基于集合经验模态分解的舰船辐射噪声能量分析

杨 宏1,2,李亚安1,李国辉1,2

振动与冲击 ›› 2015, Vol. 34 ›› Issue (16) : 55-59.

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PDF(2339 KB)
振动与冲击 ›› 2015, Vol. 34 ›› Issue (16) : 55-59.
论文

基于集合经验模态分解的舰船辐射噪声能量分析

  • 杨  宏1,2,李亚安1,李国辉1,2
作者信息 +

Energy analysis of ship radiated noise based on ensemble empirical mode decomposition

  • YANG Hong1,2,LI Ya-an1,LI Guo-hui1,2 
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摘要

利用集合经验模态分解方法研究舰船辐射噪声的特征参数提取及分类,对预处理后三种不同类别舰船辐射噪声进行能量分析,讨论其高低频能量差特征参数。计算不同类别、一定样本数量的舰船辐射噪声高低频能量差发现,同类舰船高低频能量差基本处于同一水平,不同类型舰船高低频能量差存在明显差异。结果表明,利用集合经验模态分解方法提取的舰船辐射噪声特征参数对舰船类别具有较好的可分性。可为水下目标信号探测及识别提供参考。

Abstract

Ensemble empirical mode decomposition method has been developed for nonlinear and non-stationary signal. The method can be applied to the feature extraction and classification of ship radiated noise. Three different types of ship radiated noise are chosen to perform energy analysis. After pretreatment, the ship radiated noise is decomposed into several intrinsic mode functions by ensemble empirical mode decomposition, and energy difference between the high and low frequency is extracted and analyzed. The results show that energy difference between the high and low frequency is at the same level for similar ships, but it is obvious difference for different types of ships. Therefore, we conclude that the energy difference between the high and low frequency can be used as a new feature of ship signals. It provides an alternative for detecting and recognizing underwater target signals.
 

关键词

集合经验模态分解 / 舰船辐射噪声 / 高低频能量差 / 特征提取

Key words

ensemble empirical mode decomposition / ship radiated noise / energy difference between the high and low frequency / feature extraction

引用本文

导出引用
杨 宏1,2,李亚安1,李国辉1,2. 基于集合经验模态分解的舰船辐射噪声能量分析[J]. 振动与冲击, 2015, 34(16): 55-59
YANG Hong1,2,LI Ya-an1,LI Guo-hui1,2 . Energy analysis of ship radiated noise based on ensemble empirical mode decomposition[J]. Journal of Vibration and Shock, 2015, 34(16): 55-59

参考文献

[1] 凌青,宋文华,赵春梅,等. 浅海信道中舰船辐射噪声包络线谱传播特性[J]. 中国科学: 物理学 力学 天文学, 2014, 44(2): 134-141.
LENG Qing, SONG Wen-hua, ZHAO Chun-mei, et al. Propagation characteristic of envelope line spectrum of ship radiating noise in shallow water channel[J]. Science China Physics, Mechanics & Astronomy, 2014, 44(2): 134-141.
[2] 吴国清,李靖,陈耀明,等. 舰船噪声识别(I)-总体框架、线谱分析和提取[J]. 声学学报, 1998, 23(5): 394-400.
WU Guo-qing, LI Jing, CHEN Yao-ming, et al. Ship radiated-noise recognition (I) the overall framework, analysis and extraction of line-spectrum[J]. ACTA Acustica, 1998, 23(5): 394-400.
[3] 张岩. 多元统计分析在舰船辐射噪声分类识别中的应用[D].北京:中国科学院声学研究所, 2007.
[4] 章新华,王骥程,林良骥. 基于小波变换的舰船辐射噪声特征提取[J]. 声学学报, 1997, 22(2): 139-144.
ZHANG Xin-hua, WANG Ji-cheng, LIN Liang-ji. Feature extraction of ship radiated noises based on wavelet transform [J]. ACTA Acustica, 1997, 22(2): 139-144.
[5] 李亚安,徐德民,张效民. 舰船噪声信号的混沌特性研究[J].西北工业大学学报, 2001, 19(2): 266-269.
LI Ya-an, XU De-min, ZHANG Xiao-min. Study on chaotic characteristics of the signal of ship radiated noise[J]. Journal of Northwestern Polytechnical University, 2001,19(2):266- 269.
[6] Huang N E, Shen Z, Long S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Royal Society of London Proceedings, 1998, 1971 (454): 903-995.
[7] Wang Z W, Liu J H, Yue C W, et al. The filtering characteristics of HHT and its application in acoustic log waveform signal processing[J]. Applied Geophysics, 2009, 6(1): 8-16.
[8] Roveri N, Carcaterra A. Damage detection in structures undertraveling loads by Hilbert-Huang transform[J]. Mechanical Systems and Signal Processing, 2012, 28(2): 128- 144.
[9] 周宣赤,白春华,林大超,等. HHT分析在地震信号处理中的应用[J]. 控制工程, 2013, 20(1): 141-144.
ZHOU Xuan-chi, BAI Chun-hua, LIN Da-chao, et al. Study on analysis of earthquake signal processing based on HHT[J]. Control Engineering of China, 2013, 20(1): 141-144.
[10] 关晓磊,颜景龙. 爆破振动信号的HHT时频能量谱分析[J].爆炸与冲击, 2012, 32(5): 535-541.
GUAN Xiao-lei, YAN Jing-long. The HHT time-frequency power spectrum analysis of the blasting vibration signal[J]. Explosion and Shock Waves, 2012, 32(5): 535-541.
[11] Yang Hong, Li Guo-hui. Research of noise reduction of chaotic signal based on empirical mode decomposition[J]. Telkomnika, 2014, 12(3): 1881-1886.
[12]胡利萍,宋恩亮,李宝清,等.一种适用于流数据分析的快速EMD算法[J]. 振动与冲击, 2012, 31(8): 116-120.
HU Li-ping, SONG En-liang, LI Bao-qing, et al. A new fast EMD algorithm for streaming data analysis[J]. Journal of Vibration and Shock, 2012, 31(8): 116-120.
[13] Wu Z H, Huang N E. A study of the characteristics of white noise using the empirical mode decomposition method[J].
Proceedings of the Royal Society of London A, 2004,
2046 (460): 1597-1611.
[14] Wu Z H, Huang N E. Ensemble empirical mode decomposition: a noise-assisted data analysis method[J]. Advances in Adaptive Data Analysis, 2009, 1(1): 1-41.
[15] Wang Y H, Yeh C H, Young H W, et al. On the computational complexity of the empirical mode decomposition algorithm[J]. Physica A: Statistical Mechanics and Its Applications, 2014, 400(2): 159-167.

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