Arrival Time Difference Estimation of Ultrasonic Signals from Partial Discharge in Electric Power Equipments
Journal of Electrical and Electronic Engineering
Volume 7, Issue 5, October 2019, Pages: 113-119
Received: Oct. 12, 2019;
Published: Nov. 8, 2019
Views 89 Downloads 43
Jinxi Hu, School of Electronic Information, Shanghai Dianji University, Shanghai, China
Wenhong Liu, School of Electronic Information, Shanghai Dianji University, Shanghai, China
Haotian Zhang, School of Electronic Information, Shanghai Dianji University, Shanghai, China
Hang Liu, School of Electronic Information, Shanghai Dianji University, Shanghai, China
Keni Xu, School of Electronic Information, Shanghai Dianji University, Shanghai, China
Mianmian Wang, School of Electronic Information, Shanghai Dianji University, Shanghai, China
Follow on us
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.
Partial Discharge, Ultrasonic Signals, Arrival Time Difference Estimation, Low SNR, Narrowband Signals
To cite this article
Arrival Time Difference Estimation of Ultrasonic Signals from Partial Discharge in Electric Power Equipments, Journal of Electrical and Electronic Engineering.
Vol. 7, No. 5,
2019, pp. 113-119.
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Jialin Liu, Ming Dong, Shan An. A Survey of Partial Discharge Detection and Location Technology of Power Transformers [J]. Insulation Materials, 2015 (08): 1-7.
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.
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.
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.
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.
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.
Robert Hanus. Time delay estimation of random signals using cross-correlation with Hilbert Transform [J]. Measurement, 2019, 146.
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.
Xiao Chen, Qu Zhenlin. Time Delay Estimation by Bispectrum Interpolation [J]. Sensors & Transducers, 2013, 158 (11).
Huijuan Wu, Yumei Wen, Jin Yang, Ping Li. Adaptive detection and location for water pipeline leaks in lower SNR and nonstationary environments [P]. Control and Automation, 2009. ICCA 2009. IEEE International Conference on, 2009.
YANG GAO, Tianshuang QIU, Lan SHA, et al. Narrowband time delay estimation based on correlation coefficient [J]. Journal of Systems Engineering and Electronics, 2009 (05): 937- 941.
Lan Sha. Research on Time Delay Estimation Method for Narrowband Signals in Radio Passive Location [D] Dalian: Dalian University of Technology, 2009.
Bo Sun, Jianwen Zhang, Leiluo Pan. Research on Partial Discharge Denoising Method Based on EMD. Insulation Materials, 2014 (03): 89-93.
TORRES. A complete ensemble emprirical mode decomposition with adaptive noise [J]. IEEE Transaction on Signal Process, 2011 (2): 4144-4147.
Chang Shu, Xiao Jin, ZiPin Li. CEEMDAN based distribution transformer discharge fault noise diagnosis method [J]. High voltage technology, 2018 (10): 2603-2611.
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.
Zhiman He, Jianwen Wang, Xinchuan Jiang. Research on calculation method of time delay of partial discharge UHF signal of switchgear based on EMD optimized bispectrum [J]. Smart power, 2018 (11): 59- 64.
JiaCheng Gao, Yunqin Tian, Yongli Zhu. Wavelet packet denoising method based on partial set empirical mode decomposition and permutation entropy partial discharge signal [J]. Journal of Power Systems and Automation, 2018 (03): 1-7.
Qi Liu. Research on Ultrasonic Testing Method for Partial Discharge of Power Transformer [D]. Shenyang: Shenyang University of Technology, 2017.
Wenwen Zhao, Xingwen Zeng. A new EMD denoising method [J] Electronic technology, 2008 (05): 30-32+36.