Automating the Classification of Field Leakage Current Waveforms

Authors

  • D. Pylarinos Department of Electrical & Computer Engineering, University of Patras, Greece
  • K. Siderakis Electrical Engineering Department, Technological Educational Institute of Crete, Greece
  • E. Pyrgioti Department Of Electrical & Computer Engineering, University of Patras, Greece
  • E. Thalassinakis Islands Network Operations Department, Public Power Corporation, Greece
  • I. Vitellas Islands Network Operations Department, Public Power Corporation, Greece
Volume: 1 | Issue: 1 | Pages: 8-12 | February 2011 | https://doi.org/10.48084/etasr.2

Abstract

Leakage current monitoring is widely employed to investigate the performance of high voltage insulators and the development of surface activity. Field measurements offer an exact view of experienced activity and insulators’ performance, which are strongly correlated to local conditions. The required long term monitoring however, results to the accumulation of vast amounts of data. Therefore, an identification system for the classification of field leakage current waveforms rises as a necessity. In this paper, a number of 500 leakage current waveforms recorded on a composite post insulator installed at a 150 kV High Voltage Substation suffering from intense marine pollution, are investigated. The insulator was monitored for a period of 13 months. An identification system is designed based on the considered data employing Fourier analysis, wavelet multiresolution analysis and a neural network. Results show the large impact of noise in field measurements and the effectiveness of the discussed system on the considered data set.

Keywords:

insulator, leakage current, neural network, wavelet, pattern recognition, STD_MRA, field,

Downloads

Download data is not yet available.

References

CIGRE WG 33-04, The measurement of site pollution severity and its application to insulator dimensioning for a.c. systems, Electra No. 64, pp.101-116, 1979

CIGRE WG 33-04, TF 01, A review of current knowledge: polluted insulators, Cigre publications, 1998

H. Hillborg, U.W. Gedde, “Hydrophobicity changes in silicone rubbers”, IEEE Trans. Dielectr. Electr. Insul., Vol. 6, No. 5, pp.703-717, 1999 DOI: https://doi.org/10.1109/94.798127

Z. Jia, H. Gao, Z. Guan, L. Wang, J. Yang, “Study on hydrophobicity transfer of RTV coatings based on a modification of absorption and cohesion theory, IEEE Trans. Dielectr. Electr. Insul., Vol. 13, No. 6, pp. 1317-1324, 2006 DOI: https://doi.org/10.1109/TDEI.2006.258203

D. A. Swift, C. Spellman, A. Haddad, “Hydrophobicity transfer from silicone rubber to adhering pollutans and its effect on insulator performance, IEEE Trans. Dielectr. Electr. Insul., Vol. 13, No. 4, pp. 820-829, 2006 DOI: https://doi.org/10.1109/TDEI.2006.1667741

S. Kumagai, “Hydrophobicity transfer of RTV silicone rubber aged in single and multiple environmental stresses and the behaviour of LMW silicone fluid”, IEEE Trans. Power Deliv., Vol. 18, No. 2, pp. 506-516, 2003 DOI: https://doi.org/10.1109/TPWRD.2003.809690

N. Yoshimura, S. Kumagai, S. Nishimura, “Electrical and environmental aging of silicone rubber used in outdoor insulation”, IEEE Trans. Dielectr. Electr. Insul., Vol. 6, No. 5, pp. 632-650, 1999 DOI: https://doi.org/10.1109/94.798120

K. Siderakis, D. Agoris, “Performance of RTV silicone rubber coatings installed in coastal systems”, Electr. Power Syst. Res., Vol. 78, Issue 2, pp. 248-254, 2008 DOI: https://doi.org/10.1016/j.epsr.2007.02.013

D. Pylarinos, K. Siderakis, E. Pyrgioti, E. Thalassinakis, I. Vitellas, “Impact of noise related waveforms on long term field leakage current measurements”, IEEE Trans. Dielectr. Electr. Insul., Vol. 18, No. 1, 2011 DOI: https://doi.org/10.1109/TDEI.2011.5704501

K. Siderakis, D. Agoris, S. Gubanski, “Salt fog evaluation of RTV SIR coatings with different fillers”, IEEE Trans. Power Deliv., Vol. 23, No. 4, pp. 2270-2277, 2008 DOI: https://doi.org/10.1109/TPWRD.2008.2002857

K. Siderakis, D. Agoris, J. Stefanakis, E. Thalassinakis, “Influence of the profile on the performance of porcelain insulators installed in coastal high voltage networks in the case of condensation wetting”, IEE Proceedings, Science, Measurement and Technology, Vol. 153, No. 4 , p. 158-163, 2006 DOI: https://doi.org/10.1049/ip-smt:20050050

S. G. Mallat, “A Theory for Multiresolution Signal Decomposition: The Wavelet Representation”, IEEE Trans. Pattern Analysis and Machine Intelligence, Vol. 11, pp. 674-693, 1989. DOI: https://doi.org/10.1109/34.192463

Stephane Mallat, A Wavelet Tour Of Signal Processing, Academic Press, 1999 DOI: https://doi.org/10.1016/B978-012466606-1/50008-8

S. Haykin, Neural Networks: A comprehensive Foundation, Prentice Hall , India 1999

E. Dermatas, Pattern Recognition, University of Patras’ Academic Press, Department of Electrical and Computer Engineering, 1997

C. M. Bishop, Neural Networks for Pattern Recognition, Oxford University Press 1995 DOI: https://doi.org/10.1201/9781420050646.ptb6

Downloads

How to Cite

[1]
D. Pylarinos, K. Siderakis, E. Pyrgioti, E. Thalassinakis, and I. Vitellas, “Automating the Classification of Field Leakage Current Waveforms”, Eng. Technol. Appl. Sci. Res., vol. 1, no. 1, pp. 8–12, Feb. 2011.

Metrics

Abstract Views: 718
PDF Downloads: 238

Metrics Information

Most read articles by the same author(s)

1 2 > >>