结合广义S变换和快速独立分量分析的局放信号中窄带干扰抑制方法

针对现有方法对局部放电（partial discharge,PD）信号中窄带干扰抑制效果较差的问题，提出了一种基于广义S变换和快速独立分量分析的窄带干扰抑制方案。该方案首先利用广义S变换对染噪PD信号进行时频分析，在染噪PD信号的时频分布图中，根据窄带干扰和PD信号的不同时频特征，可以确定窄带干扰的特征区域；然后在窄带干扰的特征区域中，利用Candan算法对窄带干扰的频率进行估计；最后利用窄带干扰频率估计值和快速独立分量分析方法分离出PD信号，实现窄带干扰抑制。仿真和实测结果说明，所提方法可以有效抑制染噪PD信号中窄带干扰，并且能准确获取PD信号的波形特征，对比传统的奇异值分解方法和快速傅里叶变换滤波方法，文中方法对窄带干扰的抑制效果更好，残余干扰的能量较小。

A Method for Narrowband Interference Suppression in Partial Discharge Signal Combining Generalized S-transform and Fast Independent Component Analysis

To solve the problem that the existing methods have a poor effect on narrowband interference suppression in partial discharge(PD) signal, the method based on generalized S transform and fast independent component analysis is proposed in this paper. Firstly, the generalized S-transform is used to analyze the time-frequency distribution of the noised PD signal. In the time-frequency distribution picture of the PD signal, the characteristic region of the narrowband interference can be determined according to the different time-frequency characteristics of the narrowband interference and the PD signal. Then, in the characteristic region of narrowband interference, the frequency of narrowband interference is estimated by using the Candan algorithm. Finally, the PD signal is separated by using the frequency estimation of narrowband interference and the fast independent component analysis method, suppressing the narrowband interference. The simulation and measurement results show that the proposed method can effectively suppress the narrowband interference in the noised PD signal, and it can accurately obtain the waveform characteristic of the PD signal. Compared with the singular value decomposition method and fast Fourier transform filtering method, the proposed method has a better suppression effect on narrowband interference and less residual interference energy.