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Multi-Resolution Generalized S-Transform Denoising for Precise Localization of Partial Discharge in Substations

机译:用于精确定位变电站的精确定位的多分辨率广义S转变

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摘要

Denoising is a crucial step in the localization of partial discharge (PD) in a substation. In this paper, a novel multi-resolution generalized S-transform (GST) denoising algorithm for precise localization of PD in substations is proposed. The algorithm denoises the PD signal received by the ultra-high frequency (UHF) sensor in two steps. First, the GST with the high frequency resolution is used to analyze the PD signal, and a GST filter is designed to filter out periodic narrowband noises. Then, the S-transform (a particular case of GST) is applied to analyze the PD signal, and the white Gaussian noise is suppressed according to the statistical characteristic difference between the noise and effective signal. Finally, the denoised PD signal is obtained and applied to PD localization. The simulations results show that the proposed algorithm can effectively suppress noise and can extract accurate time delay data from the denoised PD signal. The experiment results show that, compared with the wavelet transform, the localization error of the proposed algorithm is the smallest, which is 1.59m. The proposed algorithm can realize the precise localization of PD.
机译:去噪是在变电站中局部放电(PD)定位的关键步骤。本文提出了一种用于在变电站中精确定位PD的新型多分辨率广义S变换(GST)去噪算法。该算法以两步以超高频(UHF)传感器接收的PD信号代替。首先,使用高频分辨率的GST来分析PD信号,并且设计GST滤波器以滤除周期性的窄带噪声。然后,应用S转换(GST的特定情况)以分析PD信号,并且根据噪声和有效信号之间的统计特性差异抑制了白色高斯噪声。最后,获得了去噪的PD信号并将其应用于PD定位。仿真结果表明,该算法可以有效地抑制噪声,并可以从去噪PD信号提取精确的时间延迟数据。实验结果表明,与小波变换相比,所提出的算法的定位误差是最小的,即1.59米。该算法可以实现PD的精确定位。

著录项

  • 来源
    《Sensors Journal, IEEE》 |2021年第4期|4966-4980|共15页
  • 作者单位

    Shuguang Ning are with the School of Electrical Engineering and Automation Hefei University of Technology Hefei China;

    School of Electrical Engineering and Automation Hefei University of Technology Hefei China;

    Shuguang Ning are with the School of Electrical Engineering and Automation Hefei University of Technology Hefei China;

    Shuguang Ning are with the School of Electrical Engineering and Automation Hefei University of Technology Hefei China;

    Shuguang Ning are with the School of Electrical Engineering and Automation Hefei University of Technology Hefei China;

    Shuguang Ning are with the School of Electrical Engineering and Automation Hefei University of Technology Hefei China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Time-frequency analysis; Partial discharges; Sensors; Narrowband; Noise reduction; Substations; Gaussian noise;

    机译:时频分析;部分放电;传感器;窄带;降噪;变电站;高斯噪音;

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