Suppr超能文献

基于二次变分模态分解和相关系数的舰船辐射噪声去噪研究

Research on Ship-Radiated Noise Denoising Using Secondary Variational Mode Decomposition and Correlation Coefficient.

作者信息

Li Yuxing, Li Yaan, Chen Xiao, Yu Jing

机构信息

School of Marine Science and Technology, Northwestern Polytechnical University, Xi'an 710000, China.

出版信息

Sensors (Basel). 2017 Dec 26;18(1):48. doi: 10.3390/s18010048.

Abstract

As the sound signal of ships obtained by sensors contains other many significant characteristics of ships and called ship-radiated noise (SN), research into a denoising algorithm and its application has obtained great significance. Using the advantage of variational mode decomposition (VMD) combined with the correlation coefficient for denoising, a hybrid secondary denoising algorithm is proposed using secondary VMD combined with a correlation coefficient (CC). First, different kinds of simulation signals are decomposed into several bandwidth-limited intrinsic mode functions (IMFs) using VMD, where the decomposition number by VMD is equal to the number by empirical mode decomposition (EMD); then, the CCs between the IMFs and the simulation signal are calculated respectively. The noise IMFs are identified by the CC threshold and the rest of the IMFs are reconstructed in order to realize the first denoising process. Finally, secondary denoising of the simulation signal can be accomplished by repeating the above steps of decomposition, screening and reconstruction. The final denoising result is determined according to the CC threshold. The denoising effect is compared under the different signal-to-noise ratio and the time of decomposition by VMD. Experimental results show the validity of the proposed denoising algorithm using secondary VMD (2VMD) combined with CC compared to EMD denoising, ensemble EMD (EEMD) denoising, VMD denoising and cubic VMD (3VMD) denoising, as well as two denoising algorithms presented recently. The proposed denoising algorithm is applied to feature extraction and classification for SN signals, which can effectively improve the recognition rate of different kinds of ships.

摘要

由于传感器获取的舰船声信号包含舰船的许多其他重要特征,被称为舰船辐射噪声(SN),因此研究去噪算法及其应用具有重要意义。利用变分模态分解(VMD)结合相关系数进行去噪的优势,提出了一种基于二次VMD结合相关系数(CC)的混合二次去噪算法。首先,利用VMD将不同类型的仿真信号分解为若干个带宽受限的本征模态函数(IMF),其中VMD的分解个数与经验模态分解(EMD)的分解个数相等;然后,分别计算各IMF与仿真信号之间的相关系数。通过相关系数阈值识别噪声IMF,对其余IMF进行重构,以实现第一次去噪过程。最后,通过重复上述分解、筛选和重构步骤,完成对仿真信号的二次去噪。根据相关系数阈值确定最终的去噪结果。在不同信噪比和VMD分解次数下比较去噪效果。实验结果表明,与EMD去噪、总体EMD(EEMD)去噪、VMD去噪和三次VMD(3VMD)去噪以及最近提出的两种去噪算法相比,所提出的基于二次VMD(2VMD)结合CC的去噪算法是有效的。所提出的去噪算法应用于舰船辐射噪声信号的特征提取和分类,能够有效提高不同类型舰船的识别率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8604/5795591/485e5c26d207/sensors-18-00048-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验