Wavelet analysis of partial discharges acoustic waves obtained using an optical fibre interferometric sensor for transformer applications

C. Macià-Sanahuja, H. Lamela-Rivera
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引用次数: 16

Abstract

The main problem in power transformers is the degradation of the isolation, and partial discharges are a major contribution to this shortcoming. Partial discharges inside medium and high power transformers generate ultrasonic pressure waves which are detected, in this work, with an optical fibre interferometric sensor. The Mach-Zehnder interferometric sensor implemented, for the detection of partial discharges inside power transformers, is described. This sensor allows a high level sensitivity to be achieved for the typical small pressure variations created by partial discharges. Wavelet analysis is used to identify the acoustic patterns instead of more commonly used Fourier analysis. Acoustic signals contain numerous non-stationary or transitory characteristics that Fourier analysis does not allow them to be obtained: when transforming to frequency domain, temporal information disappears. It is possible to state when a particular event took place. The wavelet analysis helps to solve this problem. Some of the results of which are presented here. These results are compared to those obtained with piezoelectric acoustic sensors, when looking for the best wavelet application, showing good agreement between both methods. We have obtained clear signal between 15-17 kHz and, for the first time, wavelet analysis has provided a tool to identify the shape of the acoustic waves associated to partial discharges.
变压器用光纤干涉传感器局部放电声波的小波分析
电力变压器的主要问题是隔离性能的下降,而局部放电是造成这一缺陷的主要原因。中功率和大功率变压器内部的局部放电产生超声波压力波,在这项工作中,用光纤干涉传感器检测超声波压力波。本文描述了一种用于电力变压器内部局部放电检测的Mach-Zehnder干涉传感器。这种传感器可以对部分放电产生的典型的小压力变化实现高水平的灵敏度。小波分析用于识别声学模式,而不是更常用的傅立叶分析。声信号包含许多傅立叶分析不允许获得的非平稳或瞬态特征:当转换到频域时,时间信息消失。可以说明特定事件发生的时间。小波分析有助于解决这一问题。这里给出了其中的一些结果。在寻找最佳的小波应用时,将这些结果与压电声传感器的结果进行了比较,显示出两种方法之间的良好一致性。我们已经获得了15-17 kHz之间的清晰信号,并且第一次,小波分析提供了一种工具来识别与部分放电相关的声波形状。
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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