A new look at classification of transformer normal and abnormal currents

机译：变压器正常和异常电流分类的新观点

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The paper proposes an enhanced wavelet-based feature extraction technique to classify transformer inrush currents (TIC) and transformer internal faults (TIF). The proposed tool utilizes the number of wavelet coefficients of local maxima as current signal slides into Kaiser's window. The general pattern of number of coefficients of local maxima at the first three resolutions are used to design a new automated tool for monitoring and classifying abnormal conditions in power transformers. The proposed monitoring technique is evaluated using large data sets.

机译：本文提出了一种基于小波的增强特征提取技术，以对变压器浪涌电流（TIC）和变压器内部故障（TIF）进行分类。当电流信号滑入凯撒（Kaiser）窗口时，该工具利用局部最大值的小波系数数量。使用前三个分辨率的局部最大值系数的一般模式来设计一种新的自动化工具，用于监视和分类电力变压器中的异常状况。使用大型数据集评估了建议的监视技术。

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来源
《MELECON 2010;IEEE Mediterranean Electrotechnical Conference》|2010年|p.830-834|共5页
会议地点 Valletta(MT)
作者
Abdel-Hafez M.; Gaouda A.M.;
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作者单位

Dept. of Electr. Eng., United Arab Emirates Univ., Al-Ain, United Arab Emirates;

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会议组织
原文格式 PDF
正文语种 eng
中图分类真空电子技术;
关键词
Inrush current; Kaiser's Window; Multi-resolution analysis; Transformer Faults; Wavelet transform.;

机译：涌入电流； Kaiser窗；多分辨率分析；变压器故障；小波变换。;

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A new look at classification of transformer normal and abnormal currents

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