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Separation of corona using wavelet packet transform and neural network for detection of partial discharge in gas-insulated substations

机译:基于小波包变换和神经网络的气体绝缘变电站局部放电电晕分离

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摘要

It is essential to detect partial discharge (PD) as a symptom of insulation breakdown in gas-insulated substations (GIS). However, the accuracy of such measurement is often degraded due to the existence of noise in the signal. In this paper, a method using wavelet packet transform and neural network is proposed to separate the PD pulses from corona in air, which enables more accurate detection of insulation breakdown of GIS.
机译:重要的是要检测局部放电(PD)作为气体绝缘变电站(GIS)绝缘击穿的征兆。但是,由于信号中存在噪声,因此这种测量的准确性通常会降低。本文提出了一种利用小波包变换和神经网络的方法,将空气中的局放脉冲与电晕分离开来,从而可以更准确地检测GIS绝缘故障。

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