基于自适应傅里叶分解的船舶轴频电磁场信号提取

徐震寰; 吴永飞; 裴建新

doi:10.11993/j.issn.2096-3920.2023-0049

基于自适应傅里叶分解的船舶轴频电磁场信号提取

doi: 10.11993/j.issn.2096-3920.2023-0049

1.
太原理工大学计算机科学与技术学院(大数据学院), 山西太原, 030024
2.
中国海洋大学海洋地球科学学院, 山东青岛, 266100
3.
中国海洋大学海底科学与探测技术教育部重点实验室, 山东青岛, 266100

基金项目: 山西省基础研究计划(自由探索类青年科学研究项目)项目资助(202103021223050)

详细信息

作者简介:
徐震寰(1989-), 男, 博士, 讲师, 主要研究方向为海洋电磁信号处理

中图分类号: U674.7; TJ630.34
计量
- 文章访问数: 210
- HTML全文浏览量: 73
- PDF下载量: 46
- 被引次数: 0
出版历程
- 收稿日期: 2023-05-15
- 修回日期: 2023-06-16
- 录用日期: 2023-07-13
- 网络出版日期: 2023-07-25

Extraction of Shaft-Rate Electromagnetic Field of Ships Based on Adaptive Fourier Decomposition

1.
College of Computer Science and Technology(College of Data Science), Taiyuan University of Technology, Taiyuan 030024, China
2.
College of Marine Geosciences, Ocean University of China, Qingdao 266100, China
3.
Key Laboratory of Submarine Geosciences and Prospecting Techniques of Ministry of Education, Ocean University of China, Qingdao 266100, China

摘要

摘要: 船舶轴频电磁场是水面船舶及水下航行器非常关键的特征, 然而由于静态电磁场的存在, 大大降低了轴频电磁场的信噪比。为实现低信噪比情况下微弱轴频电磁场信号的有效检测, 文中提出一种基于自适应傅里叶分解的信号提取方法, 可以将复杂非平稳信号自低频到高频自适应地分解为一系列具有瞬时频率的单分量之和的形式。通过分别处理仿真和实测数据, 结果表明, 该算法能够克服短时傅里叶变换、小波变换及经验模态分解等方法的缺点, 可快速有效地提取到轴频电磁场信号, 进而为后续船舶及水下航行器的定位追踪提供参考。
- 船舶 /
- 轴频电磁场 /
- 自适应傅里叶分解 /
- 信号提取
Abstract: The shaft-rate electromagnetic field is a crucial feature of ships and undersea vehicles. However, due to the presence of static electromagnetic fields, the signal-to-noise ratio of the shaft-rate electromagnetic fields is greatly reduced. To effectively detect weak shaft-rate electromagnetic field signals under low signal-to-noise ratio conditions, this paper proposed a signal extraction method based on adaptive Fourier decomposition(AFD). It could adaptively decompose complex non-stationary signals from low frequency to high frequency into a series of single components with instantaneous frequency. Through simulation and measured data processing, the results show that this algorithm can overcome the shortcomings of methods such as short-time Fourier transform, wavelet transform, and empirical mode decomposition. It can quickly and effectively extract shaft-rate electromagnetic field signals, thereby providing a reference for positioning and tracking other ships and undersea vehicles.
- ship /
- shift-rate electromagnetic field /
- adaptive Fourier decomposition /
- signal extraction

HTML全文

图 1 AFD信号分解过程

Figure 1. Signal decomposition by AFD

下载: 全尺寸图片幻灯片

图 2 仿真信号波形及AFD重构结果

Figure 2. Simulation signal waveform and AFD reconstruction results

下载: 全尺寸图片幻灯片

图 3 基于AFD提取实测轴频电场信号流程图

Figure 3. Flow chart of extracting measured shaft-rate electric field signals based on AFD

下载: 全尺寸图片幻灯片

图 4 实测轴频电磁场提取前后时频图

Figure 4. Time-frequency spectra before and after extracting shaft-rate electromagnetic field

下载: 全尺寸图片幻灯片

图 5 基于EMD提取的轴频电磁场及其Hilbert谱

Figure 5. Shaft-rate electromagnetic field and its Hilbert spectrum extracted based on EMD

下载: 全尺寸图片幻灯片

参考文献(20)

[1]	Shao G, Li Y. Numerical simulation and analysis of electromagnetic fields induced by a moving ship based on a three-layer geoelectric model[J]. Journal of Ocean University of China, 2020, 19(6): 83-90.
[2]	张岳, 胡祥云, 韩波. 我国轴频电场研究现状[J]. 地球物理学进展, 2022, 37(3): 1342-1351. doi: 10.6038/pg2022FF0278 Zhang Yue, Hu Xiangyun, Han Bo. Research status of shaft-rate electric field in China[J]. Progress in Geophysics, 2022, 37(3): 1342-1351. doi: 10.6038/pg2022FF0278
[3]	卢新城, 龚沈光, 刘胜道, 等. 舰船极低频电场的产生机理及其防护[J]. 海军工程大学学报, 2003, 15(6): 70-74. doi: 10.3969/j.issn.1009-3486.2003.06.018 Lu Xincheng, Gong Shenguang, Liu Shengdao, et al. Generation mechanism of ship’s ELFE and its protection[J]. Journal of Naval University of Engineering, 2003, 15(6): 70-74. doi: 10.3969/j.issn.1009-3486.2003.06.018
[4]	胡鹏, 贾亦卓, 龚沈光. 基于1.5维谱的船舶轴频电场信号实时检测[J]. 海军工程大学学报, 2012, 24(2): 33-37. doi: 10.3969/j.issn.1009-3486.2012.02.008 Hu Peng, Jia Yizhuo, Gong Shenguang. Real-time detection of ship shaft-rate electric field signal based on 1.5-dimension spectrum[J]. Journal of Naval University of Engineering, 2012, 24(2): 33-37. doi: 10.3969/j.issn.1009-3486.2012.02.008
[5]	李松, 石敏, 杜鑫. 舰船轴频电场数据的采集与处理研究[J]. 舰船科学技术, 2015, 37(12): 100-103. doi: 10.3404/j.issn.1672-7649.2015.12.020 Li Song, Shi Min, Du Xin. Data acquisition and processing for the shaft-rate electric field of a ship[J]. Ship Science and Technology, 2015, 37(12): 100-103. doi: 10.3404/j.issn.1672-7649.2015.12.020
[6]	徐震寰, 李予国, 罗鸣. 船舶轴频电磁场信号的海底测量及其特性分析[J]. 哈尔滨工程大学学报, 2018, 39(4): 652-657. doi: 10.11990/jheu.201612066 Xu Zhenhuan, Li Yuguo, Luo Ming. Seabed survey and property analysis of ship’s shaft-rate electromagnetic signal[J]. Journal of Harbin Engineering University, 2018, 39(4): 652-657. doi: 10.11990/jheu.201612066
[7]	赵文春, 姜润翔, 喻鹏, 等. 基于轴频电场线谱特征的目标检测及识别[J]. 兵工学报, 2020, 41(6): 1165-1171. doi: 10.3969/j.issn.1000-1093.2020.06.013 Zhao Wenchun, Jiang Runxiang, Yu Peng, et al. Detection and identification of ship shaft-rate electric field based on line-spectrum characteristics[J]. Acta Armamentarii, 2020, 41(6): 1165-1171. doi: 10.3969/j.issn.1000-1093.2020.06.013
[8]	包中华, 于仕财, 龚沈光. 基于小波包分解和滑动功率谱的舰船轴频电场信号检测[J]. 海军航空工程学院学报, 2012, 27(3): 257-262. Bao Zhonghua, Yu Shicai, Gong Shenguang. Detection of ship shaft-rate electric field signals based on wavelet packet decomposition and sliding PSD[J]. Journal of Naval Aeronautical and Astronautical University, 2012, 27(3): 257-262.
[9]	贾亦卓, 姜润翔, 龚沈光. 基于小波尺度相关的船舶轴频电场检测方法[J]. 华中科技大学学报(自然科学版), 2013, 41(3): 25-29. doi: 10.13245/j.hust.2013.03.008 Jia Yizhuo, Jiang Runxiang, Gong Shenguang. Detection method of ship shaftrate electric field signal using scale correlation in wavelet domain[J]. Journal of Huazhong University of Science and Technology(Natural Science Edition), 2013, 41(3): 25-29. doi: 10.13245/j.hust.2013.03.008
[10]	贾亦卓, 姜润翔, 龚沈光. 基于小波模极大值的船舶轴频电场检测算法研究[J]. 兵工学报, 2013b, 34(5): 579-584. Jia Yizhuo, Jiang Runxiang, Gong Shenguang. Research on wavelet modulus maximum-based detection algorithm of ship’s shaft-rate electric field[J]. Acta Armamentarii, 2013b, 34(5): 579-584.
[11]	贾亦卓, 姜润翔, 龚沈光. 基于小波模极大值能量的船舶轴频电场检测[J]. 电子学报, 2014, 42(3): 592-596. doi: 10.3969/j.issn.0372-2112.2014.03.026 Jia Yizhuo, Jiang Runxiang, Gong Shenguang. Detection of ship shaft-rate electric field signal based on wavelet modulus maximum power[J]. Acta Electronica Sinica, 2014, 42(3): 592-596. doi: 10.3969/j.issn.0372-2112.2014.03.026
[12]	马育锋, 龚沈光, 姜润翔, 等. 基于小波变换的目标信号检测方法[J]. 数据采集与处理, 2009, 24(6): 789-791. doi: 10.3969/j.issn.1004-9037.2009.06.017 Ma Yufeng, Gong Shenguang, Jiang Runxiang, et al. Detection method for targe signal based on wavelet transform[J]. Journal of Data Acquisition & Processing, 2009, 24(6): 789-791. doi: 10.3969/j.issn.1004-9037.2009.06.017
[13]	程锐, 姜润翔, 龚沈光. 基于EMD和4阶累积量的船舶轴频电场线谱提取[J]. 舰船科学技术, 2016, 38(1): 94-98. doi: 10.3404/j.issn.1672-7649.2016.1.020 Cheng Rui, Jiang Runxiang, Gong Shenguang. Extraction of line spectrum of the ship shaft-rate electric field based on EMD and fourth-order cumulan[J]. Ship Science and Technology, 2016, 38(1): 94-98. doi: 10.3404/j.issn.1672-7649.2016.1.020
[14]	吴亮, 赵哲, 苏建业, 等. 基于Hilbert-Huang变换的轴频电场信号检测方法[J]. 舰船电子工程, 2019, 39(4): 138-142. doi: 10.3969/j.issn.1672-9730.2019.04.031 Wu Liang, Zhao Zhe, Su Jianye, et al. Detection of the shaft rate electric field based on the Hilbert-Huang transform[J]. Ship Electronic Engineering, 2019, 39(4): 138-142. doi: 10.3969/j.issn.1672-9730.2019.04.031
[15]	Qian T, Wang Y, Dang P. Adaptive decomposition into mono-components[J]. Advances in Adaptive Data Analysis, 2009, 1(4): 703-709. doi: 10.1142/S1793536909000278
[16]	Qian T, Zhang L, Li Z. Algorithm of adaptive fourier decomposition[J]. IEEE Transactions on Signal Processing, 2011, 59(12): 5899-5906. doi: 10.1109/TSP.2011.2168520
[17]	Mai W, Dang P, Zhang L, et al. Consecutive minimum phase expansion of physically realizable signals with applications[J]. Mathematical Methods in the Applied Sciences, 2016, 39(1): 62-72. doi: 10.1002/mma.3460
[18]	Tan C, Zhang L, Wu H. A novel blaschke unwinding adaptive-Fourier-decomposition-based signal compression algorithm with application on ECG signals[J]. IEEE Journal of Biomedical and Health Informatics, 2018, 23(2): 672-682.
[19]	王赛飞, 方勇, 王军华. 利用自适应傅里叶分解的非平稳无线信道的时频表示[J]. 信号处理, 2018, 34(6): 749-755. doi: 10.16798/j.issn.1003-0530.2018.06.014 Wang Saifei, Fang Yong, Wang Junhua. Time-Frequency representation for non-stationary wireless channel using adaptive Fourier decomposition[J]. Journal of Signal Processing, 2018, 34(6): 749-755. doi: 10.16798/j.issn.1003-0530.2018.06.014
[20]	郑近德, 潘海洋, 程军圣, 等. 基于自适应经验傅里叶分解的机械故障诊断方法[J]. 机械工程学报, 2020, 56(9): 125-136. doi: 10.3901/JME.2020.09.125 Zheng Jinde, Pan Haiyang, Cheng Junsheng, et al. Adaptive empirical Fourier decomposition based mechanical fault diagnoise method[J]. Journal of mechanical engineering, 2020, 56(9): 125-136. doi: 10.3901/JME.2020.09.125