade model, and make full use of the advantages of the two models to solve the problem of high missed detection rate. Finally, a lightweight attention module combining channel attention module and spatial attention module is added in YOLOv5 to improve the base-model’s attention to insulator region and suppress complex background features. Experimental results show that compared with the original model, the average precision of the proposed method for insulator detection is increased by 6.9%, and the missed detection rate of the fault location is 30% lower. Significant improvements in insulator detection performance have been achieved using the method proposed in this paper. It can not only effectively improve the detection accuracy, but also make the missed detection rate lower to meet the requirements of insulator defect detection and fault warning applications in complex environments, which proves that it has a wide range of application prospects in practice, especially in the field of power industry.

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来源期刊
Peer-To-Peer Networking and Applications
Peer-To-Peer Networking and Applications COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS
CiteScore
8.00
自引率
7.10%
发文量
145
审稿时长
12 months
期刊介绍: The aim of the Peer-to-Peer Networking and Applications journal is to disseminate state-of-the-art research and development results in this rapidly growing research area, to facilitate the deployment of P2P networking and applications, and to bring together the academic and industry communities, with the goal of fostering interaction to promote further research interests and activities, thus enabling new P2P applications and services. The journal not only addresses research topics related to networking and communications theory, but also considers the standardization, economic, and engineering aspects of P2P technologies, and their impacts on software engineering, computer engineering, networked communication, and security. The journal serves as a forum for tackling the technical problems arising from both file sharing and media streaming applications. It also includes state-of-the-art technologies in the P2P security domain. Peer-to-Peer Networking and Applications publishes regular papers, tutorials and review papers, case studies, and correspondence from the research, development, and standardization communities. Papers addressing system, application, and service issues are encouraged.
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