Intelligent Inspection System for Power Insulators Based on AAV on Complex Weather Conditions

IF 1.7 3区物理与天体物理 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Applied Superconductivity Pub Date : 2024-10-07 DOI:10.1109/TASC.2024.3465368

Yi Li;Yanfeng Lu;Kaixin Wu;Yuan Fang;Chaodan Zheng;Jiangang Zhang

{"title":"Intelligent Inspection System for Power Insulators Based on AAV on Complex Weather Conditions","authors":"Yi Li;Yanfeng Lu;Kaixin Wu;Yuan Fang;Chaodan Zheng;Jiangang Zhang","doi":"10.1109/TASC.2024.3465368","DOIUrl":null,"url":null,"abstract":"This paper presents an intelligent inspection system for power insulators, integrating automous aerial vehicles (AAV) to address complex conditions. A novel image enhancement technique, based on the multi-scale Retinex algorithm with combined illumination correction and compensation, is proposed to enhance both the overall image quality of insulators and the visual perception for human observers. The study employs the state-of-the-art YOLOv7 target detector for automated identification of insulator defects. The YOLOv7 model undergoes further optimization, enhancing the feature extraction structure, incorporating the SE attention mechanism, and refining the loss function. These modifications enable the model to adapt to more intricate intelligent inspection tasks related to transmission line insulators, resulting in improved efficiency and detection accuracy. Building on this research out-comes, our team introduces an intelligent power insulator detection software system tailored for AAV inspection scenarios.","PeriodicalId":13104,"journal":{"name":"IEEE Transactions on Applied Superconductivity","volume":"34 8","pages":"1-4"},"PeriodicalIF":1.7000,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Applied Superconductivity","FirstCategoryId":"101","ListUrlMain":"https://ieeexplore.ieee.org/document/10706994/","RegionNum":3,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}

引用次数: 0

Abstract

This paper presents an intelligent inspection system for power insulators, integrating automous aerial vehicles (AAV) to address complex conditions. A novel image enhancement technique, based on the multi-scale Retinex algorithm with combined illumination correction and compensation, is proposed to enhance both the overall image quality of insulators and the visual perception for human observers. The study employs the state-of-the-art YOLOv7 target detector for automated identification of insulator defects. The YOLOv7 model undergoes further optimization, enhancing the feature extraction structure, incorporating the SE attention mechanism, and refining the loss function. These modifications enable the model to adapt to more intricate intelligent inspection tasks related to transmission line insulators, resulting in improved efficiency and detection accuracy. Building on this research out-comes, our team introduces an intelligent power insulator detection software system tailored for AAV inspection scenarios.

查看原文本刊更多论文

复杂天气条件下基于 AAV 的电力绝缘子智能检测系统

本文介绍了一种电力绝缘子智能检测系统，该系统集成了自动飞行器（AAV），可应对复杂的条件。本文提出了一种基于多尺度 Retinex 算法的新型图像增强技术，该算法结合了光照校正和补偿，可同时提高绝缘子的整体图像质量和人类观察者的视觉感知能力。研究采用了最先进的 YOLOv7 目标检测器来自动识别绝缘体缺陷。YOLOv7 模型经过进一步优化，增强了特征提取结构，纳入了 SE 注意机制，并完善了损失函数。这些修改使模型能够适应与输电线路绝缘子相关的更复杂的智能检测任务，从而提高效率和检测精度。在此研究成果的基础上，我们的团队推出了针对 AAV 检测场景的智能电力绝缘子检测软件系统。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Transactions on Applied Superconductivity 工程技术-工程：电子与电气

CiteScore

3.50

自引率

33.30%

发文量

650

审稿时长

2.3 months

期刊介绍： IEEE Transactions on Applied Superconductivity (TAS) contains articles on the applications of superconductivity and other relevant technology. Electronic applications include analog and digital circuits employing thin films and active devices such as Josephson junctions. Large scale applications include magnets for power applications such as motors and generators, for magnetic resonance, for accelerators, and cable applications such as power transmission.