Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials

Characteristic Parameters Extraction and Pattern Recognition of Partial Discharges based on Envelope of Ultra-high Frequency Signal

Authors
Zhaoli Gao, Yingtao Sun, Lingen Luo, Gehao Sheng, Xiuchen Jiang
Corresponding Author
Zhaoli Gao
Available Online January 2016.
DOI
https://doi.org/10.2991/icsmim-15.2016.228How to use a DOI?
Keywords
gas insulated switchgear; partial discharge; ultra-high frequency; characteristic parameters; pattern recognition
Abstract

With the help of the Hilbert transform, the low-frequency signals modulated by high-frequency signals can be demodulated. This article proposed a method to extract the time-domain features of ultra-high frequency (UHF) signals regarding the partial discharges (PD) in a gas insulated switchgear (GIS). Utilizing the Hilbert transform, the envelope of a PD signal can be solved, and further the corresponding characteristic parameters of some key time domains can be acquired. An experimental platform for the detection of artificial insulation faults in a GIS was established. Thus, the experimental data of 3 types of typical PD signals were gained, and then used for the analysis and verification of the presented algorithm. The result shows that different types of PDs were accurately recognized. It can be concluded that the method presented is practical and effective.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials
Series
Advances in Computer Science Research
Publication Date
January 2016
ISBN
978-94-6252-157-5
ISSN
2352-538X
DOI
https://doi.org/10.2991/icsmim-15.2016.228How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhaoli Gao
AU  - Yingtao Sun
AU  - Lingen Luo
AU  - Gehao Sheng
AU  - Xiuchen Jiang
PY  - 2016/01
DA  - 2016/01
TI  - Characteristic Parameters Extraction and Pattern Recognition of Partial Discharges based on Envelope of Ultra-high Frequency Signal
BT  - Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials
PB  - Atlantis Press
SP  - 1233
EP  - 1241
SN  - 2352-538X
UR  - https://doi.org/10.2991/icsmim-15.2016.228
DO  - https://doi.org/10.2991/icsmim-15.2016.228
ID  - Gao2016/01
ER  -