奇异值重构在抑制局部放电窄带干扰中的应用

Heng Ran, Yonggan Xu, Jie Jiang, Kunming Tang, Zirun He, Taiqin Zhang, X. Tang
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引用次数: 3

摘要

为了抑制局部放电(PD)在线测量中的周期性窄带干扰,提出了一种基于奇异值重构的去噪方法。首先,利用PD样本序列构造Hankel矩阵,并对其进行奇异值分解(SVD);然后采用K-means算法自适应提取窄带干扰对应的奇异值;最后,从原始采样序列中重构并去除窄带干扰,得到PD脉冲。仿真和实测信号的去噪结果表明:与FFT阈值法和小波去噪法相比,所提方法对窄带干扰具有更好的抑制效果;该方法降噪后的PD波形更接近原始PD脉冲,更有利于PD脉冲的后续分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Singular Value Reconstruction in Suppressing Narrowband Interference of Partial Discharge
In order to suppress the periodic narrowband interference in partial discharge (PD) online measurement, this paper presents a novel de-noising method based on singular value reconstruction. Firstly, the Hankel matrix is constructed by the PD sample sequence and singular value decomposition (SVD) is performed on it. Then the singular values corresponding to the narrowband interference are adaptively extracted by the K-means algorithm. Finally, the narrowband interference is reconstructed and removed from the original sample sequence to obtain the PD pulses. The de-noised results of the simulated and measured signals show that: Compared with the FFT threshold method and the wavelet de-noising method, the proposed method has better suppression effect on the narrowband interference; The de-noised PD waveform of the proposed method is more similar to the original PD pulses, which is more conducive to the subsequent analysis of the PD pulses.
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