基于经验模态分解和自适应噪声对消算法的窄带干扰抑制

Narrow-band Interference Suppression Based on Adaptive Noise Canceller and Empirical Mode Decomposition

在局部放电在线检测中,自适应噪声对消算法是当前抑制窄带干扰的有效方法。由于窄带干扰频率范围很宽,滤波参数不易设置,同时实测时的窄带干扰在时频域都表现强烈,局部放电信号会完全淹没于干扰之中,使得一般改进噪声对消算法不能取得较好效果。为此,笔者提出一种改进经验模态分解的噪声对消算法,首先在频域中降低干扰幅值,接着利用经验模态分解的分频特性将宽频带的窄带干扰分解到不同频带,各频带内的窄带干扰频率相差有限,然后进行自适应噪声对消,以达到较好的滤波性能。仿真和实际数据验证了该算法的有效性。

Usual adaptive filter is one of the best algolithms in suppressing narrow-band interference in partial discharge signal processing. However, it is difficult to set the parameters of the adaptive filter in PD on-line monitoring due to wide frequency range of narrow bandwidth noise. Moreover, the noise is strong in both time domain and frequency domain. This paper presents a new algorithm based on empirical mode decomposition. First, the mid-signals are generated＇ by reducing the amplitude of narrow-band interference in frequency domain, which is decomposed with empirical mode decomposition, and intrinsic mode functions （IMF） which contain specific frequency are obtained, then for every. intrinsic mode function adaptive noise canceller is used to suppress narrow-band interference. Simulation results and on-site data verify the validity of the proposed algorithm.