2.845

2023影响因子

(CJCR)

  • 中文核心
  • EI
  • 中国科技核心
  • Scopus
  • CSCD
  • 英国科学文摘

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

基于总体平均经验模态分解的主动噪声控制系统研究

罗磊 黄博妍 孙金玮 温良

罗磊, 黄博妍, 孙金玮, 温良. 基于总体平均经验模态分解的主动噪声控制系统研究. 自动化学报, 2016, 42(9): 1432-1439. doi: 10.16383/j.aas.2016.c150433
引用本文: 罗磊, 黄博妍, 孙金玮, 温良. 基于总体平均经验模态分解的主动噪声控制系统研究. 自动化学报, 2016, 42(9): 1432-1439. doi: 10.16383/j.aas.2016.c150433
LUO Lei, HUANG Bo-Yan, SUN Jin-Wei, WEN Liang. A New ANC System Based on Ensemble Empirical Mode Decomposition. ACTA AUTOMATICA SINICA, 2016, 42(9): 1432-1439. doi: 10.16383/j.aas.2016.c150433
Citation: LUO Lei, HUANG Bo-Yan, SUN Jin-Wei, WEN Liang. A New ANC System Based on Ensemble Empirical Mode Decomposition. ACTA AUTOMATICA SINICA, 2016, 42(9): 1432-1439. doi: 10.16383/j.aas.2016.c150433

基于总体平均经验模态分解的主动噪声控制系统研究

doi: 10.16383/j.aas.2016.c150433
基金项目: 

2012航天支撑基金 01320214

国家自然科学基金 61171183

国家自然科学基金 61471140

哈尔滨工业大学科研创新基金 HIT.NSRIF201614

详细信息
    作者简介:

    罗磊 哈尔滨工业大学电气工程及自动化学院博士研究生.主要研究方向为信号与信息处理, 主动噪声控制理论.E-mail:llei@hit.edu.cn

    黄博妍 哈尔滨工业大学电气工程及自动化学院讲师.主要研究方向为语音增强, 主动噪声控制理论.E-mail:byhuang@hit.edu.cn

    温良 哈尔滨工业大学电气工程及自动化学院博士研究生.主要研究方向为自适应信号处理, 主动噪声控制理论.E-mail:lwen@hit.edu.cn

    通讯作者:

    孙金玮 哈尔滨工业大学电气工程及自动化学院教授.主要研究方向为生物医学传感器, 主动噪声控制理论.本文通信作者.E-mail:jwsun@hit.edu.cn

A New ANC System Based on Ensemble Empirical Mode Decomposition

Funds: 

2012 Aerospace Support Fund 01320214

National Natural Science Foundation of China 61171183

National Natural Science Foundation of China 61471140

Natural Scientific Research Innovation Foundation in Harbin Institute of Technology HIT.NSRIF201614

More Information
    Author Bio:

    Ph.D. candidate at the School of Electrical Engineering and Automation, Harbin Institute of Technology. His research interest covers signal and information processing, and active noise control theory.E-mail:

    Lecturer at the School of Electrical Engineering and Automation, Harbin Institute of Technology. Her research interest covers speech enhancement and active noise control theory.E-mail:

    Ph.D. candidate at the School of Electrical Engineering and Automation, Harbin Institute of Technology. His research interest covers adaptive signal processing and active noise control theory.E-mail:

    Corresponding author: SUN Jin-Wei Professor at the School of Electrical Engineering and Automation, Harbin Institute of Technology. His research interest covers biomedical sensors, and active noise control theory. Corresponding author of this paper. E-mail:regnier@ibpc.fr
  • 摘要: 为了提高宽窄带混合噪声的消噪效果,本文提出一种基于总体平均经验模态分解(Ensemble empirical mode decomposition,EEMD)的主动噪声控制(Active noise control,ANC)系统,利用实时EEMD算法逐段将混合噪声分解成若干个固有模态函数(Intrinsic mode functions,IMF)分量.因为这些IMF分量的频带各不相同,所以实现了混合噪声中宽带分量和窄带分量的有效分离,独立进行ANC处理后成功解决了处理混合噪声时带来的“火花”现象,而且避免了传统混合ANC(Hybrid ANC,HANC)系统中频率失调的影响. EEMD算法也是对混合噪声的平稳化处理过程,因此当混合噪声中出现非平稳变化时,本文提出的系统也能保持较好的系统稳定性.通过不同噪声环境下进行仿真分析,提出的ANC系统比HANC系统具有更好的系统稳定性和更小的稳态误差.
  • 图  1  HANC系统

    Fig.  1  HANC system

    图  2  EEMDANC系统

    Fig.  2  EEMDANC system

    图  3  实时EEMD示意图

    Fig.  3  The sketch map of real-time EEMD

    图  4  平稳宽窄带混合噪声系统性能对比

    Fig.  4  Comparisons between systems$'$ performance for stationary mixture noise of wideband and narrowband

    图  5  非平稳宽窄带混合噪声的系统性能对比

    Fig.  5  Comparisons between systems$'$ performance for non-stationary mixture noise of wideband and narrowband

    图  6  排风扇噪声

    Fig.  6  Exhaust fan noise

    图  7  排风扇噪声的消噪结果

    Fig.  7  Noise cancellation results of exhaust fan noise

    图  8  初级噪声和误差噪声的功率谱密度

    Fig.  8  PSD of primary noise and error noise

    图  9  平稳宽窄带混合噪声的EEMD时域图

    Fig.  9  Time domain EEMD view of stationary mixture noise of wideband and narrowband

    图  10  平稳宽窄带混合噪声的EEMD频域图

    Fig.  10  Frequency domain EEMD view of stationary mixture noise of wideband and narrowband

    图  11  非平稳宽窄带混合噪声的EEMD图

    Fig.  11  EEMD view of non-stationary mixture noise of wideband and narrowband

    图  12  混合噪声和EEMD后各分量的Hilbert谱

    Fig.  12  Hilbert spectrum of the mixture noise and the components after EEMD

    表  1  次级路径估计参数设置

    Table  1  Parameters of secondary path estimation

    参数名称 参数值
    初级路径$P(z)$的长度 ${\rm{40 (}}L{\rm{ = 41)}}$
    次级路径$S(z)$的长度 ${\rm{20 (}}M{\rm{ = 21)}}$
    次级路径估计${\hat S}(z)$的长度 ${\rm{30 ( }}\hat M{\rm{ = 31)}}$
    计算步长 0.001
    训练输入信号的方差 $\sigma _{xs}^2(n)= 1$
    训练观测噪声的方差 $\sigma _{vs}^2(n)= 0.1$
    训练次数 10 000
    下载: 导出CSV
  • [1] Kuo S M, Morgan D R. Active noise control: a tutorial review. Proceedings of the IEEE, 1999, 87(6): 943-973 doi: 10.1109/5.763310
    [2] Wu L F, Qiu X J, Guo Y C. A simplified adaptive feedback active noise control system. Applied Acoustics, 2014, 81: 40-46 doi: 10.1016/j.apacoust.2014.02.006
    [3] Xiao Y G, Ikuta A, Ma L Y, Khorasani K. Stochastic analysis of the FXLMS-based narrowband active noise control system. IEEE Transactions on Audio, Speech, and Language Processing, 2008, 16(5): 1000-1014 doi: 10.1109/TASL.2008.921756
    [4] Kajikawa K, Gan W S, Kuo S M. Recent applications and challenges on active noise control. In: Proceedings of the 8th International Symposium on Image and Signal Processing and Analysis. Trieste, Italy: IEEE, 2013. 661-666
    [5] Xiao Y G, Wang J. A new feedforward hybrid active noise control system. IEEE Signal Processing Letters, 2011, 18(10): 591-594 doi: 10.1109/LSP.2011.2164067
    [6] Kuo S M, Puvvala A B. Effects of frequency separation in periodic active noise control systems. IEEE Transactions on Audio, Speech, and Language Processing, 2006, 14(5): 1857-1866 doi: 10.1109/TSA.2005.858524
    [7] Jeon H J, Chang T G, Kuo S M. Analysis of frequency mismatch in narrowband active noise control. IEEE Transactions on Audio, Speech, and Language Processing, 2010, 18(6): 1632-1642 doi: 10.1109/TASL.2009.2038815
    [8] Xiao Y G, Ma L Y, Ward R K. Fast RLS Fourier analyzers capable of accommodating frequency mismatch. Signal Processing, 2007, 87(9): 2197-2212 doi: 10.1016/j.sigpro.2007.03.003
    [9] Xiao Y G, Ma L Y, Khorasani K, Ikuta A, Xu L. A filtered-X RLS based narrowband active noise control system in the presence of frequency mismatch. In: Proceedings of the 2005 IEEE International Symposium on Circuits and Systems. Kobe, Japan: IEEE, 2005. 260-263
    [10] 黄博妍, 常林, 马亚平, 孙金玮, 魏国.一种应对非平稳频率失调的窄带主动噪声控制系统.自动化学报, 2015, 41(1): 186-193 http://www.aas.net.cn/CN/abstract/abstract18597.shtml

    Huang Bo-Yan, Chang Lin, Ma Ya-Ping, Sun Jin-Wei, Wei Guo. A new narrowband ANC system against nonstationary frequency mismatch. Acta Automatica Sinica, 2015, 41(1): 186-193 http://www.aas.net.cn/CN/abstract/abstract18597.shtml
    [11] Huang N E, Shen Z, Long S R, Wu M C, Shih H H, Zheng Q A, Yen N C, Tung C C, Liu H H. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 1998, 454(1971): 903-995 doi: 10.1098/rspa.1998.0193
    [12] Flandrin P, Rilling G, Goncalves P. Empirical mode decomposition as a filter bank. IEEE Signal Processing Letters, 2004, 11(2): 112-114 doi: 10.1109/LSP.2003.821662
    [13] 曲从善, 路廷镇, 谭营.一种改进型经验模态分解及其在信号消噪中的应用.自动化学报, 2010, 36(1): 67-73 doi: 10.3724/SP.J.1004.2010.00067

    Qu Cong-Shan, Lu Ting-Zhen, Tan Ying. A modified empirical mode decomposition method with applications to signal de-noising. Acta Automatica Sinica, 2010, 36(1): 67-73 doi: 10.3724/SP.J.1004.2010.00067
    [14] 康春玉, 章新华.一种基于EMD和ANC技术的自适应降噪方法.系统工程与电子技术, 2008, 30(5): 810-812

    Kang Chun-Yu, Zhang Xin-Hua. Adaptive noise reduction method based on EMD and ANC. Systems Engineering and Electronics, 2008, 30(5): 810-812
    [15] Wu Z H, Huang N E. Ensemble empirical mode decomposition: a noise-assisted data analysis method. Advances in Adaptive Data Analysis, 2009, 1(1): 1-41 doi: 10.1142/S1793536909000047
    [16] Wang Y H, Yeh C H, Vincent Young H-W, Hu K, Lo M-T. On the computational complexity of the empirical mode decomposition algorithm. Physica A: Statistical Mechanics and its Applications, 2014, 400: 159-162 doi: 10.1016/j.physa.2014.01.020
    [17] 汤键, 柴天佑, 丛秋梅, 苑明哲, 赵立杰, 刘卓, 余文.基于EMD和选择性集成学习算法的磨机负荷参数软测量.自动化学报, 2014, 40(9): 1853-1866 http://www.aas.net.cn/CN/abstract/abstract18454.shtml

    Tang Jian, Chai Tian-You, Cong Qiu-Mei, Yuan Ming-Zhe, Zhao Li-Jie, Liu Zhuo, Yu Wen. Soft sensor approach for modeling mill load parameters based on EMD and selective ensemble learning algorithm. Acta Automatica Sinica, 2014, 40(9): 1853-1866 http://www.aas.net.cn/CN/abstract/abstract18454.shtml
  • 加载中
图(12) / 表(1)
计量
  • 文章访问数:  2122
  • HTML全文浏览量:  247
  • PDF下载量:  954
  • 被引次数: 0
出版历程
  • 收稿日期:  2015-07-07
  • 录用日期:  2016-01-15
  • 刊出日期:  2016-09-01

目录

    /

    返回文章
    返回