广东电力2023，Vol.36Issue(11)：138-145,8.DOI:10.3969/j.issn.1007-290X.2023.11.015
基于Vision Transformer的电缆终端局部放电模式识别
Partial Discharge Pattern Recognition of Cable Terminal Based on Vision Transformer
摘要
Abstract
Cable terminal defect types are generally closely related to the characteristics of partial discharge signals,thus it is feasible to classify the defect types by means of pattern recognition of the partial discharge signals.This paper analyzes the discharge pulse waveforms and time spectrogram characteristics of four typical defects of 15 kV XLPE cable terminals and obtains data samples that can be used for identification.Then it uses the Vision Transformer(VIT)model,LeNet5,AlexNet and support vector machine to train the data to compare the recognition accuracy of different algorithms.The results show that the recognition accuracy of the VIT model is higher than that of other recognition algorithms as the data is sufficient.The methods and conclusions proposed can provide a reliable basis for the insulation evaluation of cable accessories and have certain guiding significance.关键词
电缆终端/局部放电/模式识别/Vision Transformer/数据训练Key words
cable terminal/partial discharge/pattern recognition/Vision Transformer/data training分类
信息技术与安全科学引用本文复制引用
唐庆华,方静,李旭,宋鹏先,孟庆霖,魏占朋..基于Vision Transformer的电缆终端局部放电模式识别[J].广东电力,2023,36(11):138-145,8.基金项目
国家自然科学基金面上项目(52277156) （52277156）
国网天津市电力公司科技项目(电科-研发2023-37) （电科-研发2023-37）
