FFT谱最小熵解卷积滤波抑制放电信号中的周期性窄带干扰

Suppression of the Periodic Narrow-band Noise in Discharge Signal by FFT Spectrum Minimum Entropy Deconvolution Filtering

提出了一种基于放电信号FFT谱最小熵解卷积滤波抑制周期性窄带干扰的方法。其原理为将频域上的干扰分量视作有用信号,放电信号视作噪声,利用最小熵解卷积滤波滤除放电信号成分、提取出干扰成分,再在原实测信号频谱中对干扰进行抑制,最后IFFT重构出放电信号。仿真和实验结果均表明该方法能够准确抑制掉窄带干扰,与传统的FFT能量比法相比,不涉及到能量窗的选择,可直接利用经典阈值准则提取出干扰成分,过程十分简便。该方法为现场测试中放电辐射信号周期性窄带干扰抑制提供了一种快捷的新方法。

We propose a new technique with FFT spectrum minimum entropy deconvolution filtering to suppress the periodic narrow-band noise mixed in discharge signal. The principle is the narrow-band noise component will be treated as a new useful signal and the real pure discharge signal as a new noise in frequency domain. In frequency domain, the discharge signal component will be rejected and the narrow-band noise will be kept by minimum entropy deconvolution filtering. The remained noise will be suppressed in the FFT spectrum of the mixed discharge signal, and the pure dis- charge signal is obtained by IFFT process. The simulation and the experiment results indicate that the proposed method can accurately suppress the periodic narrow-band noise. Compared with the conventional energy ratio method based on FFT, the frequency window to compute the energy ratio is not necessary in this method, and the noise can be suppressed well just by classical threshold value criterion. The method offers a new effective technique for the periodic narrow-band noise suppression when detecting the discharge signals.