Journal of Electrical and Electronic Engineering

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Arrival Time Difference Estimation of Ultrasonic Signals from Partial Discharge in Electric Power Equipments

Received: 12 October 2019    Accepted:     Published: 08 November 2019
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Abstract

Partial discharge of power equipment is one of the common faults in power systems. How to quickly and accurately determine the location of partial discharge is a problem that needs to be solved in practice. The signal arrival time difference estimation technique in signal processing is one of the effective methods to solve this problem. When the power equipment is partially discharged, an ultrasonic signal is generated. Therefore, the local discharge can be positioned according to the ultrasonic signal, however, the traditional signal arrival time difference estimation methods are not ideal for the actual low signal-to-noise ratio and narrow-band ultrasonic signals. In this paper, an improved correlation coefficient waveform comparison time difference estimation algorithm based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN), threshold denoising is proposed, referred to as CEEMDAN-TDE. Firstly, according to the characteristics of the actual ultrasonic signals, the double-exponential decay oscillation model is used to model the partial discharge ultrasonic signals, and Gaussian white noises are added as the interference signals. secondly, the CEEMDAN threshold denoising is used to improve the signal-to-noise ratio of the partial discharge signals; thirdly, the cross-correlation coefficient is calculated, then the arrival time difference can be obtained by comparing the waveforms of the correlation coefficients, and the partial discharge location information is known. The computer simulations of the CEEMDAN-TDE method, and the generalized correlation method, LMS method, and correlation coefficient waveform comparison method estimation are performed. Experimental results show that the estimating performance in arrival time difference of proposed method, CEEMDAN-TDE, is better than the other three methods’ under low SNR and narrowband. The CEEMDAN-TDE method has the hopeful more application in practice.

DOI 10.11648/j.jeee.20190705.13
Published in Journal of Electrical and Electronic Engineering (Volume 7, Issue 5, October 2019)
Page(s) 113-119
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

Partial Discharge, Ultrasonic Signals, Arrival Time Difference Estimation, Low SNR, Narrowband Signals

References
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[2] Fangcheng Lv, ying Zhang, han Wu. Research on Ultrasonic Localization Method Based on Improved RD_MUSIC Algorithm and Lean_Omitted Array [J]. Journal of North China Electric Power University (Natural Science Edition). 2018 (01): 1-6.
[3] Lei Yu, Shijie Wang, Peng Wang. Simulation and Experimental Study on Partial Discharge Ultrasonic Positioning of Transformer Windings [J]. Insulation Materials, 2019, 52 (6): 72-78.
[4] DANIELE S, SERGIO C. Adaptive time delay estimation using filter length constraints for source localization in reverberant acoustic environments [J]. IEEE Signal Processing Letters, 2013, 20 (5): 507-510.
[5] Wenhong LIU, Tianshuang QIU, Zhiyue LIN, et al. Estimation of propagation velocity of gastric electrical activity using LMSTDE [C] 7 VOLS, 2005-01-01: Institute of Electrical and Electronics Engineers Inc., 445 Hoes Lane / P. O. Box 1331, Piscataway, N, 2005: 5954-5957.
[6] LE B C, Yide WANG, VINCENT B, et al. Time delay and permittivity estimation by ground-penetrating radar with support vector regression [J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11 (4): 873-877.
[7] Robert Hanus. Time delay estimation of random signals using cross-correlation with Hilbert Transform [J]. Measurement, 2019, 146.
[8] Wei XIA, Wenying JIANG, Lingfeng ZHU. An Adaptive Time Delay Estimator Based on ETDE Algorithm with Noisy Measurements [J]. Chinese Journal of Electronics, 2017, 26 (04): 760-767.
[9] Xiao Chen, Qu Zhenlin. Time Delay Estimation by Bispectrum Interpolation [J]. Sensors & Transducers, 2013, 158 (11).
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[12] Lan Sha. Research on Time Delay Estimation Method for Narrowband Signals in Radio Passive Location [D] Dalian: Dalian University of Technology, 2009.
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[16] Jianwen Zhang, Yang Liu, Dapeng Zhang. A new denoising method based on CEEMDAN and wavelet adaptive threshold [J]. Electrical measurement and instrumentation, 2018 (10): 14-18+33.
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Author Information
  • School of Electronic Information, Shanghai Dianji University, Shanghai, China

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

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

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

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

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

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    Jinxi Hu, Wenhong Liu, Haotian Zhang, Hang Liu, Keni Xu, et al. (2019). Arrival Time Difference Estimation of Ultrasonic Signals from Partial Discharge in Electric Power Equipments. Journal of Electrical and Electronic Engineering, 7(5), 113-119. https://doi.org/10.11648/j.jeee.20190705.13

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    ACS Style

    Jinxi Hu; Wenhong Liu; Haotian Zhang; Hang Liu; Keni Xu, et al. Arrival Time Difference Estimation of Ultrasonic Signals from Partial Discharge in Electric Power Equipments. J. Electr. Electron. Eng. 2019, 7(5), 113-119. doi: 10.11648/j.jeee.20190705.13

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    AMA Style

    Jinxi Hu, Wenhong Liu, Haotian Zhang, Hang Liu, Keni Xu, et al. Arrival Time Difference Estimation of Ultrasonic Signals from Partial Discharge in Electric Power Equipments. J Electr Electron Eng. 2019;7(5):113-119. doi: 10.11648/j.jeee.20190705.13

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  • @article{10.11648/j.jeee.20190705.13,
      author = {Jinxi Hu and Wenhong Liu and Haotian Zhang and Hang Liu and Keni Xu and Mianmian Wang},
      title = {Arrival Time Difference Estimation of Ultrasonic Signals from Partial Discharge in Electric Power Equipments},
      journal = {Journal of Electrical and Electronic Engineering},
      volume = {7},
      number = {5},
      pages = {113-119},
      doi = {10.11648/j.jeee.20190705.13},
      url = {https://doi.org/10.11648/j.jeee.20190705.13},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.jeee.20190705.13},
      abstract = {Partial discharge of power equipment is one of the common faults in power systems. How to quickly and accurately determine the location of partial discharge is a problem that needs to be solved in practice. The signal arrival time difference estimation technique in signal processing is one of the effective methods to solve this problem. When the power equipment is partially discharged, an ultrasonic signal is generated. Therefore, the local discharge can be positioned according to the ultrasonic signal, however, the traditional signal arrival time difference estimation methods are not ideal for the actual low signal-to-noise ratio and narrow-band ultrasonic signals. In this paper, an improved correlation coefficient waveform comparison time difference estimation algorithm based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN), threshold denoising is proposed, referred to as CEEMDAN-TDE. Firstly, according to the characteristics of the actual ultrasonic signals, the double-exponential decay oscillation model is used to model the partial discharge ultrasonic signals, and Gaussian white noises are added as the interference signals. secondly, the CEEMDAN threshold denoising is used to improve the signal-to-noise ratio of the partial discharge signals; thirdly, the cross-correlation coefficient is calculated, then the arrival time difference can be obtained by comparing the waveforms of the correlation coefficients, and the partial discharge location information is known. The computer simulations of the CEEMDAN-TDE method, and the generalized correlation method, LMS method, and correlation coefficient waveform comparison method estimation are performed. Experimental results show that the estimating performance in arrival time difference of proposed method, CEEMDAN-TDE, is better than the other three methods’ under low SNR and narrowband. The CEEMDAN-TDE method has the hopeful more application in practice.},
     year = {2019}
    }
    

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  • TY  - JOUR
    T1  - Arrival Time Difference Estimation of Ultrasonic Signals from Partial Discharge in Electric Power Equipments
    AU  - Jinxi Hu
    AU  - Wenhong Liu
    AU  - Haotian Zhang
    AU  - Hang Liu
    AU  - Keni Xu
    AU  - Mianmian Wang
    Y1  - 2019/11/08
    PY  - 2019
    N1  - https://doi.org/10.11648/j.jeee.20190705.13
    DO  - 10.11648/j.jeee.20190705.13
    T2  - Journal of Electrical and Electronic Engineering
    JF  - Journal of Electrical and Electronic Engineering
    JO  - Journal of Electrical and Electronic Engineering
    SP  - 113
    EP  - 119
    PB  - Science Publishing Group
    SN  - 2329-1605
    UR  - https://doi.org/10.11648/j.jeee.20190705.13
    AB  - Partial discharge of power equipment is one of the common faults in power systems. How to quickly and accurately determine the location of partial discharge is a problem that needs to be solved in practice. The signal arrival time difference estimation technique in signal processing is one of the effective methods to solve this problem. When the power equipment is partially discharged, an ultrasonic signal is generated. Therefore, the local discharge can be positioned according to the ultrasonic signal, however, the traditional signal arrival time difference estimation methods are not ideal for the actual low signal-to-noise ratio and narrow-band ultrasonic signals. In this paper, an improved correlation coefficient waveform comparison time difference estimation algorithm based on complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN), threshold denoising is proposed, referred to as CEEMDAN-TDE. Firstly, according to the characteristics of the actual ultrasonic signals, the double-exponential decay oscillation model is used to model the partial discharge ultrasonic signals, and Gaussian white noises are added as the interference signals. secondly, the CEEMDAN threshold denoising is used to improve the signal-to-noise ratio of the partial discharge signals; thirdly, the cross-correlation coefficient is calculated, then the arrival time difference can be obtained by comparing the waveforms of the correlation coefficients, and the partial discharge location information is known. The computer simulations of the CEEMDAN-TDE method, and the generalized correlation method, LMS method, and correlation coefficient waveform comparison method estimation are performed. Experimental results show that the estimating performance in arrival time difference of proposed method, CEEMDAN-TDE, is better than the other three methods’ under low SNR and narrowband. The CEEMDAN-TDE method has the hopeful more application in practice.
    VL  - 7
    IS  - 5
    ER  - 

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