Feature Extraction of Ship-Radiated Noise Based on Permutation Entropy of the Intrinsic Mode Function with the Highest Energy

被引:62
作者
Li, Yu-Xing [1 ]
Li, Ya-An [1 ]
Chen, Zhe [1 ]
Chen, Xiao [1 ]
机构
[1] Northwestern Polytech Univ, Sch Marine Sci & Technol, Xian 710072, Peoples R China
基金
中国国家自然科学基金;
关键词
empirical mode decomposition; intrinsic mode function; permutation entropy; multi-scale permutation entropy; feature extraction; FAULT-DIAGNOSIS; TIME-SERIES; DECOMPOSITION; DEPTH; EEG;
D O I
10.3390/e18110393
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
In order to solve the problem of feature extraction of underwater acoustic signals in complex ocean environment, a new method for feature extraction from ship-radiated noise is presented based on empirical mode decomposition theory and permutation entropy. It analyzes the separability for permutation entropies of the intrinsic mode functions of three types of ship-radiated noise signals, and discusses the permutation entropy of the intrinsic mode function with the highest energy. In this study, ship-radiated noise signals measured from three types of ships are decomposed into a set of intrinsic mode functions with empirical mode decomposition method. Then, the permutation entropies of all intrinsic mode functions are calculated with appropriate parameters. The permutation entropies are obviously different in the intrinsic mode functions with the highest energy, thus, the permutation entropy of the intrinsic mode function with the highest energy is regarded as a new characteristic parameter to extract the feature of ship-radiated noise. After that, the characteristic parametersnamely, the energy difference between high and low frequency, permutation entropy, and multi-scale permutation entropyare compared with the permutation entropy of the intrinsic mode function with the highest energy. It is discovered that the four characteristic parameters are at the same level for similar ships, however, there are differences in the parameters for different types of ships. The results demonstrate that the permutation entropy of the intrinsic mode function with the highest energy is better in separability as the characteristic parameter than the other three parameters by comparing their fluctuation ranges and the average values of the four characteristic parameters. Hence, the feature of ship-radiated noise can be extracted efficiently with the method.
引用
收藏
页数:15
相关论文
共 24 条
[1]  
Aziz W., 2005, P PAK SECT MULT C IN
[2]   Permutation entropy: A natural complexity measure for time series [J].
Bandt, C ;
Pompe, B .
PHYSICAL REVIEW LETTERS, 2002, 88 (17) :4
[3]   A technique for distinguishing dynamical species in the temperature time series of north China [J].
Hou Wei ;
Feng Guo-Ling ;
Dong Wen-Jie ;
Li Jian-Ping .
ACTA PHYSICA SINICA, 2006, 55 (05) :2663-2668
[4]   High-Speed Spindle Fault Diagnosis with the Empirical Mode Decomposition and Multiscale Entropy Method [J].
Hsieh, Nan-Kai ;
Lin, Wei-Yen ;
Young, Hong-Tsu .
ENTROPY, 2015, 17 (04) :2170-2183
[5]   The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis [J].
Huang, NE ;
Shen, Z ;
Long, SR ;
Wu, MLC ;
Shih, HH ;
Zheng, QN ;
Yen, NC ;
Tung, CC ;
Liu, HH .
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 1998, 454 (1971) :903-995
[6]  
Liu Shen, 2014, Computer Engineering and Applications, V50, P203, DOI 10.3778/j.issn.1002-8331.1207-0213
[7]  
Lu Yang, 2009, 2009 4th IEEE Conference on Industrial Electronics and Applications, P3682, DOI 10.1109/ICIEA.2009.5138843
[8]  
[秦娜 Qin Na], 2015, [振动、测试与诊断, Journal of Vibration, Measurement and Diagnosis], V35, P885
[9]   Application of the Permutation Entropy over the Heart Rate Variability for the Improvement of Electrocardiogram-based Sleep Breathing Pause Detection [J].
Ravelo-Garcia, Antonio G. ;
Navarro-Mesa, Juan L. ;
Casanova-Blancas, Ubay ;
Martin-Gonzalez, Sofia ;
Quintana-Morales, Pedro ;
Guerra-Moreno, Ivan ;
Canino-Rodriguez, Jose M. ;
Hernandez-Perez, Eduardo .
ENTROPY, 2015, 17 (03) :914-927
[10]   Application of Entropy Measures on Intrinsic Mode Functions for the Automated Identification of Focal Electroencephalogram Signals [J].
Sharma, Rajeev ;
Pachori, Ram Bilas ;
Acharya, U. Rajendra .
ENTROPY, 2015, 17 (02) :669-691