基于EMD-NLMS的船舶发动机声信号降噪处理方法

Noise reduction processing method of ship engine acoustic signal based on EMD-NLMS

针对船舶声信号降噪滤波的问题,提出了一种基于经验模态分解-归一最小均方的算法。该方法进行经验模态分解得出噪声分量,将得到的噪声分量作为输入信号进行自适应滤波,通过自适应滤波算法迭代处理得到降噪后的信号分量,并把信号分量叠加得到最终降噪后的信号。通过对比最小均方算法、归一化最小均方算法、经验模态分解-最小均方算法和经验模态分解-归一最小均方算法对船舶声信号的降噪效果,得出在船舶声信号滤波降噪方面经验模态分解-归一最小均方算法相比于其他三种算法有更好的滤波效果。

Aiming at the problem of noise reduction and filtering of ship acoustic signals,this paper proposes a method based on Empirical Mode Decomposition-Normalized Least Mean Square algorithm.In this method,the noise component is obtained by Empirical Mode Decomposition,and the noise component is used as the input signal for adaptive filtering.The denoised signal component is obtained by iterative processing of the adaptive algorithm,and the final denoised signal is obtained by superposition of the signal components.By comparing the noise reduction effects of Least Mean Square algorithm,the Normalized Least Mean Square algorithm,the Empirical Mode Decomposition-Least Mean Square algorithm and the Empirical Mode Decomposition Normalized Least Mean Square algorithm on ship acoustic signals,it is concluded that the Empirical Mode Decomposition Normalized Least Mean Square algorithm has better filtering effect than the other three methods in terms of ship acoustic signal filtering and noise reduction.