International Journal of Intelligent Systems and Applications(IJISA)

ISSN: 2074-904X (Print), ISSN: 2074-9058 (Online)

Published By: MECS Press

IJISA Vol.8, No.12, Dec. 2016

Characteristic Research of Single-Phase Grounding Fault in Small Current Grounding System based-on NHHT

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Yingwei Xiao

Index Terms

Transient component of zero-sequence current;fault phase;grounding resistance;NHHT;intrinsic mode function (IMF);EMD;Hilbert marginal spectrum


Transient analysis is carried out for the single-phase grounding fault in small current grounding system, the transient grounding current expression is derived, and the influence factors are analyzed. Introduces a method for non-stationary and non-linear signal analysis method –Hilbert Huang transform (HHT) to analyze the single phase grounding fault in small current grounding system, HHT can be better used to extract the abundant transient time frequency information from the non-stationary and nonlinear fault current signals. The empirical mode decomposition (EMD) process and the normalized Hilbert Huang transform (NHHT) algorithm are presented, NHHT is used to analyze and verify an example of the nonlinear and non-stationary amplitude modulation signals. Build a small current grounding system in the EMTP_ATP environment, by selecting the appropriate time window to extract the transient signals, NHHT is used to analyze the transient current signals, and the Hilbert amplitude spectrum and the Hilbert marginal spectrum of the zero sequence transient current signals are obtained. Finally, the influences of the fault phase and the grounding resistance on the time-frequency characteristics of the signals are analyzed.

Cite This Paper

Yingwei Xiao,"Characteristic Research of Single-Phase Grounding Fault in Small Current Grounding System based-on NHHT", International Journal of Intelligent Systems and Applications(IJISA), Vol.8, No.12, pp.46-56, 2016. DOI: 10.5815/ijisa.2016.12.06


[1]N.E.Huang, Z.Shen, S.R.Long, et al., “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,” Proc R Soc Lond A, 454, pp.903-995, 1998.

[2]Vasudevan K, Cook FA., “Empirical mode skeletonization of deep crustal seismic data: Theory and applications,” Journal of Geophysical Research-Solid Earth, Vol.105(B4), APR 10, pp.7845-7856, 2000.

[3]Loh CH, Wu TC, Huang NE., “Application of the empirical mode decomposition-Hilbert spectrum method to identify near-fault ground-motion characteristics and structural responses,” Bulletin of the Seismological Society of America, Vol.91, No.5, pp.1339-1357, 2001.

[4]Xun Zhu, Zheng Shen, Stephen D.E, et al., “Gravity wave characteristics in the middle atmosphere derived from the empirical mode decomposition method,” Journal of Geophysical Research, Vol.102, No.D14, pp.16545-16561, 1997.

[5]Yang Jann N, L.Y., “System identification of linear structures using Hilbert transform and Empirical Mode Decomposition,” Proceedings of the International Modal Analysis Conference, pp.213-219, 2000.

[6]Komm RW, Hill F. Howe R., “Empirical mode decomposition and Hilbert analysis applied to rotation residuals of the solar convection zone,” Astrophysical Journal, Vol.558, No.1, pp.428-441, 2001.

[7]Ranjit A. Thuraisingham, “Estimation of Teager energy using the Hilbert–Huang transform,” IET Signal Process, Vol.9, No.1, pp.82–87, 2015.

[8]Dhouha Kbaier Ben Ismail, Pascal Lazure, Ingrid Puillat, “Advanced Spectral Analysis and Cross Correlation Based on the Empirical Mode Decomposition: Application to the Environmental Time Series,” IEEE Geoscience and Remote Sensing Letters, Vol.12, No.9, pp.1968-1972, 2015.

[9]Liang H, Lin Z, McCallum RW., “Artifact reduction in electrogastrogram based on empirical mode decomposition method,” Medical& Biological Engineering & Computing, Vol.38, No.1, pp.35-41, 2000.

[10]Echeverria J C,Crowe J A,Woolfson M S,Hayes-Gill B R., “Application of empirical mode decomposition to heart rate variability analysis,” Medical& Biological Engineering& Computing, 39(2): 471-479, 2001.

[11]Abdenour Soualhi, Kamal Medjaher, Noureddine Zerhouni, “Bearing Health Monitoring Based on Hilbert–Huang Transform, Support Vector Machine, and Regression,” IEEE Transactions on Instrumentation and Measurement, Vol.64, No.1, pp.52-62, 2015.

[12]Helong Li, Sam Kwong, Lihua Yang, Daren Huang, Dongping Xiao, “Hilbert-Huang Transform for Analysis of Heart Rate Variability in Cardiac Health,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol.8, No.6, pp.1557-1567, 2011.

[13]Amin Yazdanpanah Goharrizi, Nariman Sepehri, “Internal Leakage Detection in Hydraulic Actuators Using Empirical Mode Decomposition and Hilbert Spectrum,” IEEE Transactions on Instrumentation and Measurement, Vol.61, No.2, pp.368-378, 2012.

[14]Chao Wang, Xiao Liu, Zhe Chen, “Incipient Stator Insulation Fault Detection of Permanent Magnet Synchronous Wind Generators Based on Hilbert–Huang Transformation,” IEEE Transactions on Magnetics, Vol.50, No.11, pp.1-4, 2014.

[15]Antonio Garcia Espinosa, Javier A. Rosero, Jordi Cusid´o, Luis Romeral, Juan Antonio Ortega, “Fault Detection by Means of Hilbert–Huang Transform of the Stator Current in a PMSM With Demagnetization,” IEEE Transactions on Energy Conversion, Vol.25, No.2, pp.312-318, 2010.

[16]Shu Hongchun, Tian Xincui, Dai Yuetao, “The Identification of Internal and External Faults for ±800kV UHVDC Transmission Line Using Wavelet based Multi-Resolution Analysis,” I.J. Intelligent Systems and Applications, 3(03): 47-53, 2011.

[17]Ashwani Kumar Narula, Amar Partap Singh, “Fault Diagnosis of Mixed-Signal Analog Circuit using Artificial Neural Networks,” I.J. Intelligent Systems and Applications, 7(07): 11-17, 2015.

[18]A. R. Messina, Vijay Vittal, “Nonlinear, Non-Stationary Analysis of Interarea Oscillations via Hilbert Spectral Analysis,” IEEE Transactions on Power Systems, Vol.21, No.3, pp.1234-1241, 2006.

[19]Mohammad Jasa Afroni, Danny Sutanto, David Stirling, “Analysis of Nonstationary Power-Quality Waveforms Using Iterative Hilbert Huang Transform and SAX Algorithm,” IEEE Transactions on Power Delivery, Vol.28, No.4, pp.2134-2144, 2013.

[20]Patrick Flandrin, “Empirical Mode Decomposition as a Filter Bank,” IEEE Signal Processing Letters, Vol.11, No.2, pp.431-435, 2004.

[21]Gabriel Rilling, “On the Influence of Sampling on the Empirical Mode Decomposition,” IEEE Signal Processing Letters, Vol.17, No.4, pp.214-218, 2005.

[22]Xiaonan Hui, Shilie Zheng, Jinhai Zhou, Hao Chi, Xiaofeng Jin, Xianmin Zhang, “Hilbert–Huang Transform Time-Frequency Analysis in φ-OTDR Distributed Sensor,” IEEE Photonics Technology Letters, Vol.26, No.23, pp.2403-2406, 2014.

[23]Yingjun Yuan, Zhitao Huang, Hao Wu, Xiang Wang, “Specific emitter identification based on Hilbert–Huang transform-based time–frequency–energy distribution features,” IET Commun., Vol.8, No.13, pp.2404-2412, 2014.

[24]Zhaohua Wu, Norden E.Huang, “Ensemble Empirical Mode Decomposition: a noise assisted data analysis method,” Advances in Adaptive Data Analysis, 1(1):1-41, 2009.

[25]Norden E. Huang, Zhaohua Wu, “On Instantaneous Frequency,” Advances in Adaptive Data Analysis, Vol.1, No.2, pp.177-229, 2009.

[26]Thomas N., “The effects of very-high resistance grounding on the selectivity of ground-fault relaying in high-voltage long wall power systems,” IEEE Trans Ind Appl., Vol.37, No.2, pp.398-406, 2001.