近海摩托艇信号的模态分解

在非线性非平稳信号的分析、处理以及特征提取中，希尔伯特-黄变换(HHT)是一种高效的自适应分析方法，在工程领域中有着广泛应用。本文利用经验模态分解(EMD)和变分模态分解(VMD)方法对近海摩托艇的水声信号进行对比分析，发现水声信号能量主要集中在低频段。与高频段相比，其振幅相对较大。EMD方法在分析这类信号时，会产生模态混叠，因此不能有效分解信号和提取特征；而VMD方法可有效降低模态混叠现象，能够成功提取其信号特征。研究结果表明，VMD方法在船舶水声信号处理分析及特征提取时更为有效，为复杂水声信号的处理提供了一种可行的技术参考。

Mode decomposition of offshore motorboat signals

Hilbert-Huang Transform(HHT) is an efficient adaptive analysis method in nonlinear and nonstationary signal analysis, processing and feature extraction, which is widely used in engineering field. In this paper, Empirical Mode Decomposition(EMD) and Variational Mode Decomposition(VMD) are employed to compare and analyze the underwater acoustic signals of offshore motorboats. It is found that the energy of underwater acoustic signal is mainly concentrated in the low frequency band, and its amplitude is relatively large compared with that in the high frequency band. When analyzing this kind of signal, mode mixing is produced by EMD method, therefore using EMD cannot effectively decompose the signal and extract features. Nevertheless, using VMD method can effectively reduce the phenomenon of mode mixing and successfully extract its signal characteristics. The results show that VMD method is more effective in ship underwater acoustic signal processing and feature extraction.