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Orta Gerilim Kablolarında Kısmi Boşalma Analizi Üzerine Deneysel Bir Yaklaşım

Year 2018, Volume: 18 Issue: 3, 904 - 912, 30.12.2018

Fatih Serttaş Fatih Onur Hocaoğlu

Abstract

Elektriksel kısmi boşalmalar, yüksek gerilim arızalarının büyük bir çoğunluğunu oluşturmaktadır. Yalıtkan malzemelerde hasar meydana getirebilecek kadar güçlü elektrik alanın olduğu her yerde elektriksel kısmi boşalma (deşarj) oluşabilir. Trafolarda, yüksek gerilim kablolarında veya diğer yüksek gerilim elemanlarında meydana gelen kısmi boşalmaların yeri, büyüklüğü ve meydana gelme sıklığı doğru tespit edilemezse zaman içerisinde önemli kalıcı hasarlara sebep olmaktadır. Bu çalışmada, orta gerilim hatlarında yaygın olarak kullanılan XLPE kabloları üzerinde kısmi boşalma ölçüm testleri gerçekleştirilmiştir. XLPE kablolar üzerinde çeşitli küçük hasarlar (defektler) oluşturulmuş ve laboratuvar ortamında bu kablolar yüksek gerilim altında test edilmiştir. Defektler, sahada kablo montaj işlemlerinde meydana gelebilecek-gelebilen hasarlar ve kabloların üretiminden kaynaklanabilecek iç kısmi boşalmalar göz önüne alınarak oluşturulmuştur. Testlerden elde edilen kısmi boşalma sinyallerinin istatistiksel özellikleri incelenmiş ve analiz edilmiştir. Sonuç olarak kablo üzerindeki yakın özellikteki farklı defektlerde kısmi boşalma sinyallerinin farklı özellikler gösterebildiği görülmüştür.

Keywords

XLPE Kablo Kısmi Boşalma Deşarj Yüksek Gerilim İstatistiksel Öznitelikler

References

  • Ambikairajah, R., Phung, B. T., Blackburn, T., Ravishankar, J., (2013). Spectral features for the classification of partial discharge signals from selected insulation defect models. IET Science, Measurement & Technology, 7(2):104–111.
  • Arora, R., Abdul Rahman, M.K. ve Srivastava, S.C., (2000). Partial discharge classification using principal component transformation. IEE Proceedings - Science, Measurement and Technology, 147(1):7–13.
  • Van Brunt, R.J., Cernyar, E.W. ve von Glahn, P., (1993). Importance of unraveling memory propagation effects in interpreting data on partial discharge statistics. IEEE Transactions on Electrical Insulation, 28(6):905–916.
  • Chan, J.C., Hui Ma ve Saha, T.K., (2013). Partial discharge pattern recognition using multiscale feature extraction and support vector machine. In 2013 IEEE Power & Energy Society General Meeting. IEEE: 1–5.
  • Chen, X., Qian, Y., Xu, Y.,Sheng, G., Jiang,X., (2016). Energy Estimation of Partial Discharge Pulse Signals Based on Noise Parameters. IEEE Access, 4:10270–10279.
  • Eigner, A. ve Rethmeier, K., (2016). An overview on the current status of partial discharge measurements on AC high voltage cable accessories. IEEE Electrical Insulation Magazine, 32(2):48–55.
  • Evagorou, D., Kyprianou, A.,Georghiou, G.E., Hunter, J.A., Hao, L., Lewin, P.L., Stavrou, A., (2010). Performance of the Support Vector Machine Partial Discharge classification method to noise contamination using phase synchronous measurements. In 2010 Annual Report Conference on Electrical Insulation and Dielectic Phenomena. IEEE: 1–4.
  • Fynes-Clinton, D. ve Nyamupangedengu, C., (2016). Partial discharge characterization of cross-linked polyethylene medium voltage power cable termination defects at very low frequency (0.1 Hz) and power frequency test voltages. IEEE Electrical Insulation Magazine, 32(4):15–23.
  • Hucker, T. ve Krantz, H.-G., (1995). Requirements of automated PD diagnosis systems for fault identification in noisy conditions. IEEE Transactions on Dielectrics and Electrical Insulation, 2(4):544–556.
  • Hunter, J.A., Hao,L., Lewin, P.L., Evagorou, d., Kyprianou, A., Georghiou, G.E., (2010). Comparison of two partial discharge classification methods. In 2010 IEEE International Symposium on Electrical Insulation. IEEE: 1–5.
  • Lalitha, E.M. ve Satish, L., (2000). Wavelet analysis for classification of multi-source PD patterns. IEEE Transactions on Dielectrics and Electrical Insulation, 7(1):40–47.
  • Li, J., Jiang, T., Harrison, R., Grzybowski, S., (2012). Recognition of ultra high frequency partial discharge signals using multi-scale features. IEEE Transactions on Dielectrics and Electrical Insulation, 19(4):1412–1420.
  • Li, P., Zhou, W., Yang, S., Liu,Y., Tian, Y., Wang, Y., (2017). Method for partial discharge localisation in air-insulated substations. IET Science, Measurement & Technology, 11(3):331–338.
  • Luo, L., Han, B., Chen, J., Sheng, G., Jiang, X., (2017). Partial Discharge Detection and Recognition in Random Matrix Theory Paradigm. IEEE Access, 5:8205–8213.
  • Ma, H., Chan, J., Saha, T., Seo, J., Ekanayake, C., (2015). Advanced signal processing techniques for transformer condition assessment. In 2015 IEEE 11th International Conference on the Properties and Applications of Dielectric Materials (ICPADM). IEEE: 96–99.
  • Mas’ud, A.A., Stewart, B.G. ve McMeekin, S.G., (2016). An investigative study into the sensitivity of different partial discharge φ-q-n pattern resolution sizes on statistical neural network pattern classification. Measurement, 92:497–507.
  • McDonnell, J.T.E. ve Bentley, P.M., (1994). Wavelet transforms: an introduction. Electronics & Communication Engineering Journal, 6(4):175–186.
  • Montanari, G.C., (2016). Partial discharge detection in medium voltage and high voltage cables: maximum distance for detection, length of cable, and some answers. IEEE Electrical Insulation Magazine, 32(5):41–46.
  • Sahoo, N.C., Salama, M.M.A. ve Bartnikas, R., (2005). Trends in partial discharge pattern classification: a survey. IEEE Transactions on Dielectrics and Electrical Insulation, 12(2):248–264.
  • Zheng, W., Qian, Y., Yang, N., Huang, C., Jiang, X., (2011). Research on Partial Discharge Localization in XLPE Cable Accessories Using Multi-Sensor Joint Detection Technology. PRZEGLĄD ELEKTROTECHNICZNY (Electrical Review, 87(111):33–2097.

Year 2018, Volume: 18 Issue: 3, 904 - 912, 30.12.2018

Fatih Serttaş Fatih Onur Hocaoğlu

Abstract

References

  • Ambikairajah, R., Phung, B. T., Blackburn, T., Ravishankar, J., (2013). Spectral features for the classification of partial discharge signals from selected insulation defect models. IET Science, Measurement & Technology, 7(2):104–111.
  • Arora, R., Abdul Rahman, M.K. ve Srivastava, S.C., (2000). Partial discharge classification using principal component transformation. IEE Proceedings - Science, Measurement and Technology, 147(1):7–13.
  • Van Brunt, R.J., Cernyar, E.W. ve von Glahn, P., (1993). Importance of unraveling memory propagation effects in interpreting data on partial discharge statistics. IEEE Transactions on Electrical Insulation, 28(6):905–916.
  • Chan, J.C., Hui Ma ve Saha, T.K., (2013). Partial discharge pattern recognition using multiscale feature extraction and support vector machine. In 2013 IEEE Power & Energy Society General Meeting. IEEE: 1–5.
  • Chen, X., Qian, Y., Xu, Y.,Sheng, G., Jiang,X., (2016). Energy Estimation of Partial Discharge Pulse Signals Based on Noise Parameters. IEEE Access, 4:10270–10279.
  • Eigner, A. ve Rethmeier, K., (2016). An overview on the current status of partial discharge measurements on AC high voltage cable accessories. IEEE Electrical Insulation Magazine, 32(2):48–55.
  • Evagorou, D., Kyprianou, A.,Georghiou, G.E., Hunter, J.A., Hao, L., Lewin, P.L., Stavrou, A., (2010). Performance of the Support Vector Machine Partial Discharge classification method to noise contamination using phase synchronous measurements. In 2010 Annual Report Conference on Electrical Insulation and Dielectic Phenomena. IEEE: 1–4.
  • Fynes-Clinton, D. ve Nyamupangedengu, C., (2016). Partial discharge characterization of cross-linked polyethylene medium voltage power cable termination defects at very low frequency (0.1 Hz) and power frequency test voltages. IEEE Electrical Insulation Magazine, 32(4):15–23.
  • Hucker, T. ve Krantz, H.-G., (1995). Requirements of automated PD diagnosis systems for fault identification in noisy conditions. IEEE Transactions on Dielectrics and Electrical Insulation, 2(4):544–556.
  • Hunter, J.A., Hao,L., Lewin, P.L., Evagorou, d., Kyprianou, A., Georghiou, G.E., (2010). Comparison of two partial discharge classification methods. In 2010 IEEE International Symposium on Electrical Insulation. IEEE: 1–5.
  • Lalitha, E.M. ve Satish, L., (2000). Wavelet analysis for classification of multi-source PD patterns. IEEE Transactions on Dielectrics and Electrical Insulation, 7(1):40–47.
  • Li, J., Jiang, T., Harrison, R., Grzybowski, S., (2012). Recognition of ultra high frequency partial discharge signals using multi-scale features. IEEE Transactions on Dielectrics and Electrical Insulation, 19(4):1412–1420.
  • Li, P., Zhou, W., Yang, S., Liu,Y., Tian, Y., Wang, Y., (2017). Method for partial discharge localisation in air-insulated substations. IET Science, Measurement & Technology, 11(3):331–338.
  • Luo, L., Han, B., Chen, J., Sheng, G., Jiang, X., (2017). Partial Discharge Detection and Recognition in Random Matrix Theory Paradigm. IEEE Access, 5:8205–8213.
  • Ma, H., Chan, J., Saha, T., Seo, J., Ekanayake, C., (2015). Advanced signal processing techniques for transformer condition assessment. In 2015 IEEE 11th International Conference on the Properties and Applications of Dielectric Materials (ICPADM). IEEE: 96–99.
  • Mas’ud, A.A., Stewart, B.G. ve McMeekin, S.G., (2016). An investigative study into the sensitivity of different partial discharge φ-q-n pattern resolution sizes on statistical neural network pattern classification. Measurement, 92:497–507.
  • McDonnell, J.T.E. ve Bentley, P.M., (1994). Wavelet transforms: an introduction. Electronics & Communication Engineering Journal, 6(4):175–186.
  • Montanari, G.C., (2016). Partial discharge detection in medium voltage and high voltage cables: maximum distance for detection, length of cable, and some answers. IEEE Electrical Insulation Magazine, 32(5):41–46.
  • Sahoo, N.C., Salama, M.M.A. ve Bartnikas, R., (2005). Trends in partial discharge pattern classification: a survey. IEEE Transactions on Dielectrics and Electrical Insulation, 12(2):248–264.
  • Zheng, W., Qian, Y., Yang, N., Huang, C., Jiang, X., (2011). Research on Partial Discharge Localization in XLPE Cable Accessories Using Multi-Sensor Joint Detection Technology. PRZEGLĄD ELEKTROTECHNICZNY (Electrical Review, 87(111):33–2097.
There are 20 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Fatih Serttaş

Fatih Onur Hocaoğlu

Publication Date December 30, 2018
Submission Date May 21, 2018
Published in Issue Year 2018 Volume: 18 Issue: 3

Cite

APA Serttaş, F., & Hocaoğlu, F. O. (2018). Orta Gerilim Kablolarında Kısmi Boşalma Analizi Üzerine Deneysel Bir Yaklaşım. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, 18(3), 904-912.
AMA Serttaş F, Hocaoğlu FO. Orta Gerilim Kablolarında Kısmi Boşalma Analizi Üzerine Deneysel Bir Yaklaşım. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. December 2018;18(3):904-912.
Chicago Serttaş, Fatih, and Fatih Onur Hocaoğlu. “Orta Gerilim Kablolarında Kısmi Boşalma Analizi Üzerine Deneysel Bir Yaklaşım”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 18, no. 3 (December 2018): 904-12.
EndNote Serttaş F, Hocaoğlu FO (December 1, 2018) Orta Gerilim Kablolarında Kısmi Boşalma Analizi Üzerine Deneysel Bir Yaklaşım. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 18 3 904–912.
IEEE F. Serttaş and F. O. Hocaoğlu, “Orta Gerilim Kablolarında Kısmi Boşalma Analizi Üzerine Deneysel Bir Yaklaşım”, Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, vol. 18, no. 3, pp. 904–912, 2018.
ISNAD Serttaş, Fatih - Hocaoğlu, Fatih Onur. “Orta Gerilim Kablolarında Kısmi Boşalma Analizi Üzerine Deneysel Bir Yaklaşım”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi 18/3 (December 2018), 904-912.
JAMA Serttaş F, Hocaoğlu FO. Orta Gerilim Kablolarında Kısmi Boşalma Analizi Üzerine Deneysel Bir Yaklaşım. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. 2018;18:904–912.
MLA Serttaş, Fatih and Fatih Onur Hocaoğlu. “Orta Gerilim Kablolarında Kısmi Boşalma Analizi Üzerine Deneysel Bir Yaklaşım”. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi, vol. 18, no. 3, 2018, pp. 904-12.
Vancouver Serttaş F, Hocaoğlu FO. Orta Gerilim Kablolarında Kısmi Boşalma Analizi Üzerine Deneysel Bir Yaklaşım. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilimleri Dergisi. 2018;18(3):904-12.


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