Research on noise reduction method for ship radiate noise based on secondary decomposition

被引:31
作者
Li, Guohui [1 ]
Bu, Wenjia [1 ]
Yang, Hong [1 ]
机构
[1] Xian Univ Posts & Telecommun, Sch Elect Engn, Xian 710121, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Combined secondary optimization; decomposition; Differential phase diagram; Dynamic interval threshold; Ship radiated noise; EMPIRICAL MODE DECOMPOSITION; APPROXIMATE ENTROPY; SIGNAL; SPECTRUM;
D O I
10.1016/j.oceaneng.2022.113412
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Underwater acoustic signal denoising is of great significance for the accurate identification of underwater targets, the research of military detection equipment and the monitoring of marine ecological environment. In this paper, a new denoising method for ship radiated noise based on combined secondary optimization decomposition model, amplitude-aware permutation entropy, dynamic interval threshold filtering and mutual information is proposed. Compared with one-time decomposition, the proposed method can better restore the waveform characteristics of the original signal and filter out the mixed residual noise. In addition, this paper discoveries the influence of differential operation on phase diagram morphology under high signal-to-noise ratio. The experimental results show that the differential phase diagram can show the weak noise contained in the signal with high signal-to-noise ratio. This new discovery has been applied to the evaluation of noise reduction effect of underwater acoustic signal for the first time.
引用
收藏
页数:21
相关论文
共 56 条
[1]   Boundary layer noise subtraction in hydrodynamic tunnel using robust principal component analysis [J].
Amailland, Sylvain ;
Thomas, Jean-Hugh ;
Pezerat, Charles ;
Boucheron, Romuald .
JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 2018, 143 (04) :2152-2163
[2]   Application of adaptive local iterative filtering and approximate entropy to vibration signal denoising of hydropower unit [J].
An, Xueli ;
Li, Chaoshun ;
Zhang, Fei .
JOURNAL OF VIBROENGINEERING, 2016, 18 (07) :4299-4311
[3]   Amplitude-aware permutation entropy: Illustration in spike detection and signal segmentation [J].
Azami, Hamed ;
Escudero, Javier .
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2016, 128 :40-51
[4]   Permutation entropy: A natural complexity measure for time series [J].
Bandt, C ;
Pompe, B .
PHYSICAL REVIEW LETTERS, 2002, 88 (17) :4
[5]   A New Joint Denoising Algorithm for High-G Calibration of MEMS Accelerometer Based on VMD-PE-Wavelet Threshold [J].
Cao, Huiliang ;
Zhang, Zekai ;
Zheng, Yu ;
Guo, Hao ;
Zhao, Rui ;
Shi, Yunbo ;
Chou, Xiujian .
SHOCK AND VIBRATION, 2021, 2021
[6]   Characterization of surface EMG signal based on fuzzy entropy [J].
Chen, Weiting ;
Wang, Zhizhong ;
Xie, Hongbo ;
Yu, Wangxin .
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2007, 15 (02) :266-272
[7]  
[陈旭升 Chen Xusheng], 2021, [测绘科学, Science of Surveying and Mapping], V46, P48
[8]  
Deering R, 2005, INT CONF ACOUST SPEE, P485
[9]   Variational Mode Decomposition [J].
Dragomiretskiy, Konstantin ;
Zosso, Dominique .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2014, 62 (03) :531-544
[10]  
Guo F, 2022, J TEST MEAS TECHNOL, V36, P117