Diagnosis and identification of transformer faults from frequency response data

S. Birlasekaran, Y. Xingzhou, F. Fetherstone, R. Abell, R. Middleton
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引用次数: 24

Abstract

Identification of transformer faults using matched amplitude and phase response characteristics is presented. In frequency response analysis, fault diagnosis is done by detecting changes in frequency response tests. The vast amount of data up to 2 MHz needs to be quantified and characterized for the classification of faults. By a matched fitting with higher order transfer function up to 40, poles, zeros and their relative damping were determined in the frequency plane. Each set of data corresponding to faults is used to train a backpropagation ANN network. Out of 12 faults, the processing technique is able to identify the changes and classify the type of fault for on-line analysis. The location of fault and the severity of faults in the form of more sensitivity are brought out using this signal processing technique.
基于频率响应数据的变压器故障诊断与识别
提出了利用匹配的幅相响应特征识别变压器故障的方法。在频响分析中,故障诊断是通过检测频响试验的变化来完成的。对于高达2 MHz的海量数据,需要对其进行量化和特征化,以便对故障进行分类。通过高阶传递函数的匹配拟合,确定了频率平面上的极点、零点及其相对阻尼。每个故障对应的数据集被用来训练反向传播人工神经网络。在12个故障中,该处理技术能够识别故障的变化并对故障类型进行分类,便于在线分析。利用该信号处理技术,以更灵敏的形式给出了故障的位置和严重程度。
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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