摘要
为提高矿用干式变压器局部放电模式识别准确率,提出了一种矿用干式变压器局部放电模式识别方法。首先,采用正交匹配追踪算法对原始局部放电信号进行去噪,最大程度保留原始局部放电信号的有用信息;然后,通过自回归模型提取去噪后局部放电信号的自回归系数特征;最后,将自回归系数特征输入随机森林集成分类器对局部放电模式进行识别。实验结果表明,该方法平均识别准确率达98%。
In order to improve recognition accuracy of partial discharge pattern of mine-used dry-type transformer,a partial discharge pattern recognition method for mine-used dry-type transformer was proposed.Firstly,orthogonal matching pursuit algorithm is used to denoise original partial discharge signal,which can retain useful information of the original partial discharge signal to the greatest extent.Then,autoregressive coefficient features of the partial discharge signal after denoising are extracted by autoregressive model.Finally,the autoregressive coefficient features are input into random forest integrated classifier to recognize partial discharge pattern.The experimental result shows that average recognition accuracy of the method is98%.
作者
唐建伟
苏红
严家明
张建文
王金川
王恩俊
TANG Jianwei;SU Hong;YAN Jiaming;ZHANG Jianwen;WANG Jinchuan;WANG Enjun(School of Electrical and Power Engineering, China University of Mining and Technology,Xuzhou 221008, China;Anhui Electric Power Design Institute Co., Ltd., China Energy Engineering Group, Hefei 230000, China)
出处
《工矿自动化》
北大核心
2019年第1期76-80,共5页
Journal Of Mine Automation
基金
国家重点研发计划资助项目(2017YFF0210600)
关键词
矿用干式变压器
局部放电
正交匹配追踪
自回归系数特征
随机森林集成分类器
mine-used dry-type transformer
partial discharge
orthogonal matching pursuit
autoregressive coefficient feature
random forest integrated classifier