Journal of Electrical and Electronic Engineering

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Research of FTRLS Algorithm in Acoustic Signal De-noising

Received: Nov. 16, 2017    Accepted:     Published: Nov. 20, 2017
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Abstract

In the acoustic temperature measurement system, the acoustic emission signal is easily affected by the wind field, the ambient noise and so on during the propagation process. Coupled with its own reflection, diffraction and scattering properties, the sensor receive the acoustic signals that are weak, difficult to identify, and even submerged in the background noise. In order to solve the above problem, this paper combines the principle of adaptive filter, and the FTRLS adaptive filter algorithm is designed to deal with linear frequency modulation signal, and the simulation experiment was carried out by MATLAB software. The results show that the noise-disturbing chirp signal can be effectively restored to a certain extent after denoising.

DOI 10.11648/j.jeee.20170505.15
Published in Journal of Electrical and Electronic Engineering ( Volume 5, Issue 5, October 2017 )
Page(s) 186-191
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

The Acoustic Temperature Measurement System, FTRLS Adaptive Filter Algorithm, Chirp Signal, Denoising

References
[1] Liu Xia, Liu Shi. Research on Temperature Distribution Reconstruction of a Boiler Furnace Based on Acoustic Tomography [J]. Journal of Chinese Society of Power Engineering, 2017, 37(7): 525—532.
[2] Debenjak A, Boškoski P, Musizza B. Fast measurement of proton exchange membrane fuel cell impedance based on pseudo—random binary sequence perturbation signals and continuous wavelet transform [J]. Journal of Power Sources, 2014, 15(254): 112—118.
[3] Hu Zhukuan. Study status and development trend discussion of measuring technology of furnace temperature fields in plant boilers [J]. CHINA MEASUREMENT & TEST, 2015, 41(4): 5—9.
[4] Tian Youjia, Wang wei. A Method of Multi—LFM Signal Detection and Parameter Estimation [J]. Shipboard Electronic Countermeasure, 2016, 39 (3): 45—48.
[5] Wang Mingji, Shi Jianfeng, Li Wanning. Study on Measurement of Acoustic Flying Time Based on Cross—correlation [J]. Electronic Design Engineering, 2016, 24 (15): 102—104.
[6] Wang Dongfeng, Liu Qian. Development of Furnace Temperature Measurement Technology for Utility Boilers [J]. China Measurement & Test, 2014, 40 (3): 8—12.
[7] Wang Jiaofeng, Tian Feng, Tian Jinguang. Research on Reconstruction of Temperature Field of Aeroengine Combustion Chamber Based on Acoustic CT [J]. Journal of Shenyang Aerospace University, 2009, 26 (2): 38—42.
[8] Zhao Xia, Li Rongyan. Study on the Teaching Method of Sampling Theorem and Determining the Sampling Cycle of the System [J]. Industry and Information Technology Education, 2014, 2 (5): 24—29.
[9] Hu Ronghua, Yang Shiyi. Phase optimization in design of imag-rejection mixer [J]. Electronic Design Engineering, 2016, 24(1): 80—81.
[10] Chen Tiantian, Chen Lu, Wang Wei, et al. Weighting adjustable general triangular midpoint subdivision scheme [J]. Computer Integrated Manufacturing Systems, 2017, 23(4): 689—694.
[11] Yu Xinying. The Analysis and Simulation of Adaptive Filtering Algorithms [J]. Shanxi Electronic Technology, 2016, (6): 7—8.
[12] Mahbub U, Fattah SA, Zhu WP. et al. Single—channel acoustic echo cancellation in noise based on gradient—based adaptive filtering [J]. EURASIP Journal on Audio, Speech, and Music Processing, 2014, 2014(1): 1—16.
[13] Ren Zhiyong, Xu Dong. Adaptive Identification of Bilinear Feedback System Based on Least Squares Algorithm [J]. Automation Application, 2017, (3): 36—37.
[14] Jia Dan, Zhang Xing. Research on Time Complexity Measure Method Based on Analysis Method [J]. Journal of Liaoning University of Technology (Natural Science Edition), 2015, 35(4): 231—233.
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    Sun Yanpeng, Zuo Chenmeng. (2017). Research of FTRLS Algorithm in Acoustic Signal De-noising. Journal of Electrical and Electronic Engineering, 5(5), 186-191. https://doi.org/10.11648/j.jeee.20170505.15

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    ACS Style

    Sun Yanpeng; Zuo Chenmeng. Research of FTRLS Algorithm in Acoustic Signal De-noising. J. Electr. Electron. Eng. 2017, 5(5), 186-191. doi: 10.11648/j.jeee.20170505.15

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    AMA Style

    Sun Yanpeng, Zuo Chenmeng. Research of FTRLS Algorithm in Acoustic Signal De-noising. J Electr Electron Eng. 2017;5(5):186-191. doi: 10.11648/j.jeee.20170505.15

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  • @article{10.11648/j.jeee.20170505.15,
      author = {Sun Yanpeng and Zuo Chenmeng},
      title = {Research of FTRLS Algorithm in Acoustic Signal De-noising},
      journal = {Journal of Electrical and Electronic Engineering},
      volume = {5},
      number = {5},
      pages = {186-191},
      doi = {10.11648/j.jeee.20170505.15},
      url = {https://doi.org/10.11648/j.jeee.20170505.15},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.jeee.20170505.15},
      abstract = {In the acoustic temperature measurement system, the acoustic emission signal is easily affected by the wind field, the ambient noise and so on during the propagation process. Coupled with its own reflection, diffraction and scattering properties, the sensor receive the acoustic signals that are weak, difficult to identify, and even submerged in the background noise. In order to solve the above problem, this paper combines the principle of adaptive filter, and the FTRLS adaptive filter algorithm is designed to deal with linear frequency modulation signal, and the simulation experiment was carried out by MATLAB software. The results show that the noise-disturbing chirp signal can be effectively restored to a certain extent after denoising.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - Research of FTRLS Algorithm in Acoustic Signal De-noising
    AU  - Sun Yanpeng
    AU  - Zuo Chenmeng
    Y1  - 2017/11/20
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    N1  - https://doi.org/10.11648/j.jeee.20170505.15
    DO  - 10.11648/j.jeee.20170505.15
    T2  - Journal of Electrical and Electronic Engineering
    JF  - Journal of Electrical and Electronic Engineering
    JO  - Journal of Electrical and Electronic Engineering
    SP  - 186
    EP  - 191
    PB  - Science Publishing Group
    SN  - 2329-1605
    UR  - https://doi.org/10.11648/j.jeee.20170505.15
    AB  - In the acoustic temperature measurement system, the acoustic emission signal is easily affected by the wind field, the ambient noise and so on during the propagation process. Coupled with its own reflection, diffraction and scattering properties, the sensor receive the acoustic signals that are weak, difficult to identify, and even submerged in the background noise. In order to solve the above problem, this paper combines the principle of adaptive filter, and the FTRLS adaptive filter algorithm is designed to deal with linear frequency modulation signal, and the simulation experiment was carried out by MATLAB software. The results show that the noise-disturbing chirp signal can be effectively restored to a certain extent after denoising.
    VL  - 5
    IS  - 5
    ER  - 

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Author Information
  • Department of Electronic Information Engineering, Shenyang Aerospace University, Shenyang, China

  • Department of Electronic Information Engineering, Shenyang Aerospace University, Shenyang, China

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