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Novel noise reduction method based on improved empirical wavelet transform and kurtosis for partial discharge signal of high-voltage cables

机译:基于改进经验小波变换和峰度的高压电缆局部放电信号降噪方法

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摘要

Partial discharge (PD) detection is useful to the online monitoring of high-voltage cables, which are affected by periodic narrowband interference and random white noise. To suppress the influence of complex noise signals on the measurement of PD signals, a novel noise reduction method based on improved empirical wavelet transform (IEWT) and kurtosis for the PD signals of high-voltage cables is proposed. First, empirical wavelet function (EWF) signals arranged in order of frequency are obtained by decomposing the signal with IEWT. Then, the kurtosis criterion is introduced, and the reconstructed inherent modal function is adaptively screened. Finally, the improved threshold function is used in eliminating residual noise information in the reconstructed signal. Compared with the noise reduction methods based on EWT and EMD, the proposed noise reduction method can effectively suppress noise information in PD and has good practicability.
机译:局部放电(PD)检测对于高压电缆的在线监测非常有用,高压电缆会受到周期性窄带干扰和随机白噪声的影响。为了抑制复杂噪声信号对PD信号测量的影响,该文提出一种基于改进经验小波变换(IEWT)和峰度的高压电缆PD信号降噪方法。首先,利用IEWT对信号进行分解,得到按频率顺序排列的经验小波函数(EWF)信号;然后,引入峰度准则,对重构的固有模态函数进行自适应筛选;最后,利用改进的阈值函数消除重构信号中的残余噪声信息。与基于EWT和EMD的降噪方法相比,所提出的降噪方法能有效抑制PD中的噪声信息,具有较好的实用性。

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