高压交流电下玻璃绝缘子污染等级的CNN分类器

IF 0.7 4区工程技术 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC

Electronics Letters Pub Date : 2025-06-07 DOI:10.1049/ell2.70327

Yuri dos Reis Oliveira, Eduardo Costa da Silva, Carlos Roberto Hall Barbosa

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引用次数: 0

摘要

本文旨在利用日冕紫外线（UV）图像数据库和基于卷积神经网络的计算智能算法，考虑极弱、弱和中度三种不同的污染水平，开发绝缘子污染严重程度（LPS）分类器。结果表明，所开发的分类器准确率高（98.57%），对数损失值低（0.059），具有较好的处理分类任务的能力。

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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CNN Classifier for Pollution Level in Glass Insulators Operating at High Voltage Alternating Current

This paper aims at developing a level of pollution severity (LPS) classifier for insulators, using a database of corona ultraviolet (UV) images and a computational intelligence algorithm based on convolutional neural networks, considering three different levels of pollution: very weak, weak and moderate. The obtained results show that the developed classifier reached high accuracy (98.57%) and low logarithmic loss values (0.059), indicating that it has a good capability to deal with the proposed classification task.

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来源期刊

Electronics Letters 工程技术-工程：电子与电气

CiteScore

2.70

自引率

0.00%

发文量

268

审稿时长

3.6 months

期刊介绍： Electronics Letters is an internationally renowned peer-reviewed rapid-communication journal that publishes short original research papers every two weeks. Its broad and interdisciplinary scope covers the latest developments in all electronic engineering related fields including communication, biomedical, optical and device technologies. Electronics Letters also provides further insight into some of the latest developments through special features and interviews. Scope As a journal at the forefront of its field, Electronics Letters publishes papers covering all themes of electronic and electrical engineering. The major themes of the journal are listed below. Antennas and Propagation Biomedical and Bioinspired Technologies, Signal Processing and Applications Control Engineering Electromagnetism: Theory, Materials and Devices Electronic Circuits and Systems Image, Video and Vision Processing and Applications Information, Computing and Communications Instrumentation and Measurement Microwave Technology Optical Communications Photonics and Opto-Electronics Power Electronics, Energy and Sustainability Radar, Sonar and Navigation Semiconductor Technology Signal Processing MIMO