| Peer-Reviewed

An Improved Adaptive Time Difference Estimation Method Based on Median Filter in Impulse Environment

Received: 16 August 2021     Accepted: 11 September 2021     Published: 14 September 2021
Views:       Downloads:
Abstract

Boiler tube burst is the main reason for the unplanned shutdown of thermal power plants. The time difference can be estimated and analyzed by the acoustic signal generated when the boiler tube leaks, and the time difference can be converted into a distance difference to locate the leakage point. The accuracy of positioning depends on the accuracy of the time difference estimation, and the various background noises produced by the complex production environment of the boiler and the impulse noise generated by the uncertain factors in the signal acquisition circuit have a non-negligible effect on the accuracy of the time difference estimation. Aiming at the problem that the signal does not have obvious second-order statistics in the environment of impulse noise, a Wiener weighted adaptive time difference estimation method based on median filtering is proposed. First, the median filter is used to remove the impulse points in the noise to make it obey the normal distribution and have second-order statistics; Next, select the generalized correlation method based on the Wiener weighting function of linear minimum mean square error to eliminate the influence of noise; Finally, according to the characteristics of the generalized correlation method that relies on the prior knowledge of the signal but the ability to suppress noise and the characteristics of the adaptive method that the ability to suppress noise is weak but does not rely on the prior knowledge of the signal, the two methods are combined to form a Wiener-weighted generalized correlation and its adaptive method. Simulation experiments prove that the Wiener weighted adaptive time difference estimation method based on median filtering has better estimation performance under impulsive noise than the adaptive minimum average p-norm method based on fractional low-order statistics.

Published in International Journal of Information and Communication Sciences (Volume 6, Issue 3)
DOI 10.11648/j.ijics.20210603.13
Page(s) 66-74
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), 2021. Published by Science Publishing Group

Keywords

Median Filter, Impulse Noise, Time Difference Estimation, Adaptive

References
[1] WANG Hongyan, WANG Hongyan, PEI Bingnan, “Matrix Completion Based Second Order Statistic Reconstruction DOA Estimation Method,” Journal of Electronics & Information Technology. DaLian vol. 2018, 40 (6), pp. 1383–1389.
[2] Li JL, Zou SY, Gu B, Fang JC, “Adaptive two-filter smoothing based on second-order divided difference filter for distributed position and orientation system,” Science China-Information Sciences. Vol. 2019, 62 (9).
[3] Meng L, li XH, Zhang WG, Liu DZ, “The generalized cross-correlation Method for time delay estimation of infrasound signal,” IMCCC. Qinghuangdao. VOL. 2015, pp. 1320-1323.
[4] Han Zheng Xing, Qiao Yao Hua, LI Bing Bing, and Chen Da Hao, Wang Xin. De-noising method of transmission line laser ranging signal based on median filtering and improved lifting wavelet [J]. Power System & Automation, 2019, 41 (2): 45-48.
[5] Qiu Tian Shuang, Zhuang Xu Xiu and Li Xiao Bing, Y. M. Sun. Statistical signal process—non gaussian signal processing and its application [M]. Beijing: Publishing House of Electronics Industry, 2004.
[6] LIU Ye, “Research on Modeling non-Gaussian Reverberation Using SαS Distribution and its Application,” Changsha: Graduate School of National University of Defense Technology, 2013. 4.
[7] Ishikawa A, Tajima H, Fukushima N, “Hailde implementation of weighted median filter,” Jan, IWAIT 2020, vol, 11515.
[8] Hu Xiaofeng, Liu Weidong, Wang Lei, Wei Ming, Zhang Yue, “Time-delay estimation of corona discharge radiation signal based on generalized cross correlation,” High Power Laser and Particle Beams. Shijiazhuang. Vol. 2018, 30 (1), pp. 50-54.
[9] Huo Yuan-Lian, Wang Dan-Feng, Long Xiao-Qiang, Lian Pei-Jun, “Kernel adaptive filtering algorithm based on Softplus function under non-Gaussian impulse interference,” Acta Physica Sinica. Lanzhou, Vol. 2020, 70 (2), pp. 409-415.
[10] WANG Bin, HOU Yuesheng, “Extraction of Target Propeller Features in Alpha Distribution Noise,” Journal of Electronics & Information Technology. Zhengzhou. Vol. 2020, 42 (10), pp. 2478-2484.
[11] Zhang Wen Bo, Liang Chen, and Gao Xin. A median filtering algorithm design based on multi-level thresholds [J]. Computer Age, 2020, vol. 5: 9-12.
[12] WANG Zhendong, GUI Yuchen, SUN Wei, MA Hongliang. “Improved Wavelet Domain Wiener Filter Based on Multi-direction Weighted,” Journal of China West Normal University (Natural Science). Vol. 2017, 38 (2), pp. 222-226.
[13] ZHU Chao, QU Xiao-xu, LOU Jing-yi. “Time-Delay Estimation Algorithm based on Generalized Cross-Correlation,” Communications Technology. Vol. 2018, 51 (5), pp. 1030-1035.
[14] WEI Wenliang, MAO Yulong. “Cross-correlation Time Delay Estimation Optimization Algorithm Based on LMS Adaptive Filtering,” Electronic Science and Technology. Vol. 2020, 33 (6), pp. 29-34.
[15] TANG Li-han, XIE Xian-zhong, LEI Wei-jia. “New Time Delay Estimation Method Based on the Fractional Lower Order Statistics and Function Transformation in Spike Impulsive Noise Environment,” Science Technology and Engineering. Vol. 2015, 15 (20), pp. 58-65.
[16] CHEN Si-jia, ZHAO Zhi-jin. “Variable step-size reweighted zero attracting least mean p-norm algorithm for sparse system identification,” Control Theory & Applications. Vol. 2020, 37 (5), pp. 1103-1108.
Cite This Article
  • APA Style

    Hang Liu, Wenhong Liu. (2021). An Improved Adaptive Time Difference Estimation Method Based on Median Filter in Impulse Environment. International Journal of Information and Communication Sciences, 6(3), 66-74. https://doi.org/10.11648/j.ijics.20210603.13

    Copy | Download

    ACS Style

    Hang Liu; Wenhong Liu. An Improved Adaptive Time Difference Estimation Method Based on Median Filter in Impulse Environment. Int. J. Inf. Commun. Sci. 2021, 6(3), 66-74. doi: 10.11648/j.ijics.20210603.13

    Copy | Download

    AMA Style

    Hang Liu, Wenhong Liu. An Improved Adaptive Time Difference Estimation Method Based on Median Filter in Impulse Environment. Int J Inf Commun Sci. 2021;6(3):66-74. doi: 10.11648/j.ijics.20210603.13

    Copy | Download

  • @article{10.11648/j.ijics.20210603.13,
      author = {Hang Liu and Wenhong Liu},
      title = {An Improved Adaptive Time Difference Estimation Method Based on Median Filter in Impulse Environment},
      journal = {International Journal of Information and Communication Sciences},
      volume = {6},
      number = {3},
      pages = {66-74},
      doi = {10.11648/j.ijics.20210603.13},
      url = {https://doi.org/10.11648/j.ijics.20210603.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijics.20210603.13},
      abstract = {Boiler tube burst is the main reason for the unplanned shutdown of thermal power plants. The time difference can be estimated and analyzed by the acoustic signal generated when the boiler tube leaks, and the time difference can be converted into a distance difference to locate the leakage point. The accuracy of positioning depends on the accuracy of the time difference estimation, and the various background noises produced by the complex production environment of the boiler and the impulse noise generated by the uncertain factors in the signal acquisition circuit have a non-negligible effect on the accuracy of the time difference estimation. Aiming at the problem that the signal does not have obvious second-order statistics in the environment of impulse noise, a Wiener weighted adaptive time difference estimation method based on median filtering is proposed. First, the median filter is used to remove the impulse points in the noise to make it obey the normal distribution and have second-order statistics; Next, select the generalized correlation method based on the Wiener weighting function of linear minimum mean square error to eliminate the influence of noise; Finally, according to the characteristics of the generalized correlation method that relies on the prior knowledge of the signal but the ability to suppress noise and the characteristics of the adaptive method that the ability to suppress noise is weak but does not rely on the prior knowledge of the signal, the two methods are combined to form a Wiener-weighted generalized correlation and its adaptive method. Simulation experiments prove that the Wiener weighted adaptive time difference estimation method based on median filtering has better estimation performance under impulsive noise than the adaptive minimum average p-norm method based on fractional low-order statistics.},
     year = {2021}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - An Improved Adaptive Time Difference Estimation Method Based on Median Filter in Impulse Environment
    AU  - Hang Liu
    AU  - Wenhong Liu
    Y1  - 2021/09/14
    PY  - 2021
    N1  - https://doi.org/10.11648/j.ijics.20210603.13
    DO  - 10.11648/j.ijics.20210603.13
    T2  - International Journal of Information and Communication Sciences
    JF  - International Journal of Information and Communication Sciences
    JO  - International Journal of Information and Communication Sciences
    SP  - 66
    EP  - 74
    PB  - Science Publishing Group
    SN  - 2575-1719
    UR  - https://doi.org/10.11648/j.ijics.20210603.13
    AB  - Boiler tube burst is the main reason for the unplanned shutdown of thermal power plants. The time difference can be estimated and analyzed by the acoustic signal generated when the boiler tube leaks, and the time difference can be converted into a distance difference to locate the leakage point. The accuracy of positioning depends on the accuracy of the time difference estimation, and the various background noises produced by the complex production environment of the boiler and the impulse noise generated by the uncertain factors in the signal acquisition circuit have a non-negligible effect on the accuracy of the time difference estimation. Aiming at the problem that the signal does not have obvious second-order statistics in the environment of impulse noise, a Wiener weighted adaptive time difference estimation method based on median filtering is proposed. First, the median filter is used to remove the impulse points in the noise to make it obey the normal distribution and have second-order statistics; Next, select the generalized correlation method based on the Wiener weighting function of linear minimum mean square error to eliminate the influence of noise; Finally, according to the characteristics of the generalized correlation method that relies on the prior knowledge of the signal but the ability to suppress noise and the characteristics of the adaptive method that the ability to suppress noise is weak but does not rely on the prior knowledge of the signal, the two methods are combined to form a Wiener-weighted generalized correlation and its adaptive method. Simulation experiments prove that the Wiener weighted adaptive time difference estimation method based on median filtering has better estimation performance under impulsive noise than the adaptive minimum average p-norm method based on fractional low-order statistics.
    VL  - 6
    IS  - 3
    ER  - 

    Copy | Download

Author Information
  • School of Electronic Information, Shanghai Dianji University, Shanghai, China

  • School of Electronic Information, Shanghai Dianji University, Shanghai, China

  • Sections