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A signal processing technique for PD detection and localization in power transformer

机译:电力变压器局部放电检测与定位的信号处理技术

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摘要

The activity of partial discharge (PD) is major problem that causes degradation to the insulation system. Due to continuous stresses of high voltage it may lead to complete breakdown of insulation system. Due to the high cost of transformer windings, especially in the case of high kVA capacity, it is necessary to find a way to localize the PD along the winding length so that only faulty part is replaced instead of the whole winding. In this project a new technique of a digital signal processing method based on the Fast Fourier Transformation (FFT) is applied to locate the PD. The transformer winding was modelled in Matlab using an equivalent lumped transformer circuit for each winding section. The PD source is injected at different section, each section represent a different PD location. The output current was then analysed using FFT. For validation, comparisons had been made with the results of an experimental work on the same transformer winding configuration as well as with theoretical equations. The work has shown that the frequency spectra of the simulated output current have the same characteristic as that for the measured signal as well as for the theoretically derived transfer function. It is also shown that the crests and troughs in the frequency spectra could be used for locating the source of the discharge activity in the power transformer winding. The frequency of the zero in the simulated spectra increases as the discharge moves away from the measuring terminal. The poles are however not affected by the position of the PD source. An Artificial Neural Network (ANN) was successfully used to determine the section number where PD occurs based on just the frequency response of the output current. Further studies on the effects of the modelling parameters such as variations in the capacitance and inductance values due to factors such as ageing on the PD localization show that the capacitance is the most sensitive parameter in the model. In addition, it is also shown that the effect of noise on the PD localization can be eliminated using the Free Induction Decay (FID) technique.
机译:部分放电(PD)的活动是导致绝缘系统退化的主要问题。由于高压持续施加压力,可能导致绝缘系统完全损坏。由于变压器绕组的高成本,特别是在大kVA容量的情况下,有必要找到一种方法来沿着绕组长度定位PD,以便仅更换故障部分而不是整个绕组。在该项目中,基于快速傅立叶变换(FFT)的数字信号处理方法的新技术被应用于定位PD。在Matlab中为每个绕组部分使用等效的集总变压器电路对变压器绕组建模。 PD源注入在不同的部分,每个部分代表一个不同的PD位置。然后使用FFT分析输出电流。为了进行验证,已将相同变压器绕组配置下的实验结果与理论方程进行了比较。这项工作表明,模拟输出电流的频谱具有与被测信号以及理论上导出的传递函数相同的特性。还表明,频谱中的波峰和波谷可用于定位电力变压器绕组中放电活动的来源。随着放电远离测量端子,模拟频谱中的零频率会增加。但是,极点不受PD源位置的影响。仅基于输出电流的频率响应,成功地使用了人工神经网络(ANN)来确定发生PD的区域编号。进一步研究建模参数(例如,由于老化等因素导致的电容和电感值变化)对局部放电局部化的影响,结果表明,电容是模型中最敏感的参数。此外,还表明,使用自由感应衰减(FID)技术可以消除噪声对PD定位的影响。

著录项

  • 作者

    Aziz Mohammed Abd. Ali;

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  • 年度 2014
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  • 原文格式 PDF
  • 正文语种 en
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