微弱信号检测的变尺度Duffing振子方法

doi:10.3969/j.issn.0372-2112.2020.04.015

电子学报 ›› 2020, Vol. 48 ›› Issue (4): 734-742.DOI: 10.3969/j.issn.0372-2112.2020.04.015

微弱信号检测的变尺度Duffing振子方法

行鸿彦^1,2, 吴慧^1,2, 刘刚^1,2

1. 南京信息工程大学气象灾害预报预警与评估协同创新中心, 江苏南京 210044;
2. 南京信息工程大学, 江苏省气象探测与信息处理重点实验室, 江苏南京 210044

收稿日期:2018-10-08 修回日期:2019-04-19 出版日期:2020-04-25
- 基金资助:
- 国家自然科学基金 (No.61671248）; 国家重点研发计划 (No.2018YFC1506102）; 江苏省重点研发计划 (No.BE2018719）; 江苏省"信息与通信工程"优势学科计划

Variable-Scale Duffing Oscillator Method for Weak Signal Detection

XING Hong-yan^1,2, WU Hui^1,2, LIU Gang^1,2

1. Collaborative Innovation Center for Meteorological Disaster Prediction and Evaluation, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China;
2. Jiangsu Key Laboratory of Meteorological Detection and Information Processing, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China

Received:2018-10-08 Revised:2019-04-19 Online:2020-04-25 Published:2020-04-25

摘要/Abstract

摘要： 针对强噪声背景下微弱信号检测问题，本文把互补集总经验模式分解（CEEMD）方法和变尺度Duffing振子结合，提出了一种新的微弱信号检测方法.利用CEEMD将复杂含噪信号分解为不同的固有模态函数（IMF），通过Duffing系统分岔图及其变化找到相轨迹变化的临界阈值，实现含噪信号的信息检测.结果表明，本文所提方法不仅可以很好地免疫噪声，而且能有效检测出信噪比低至-73dB的多频率周期信号.

关键词: 微弱信号检测, 混沌, 分岔图, 互补集总经验模式分解方法

Abstract: Aiming at the weak signal detection problem under strong noise background,the weak signal detection principle based on Duffing oscillator is analyzed.Combining the complementary ensemble empirical mode decomposition(CEEMD)method with the variable-scale Duffing oscillator,a new weak signal detection method is proposed.The complex noisy signal is decomposed into different intrinsic mode functions(IMF) by using CEEMD.Through the Duffing system bifurcation diagram and its changes,the critical threshold of the phase trajectory change is found,and the information detection of the noisy signal is realized.The results show that the joint detection method can not only immune noise well,but also effectively detect multi-frequency periodic signals with signal-to-noise ratio as low as -73dB.

Key words: weak signal detection, chaos, bifurcation diagram, complementary ensemble empirical mode decomposition

中图分类号:

TM93

行鸿彦, 吴慧, 刘刚. 微弱信号检测的变尺度Duffing振子方法[J]. 电子学报, 2020, 48(4): 734-742.

XING Hong-yan, WU Hui, LIU Gang. Variable-Scale Duffing Oscillator Method for Weak Signal Detection[J]. Acta Electronica Sinica, 2020, 48(4): 734-742.

参考文献

[1] 孙伟峰,彭玉华.一种改进的非局部平均去噪方法[J].电子学报,2010,38(4):923-928. SUN Wei-feng,PENG Yu-hua.Animproved non-local means de-noising approach[J].Acta Electronica Sinica,2010,38(4):923-928.(in Chinese)
[2] 魏恒东,甘露,李立萍.基于哈密顿量的Duffing振子微弱信号检测[J].电子科技大学学报,2012,41(2):203-207. WEI Heng-dong,GAN Lu,LI Li-ping.Weak signal detection by duffing oscillator based on Hamiltonian[J].Journal of University of Electronic Science and Technology of China,2012,41(2):203-207.(in Chinese)
[3] 毛健美,王莉,胡苏阳,等.混沌扩频多根电缆故障在线同步诊断研究[J].电子学报,2018,46(7):1625-1632. MAO Jian-mei,WANG Li,HU Su-yang,et al.Research on synchronous online diagnosis of multiple cable faults based on chaotic spread spectrum sequence[J].Acta Electronica Sinica,2018,46(7):1625-1632.(in Chinese)
[4] 胡文静,刘志珍,厉志辉.用于微弱信号检测的改进Duffing混沌电路性能分析[J].电机与控制学报,2011,15(9):80-85. HU Wen-jing,LIU Zhi-zheng,LI Zhi-hui.Weak signal detection performance of improved Duffing circuit[J].Electric Machines and Control,2011,15(9):80-85.(in Chinese)
[5] 王慧武,丛超.一种基于Duffing系统的信号检测与参数估计新方法[J].电子学报,2016,44(6):1450-1457. WANG Hui-wu,CONG Chao.A new signal detection and estimation method by using duffing system[J].Acta Electronica Sinica,2016,44(6):1450-1457.(in Chinese)
[6] 关贞珍,郑海起,杨云涛,等.基于经验模态分解和Duffing振子的轴承故障诊断[J].农业机械学报,2010,41(9):214-217. GUAN Zhen-zhen,ZHENG Hai-qi,YANG Yun-tao,et al.Fault diagnosis of bearing based on EMD and duffing oscillator[J].Transactions of the Chinese Society for Agricultural Machinery,2010,41(9):214-217.(in Chinese)
[7] 张刚,李红威.小波-EMD和随机共振级联微弱信号检测[J].电子测量与仪器学报,2018,32(1):57-65. ZHANG Gang,LI Hong-wei.Wavelet-EMD and stochastic resonance cascade weak signal detection[J].Journal of Electronic Measurement and Instrumentation,2018,32(1):57-65.(in Chinese)
[8] 韩建群,石旭东.基于EMD航空发电机定子绕组故障检测方法[J].国外电子测量技术,2016,35(10):34-37+49. HAN Jian-qun,SHI Xu-dong.Detection method for the internal stator winding fault in aircraft based on EMD[J].Foreign Electronic Measurement Tech-nology,2016,35(10):34-37+49.(in Chinese)
[9] 王永生,杜文超,安昕,等.驱动输入白噪声对Duffing振子运动影响分析[J].振动与冲击,2007,(3):131-134+164. WANG Yong-sheng,DU Wen-chao,AN Xing,et al.Analysis of drive input white noise-effect on movement of a duffing oscillator[J].Journal of Vibration and Shock,2007,(3):131-134+164.(in Chinese)
[10] 行鸿彦,朱清清.基于集成经验模态分解的海杂波去噪[J].电子学报,2016,44(1):1-7. XING Hong-yan,ZHU Qing-qing.The sea clutter de-noising based on ensemble empirical mode decomposition[J].Acta Electronica Sinica,2016,44(1):1-7.(in Chinese)
[11] 赵迎,乐友喜,黄健良,等.CEEMD与小波变换联合去噪方法研究[J].地球物理学进展,2015,30(6):2870-2877. ZHAO Ying,LE You-xi,HUANG Jian-liang,et al.CE-EMD and wavelet transform jointed de-noising method[J].Progress in Geophysics,2015,30(6):2870-2877.(in Chinese)
[12] 张明,曾庆军,眭翔,等.基于CEEMD的水下机器人MEMS陀螺降噪方法[J].传感技术学报,2014,27(12):1622-1626. ZHANG Ming,ZENG Qing-jun,GUI Xiang,et al.De-noising method of MEMS Gyro of an underwater vehicle based on CEEMD[J].Chinese Journal of Sensors and Actuators,2014,27(12):1622-1626.(in Chinese)
[13] 张强,行鸿彦.基于EMD方差特性的混沌信号自适应去噪算法[J].电子学报,2015,43(5):901-906. ZHANG Qiang,XING Hong-yan.Adaptive denoising algorithm based on the variance characteristics of EMD[J].Acta Electronica Sinica,2015,43(5):901-906.(in Chinese)
[14] 李国正,张波.基于Duffing振子检测频率未知微弱信号的新方法[J].仪器仪表学报,2017,38(1):181-189. LI Guo-zheng,ZHANG Bo.Novel method for detecting weak signal with unknown frequency based on duffing oscillator[J].Chinese Journal of Scientific Instrument,2017,38(1):181-189.(in Chinese)
[15] 李新杰,胡铁松,郭旭宁,等.不同时间尺度的径流时间序列混沌特性分析[J].水利学报,2013,44(5):515-520. LI Xin-jie,HU Tie-song,GUO Xu-ning,et al.Chaos analysis of runoff time series at different timescales[J].Journal of Hydraulic Engineering,2013,44(5):515-520.(in Chinese)
[16] 赖志慧,冷永刚,孙建桥,等.基于Duffing振子的变尺度微弱特征信号检测方法研究[J].物理学报,2012,61(5):60-68. LAI Zhi-hui,LENG Yong-gang,SUN Jian-qiao,et al.Weak characteristic signal detection based on scale transformation of Duffing oscillator[J].Acta Physica Sinica,2012,61(5):60-68.(in Chinese)
[17] 曾喆昭,周勇,胡凯.基于扩展型Duffing振子的局部放电信号检测方法研究[J].物理学报,2015,64(7):144-150. ZENG Zhe-zhao,ZHOU Yong,HU Kai.Study on partial discharge signals detection by extended Duffing oscillator[J].Acta Physica Sinica,2015,64(7):144-150.(in Chinese)
[18] 赵文礼,范剑,吴敏,等.微弱信号混沌检测的自跟踪扫频控制方法[J].控制理论与应用,2014,31(2):250-255. ZHAO Wen-li,FAN Jian,WU Min,et al.Self-tracing-frequency control in weak signal chaotic detection[J].Control Theory & Applications,2014,31(2):250-255.(in Chinese)
[19] 蔡云龙,吕琛.基于混沌理论的滚动轴承早期故障检测[J].华中科技大学学报(自然科学版),2009,37(S1):187-189. CAI Yun-long,LÜ Chen.Incipient fault detection of rolling bearing based on chaos theory[J].Journal of Huazhong University of Science and Technology (Natural Science Edition),2009,37(S1):187-189.(in Chinese) 行鸿彦(通讯作者) 男,1962年生于山西.1983年于太原理工大学获得学士学位,1990年于吉林大学获得硕士学位,2003年于西安交通大学获得博士学位,现为南京信息工程大学教授、博士生导师,主要研究方向为气象仪器设计与计量,信号检测与处理等. E-mail:xinghy@nuist.edu.cn 吴慧女,1995年生于江苏.2017年于江苏理工学院获得学士学位,现为南京信息工程大学硕士研究生,主要研究方向为仪器仪表技术、信号检测与处理. E-mail:1627986719@qq.com

微弱信号检测的变尺度Duffing振子方法

Variable-Scale Duffing Oscillator Method for Weak Signal Detection

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