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Investigation of the effect of layered structure on partial discharges in transformer pressboard insulator

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Abstract

The dielectric performance of pressboards impregnated with mineral oil is one of the key points in regard to the quality of the transformer’s working life. Partial discharges (PDs) occurring in the pressboard can cause some insulation defects which might be one of the major reasons for an electrical breakdown. Detection of the PDs in pressboards gives a chance to understand the dielectric behavior of the insulators, hence major defects can be prevented just in early stage. The main point of the study is to investigate the differences in dielectric performance of layered and non-layered pressboards in the presence of PDs. For this purpose, the PD behavior of a layered pressboard with three layers (each with a thickness of 0.5 mm) and of a non-layered (solid) pressboard (with a thickness of 1.5 mm) is examined for two different high voltage levels (20 and 30 kV). To detect the PDs, Hall Effect Sensors are employed, considering that PDs cause fluctuations in the magnetic field. To analyze the magnetic field measurements from a statistical point of view, the Kaplan–Meier method and the Weibull analysis are used.

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References

  1. Zhang Y, Qi B, Ma Y, Huang M, Yuan Q, Lv Y, Jiao Y, Li C, Zhang S (2021) Influencing mechanism of adhesive on partial discharge of pressboard block under AC/DC composite voltage. IEEE Trans Dielectr Electr Insul 28(6):1883–1891. https://doi.org/10.1109/TDEI.2021.009610

    Article  Google Scholar 

  2. Yoshida S, Kozako M, Hikita M (2021) Characteristics of creepage discharge in oil/pressboard composite insulation. IEEE Trans Dielectr Electr Insul 28(2):608–615. https://doi.org/10.1109/TDEI.2020.009313

    Article  Google Scholar 

  3. Zhixian Z, Jiali L, Weigen C, Tianhe Y, Yuxuan S, Kejie W, Fan L (2022) Oil-paper insulation partial discharge ultrasonic multifrequency sensing array based on fibre-optic fabry-perot sensor. High Voltage 7(2):325–335. https://doi.org/10.1049/hve2.12123

    Article  Google Scholar 

  4. Li Y, Zhang Q, Ding Y, Zhao Y (2017) Effect of cellulose impurities on partial discharges in oil-pressboard insulation under DC voltage. IEEE Trans Dielectr Electr Insul 24(4):2271–2273. https://doi.org/10.1109/TDEI.2017.006451

    Article  Google Scholar 

  5. Li S, Liu Z, Ji S (2021) Characteristics of creeping discharge caused by a needle electrode in oil-pressboard insulation under +DC voltage. IEEE Trans Dielectr Electr Insul 28(1):215–222. https://doi.org/10.1109/TDEI.2020.009157

    Article  Google Scholar 

  6. Zhang R, Zhang Q, Guo C, Zhang Z, Wu Z, Wen T (2022) Effects of thermally induced bubbles on the discharge characteristics of oil-impregnated pressboard. IEEE Trans Dielectrics Electrical Insul. Early Access. https://doi.org/10.1109/TDEI.2022.3165737

  7. Azrin NA, Ahmad MH, Piah MAM, Talib MA, Nawawi Z (2017) Partial discharge characteristics of oil-ımpregnated Kenaf based pressboard. In: The IEEE student conference on research and development (SCOReD), pp 13–14 Dec 2017, Putrajaya, Malaysia, pp 366–370

  8. Zhao C, Song Y, Cheng Y, Xue Y (2016) Risk assessment of oil ımpregnated pressboards using the statistical distribution of partial discharge before breakdown. In: IEEE ınternational conference on dielectrics (ICD), 3–7 July 2016. University of Montpellier, France, pp 654–657

  9. Wang Y, Zhang X, Jiang X, Wang Y (2019) Effect of aging on material properties and partial discharge characteristics of ınsulating pressboard. BioResources 14(1):1303–1316

    Article  Google Scholar 

  10. Bing L, Jian W.g, Dong D., Lei J., Licheng L. and Tingting W. (2021) Partial discharge simulation of air gap defects in oil-paper insulation paperboard of converter transformer under different ratios of AC–DC combined voltage. Energies 14(21):6995. https://doi.org/10.3390/en14216995

    Article  Google Scholar 

  11. Yangchun C, Jinqing W, Chongzhi Z, Haoyong S (2016) Experimental research on creepage discharge between oil-ımpregnated pressboard layers. In: IEEE conference on electrical ınsulation and dielectric phenomena (CEIDP), Toronto, ON, Canada, pp 999–1002

  12. Jang KH, Yoshida S, Kozako M, Hikita M (2015) Effect of thin solid layer coating on creepage discharge characteristics in oil/pressboard composite ınsulation system. In: IEEE conference on electrical ınsulation and dielectric phenomena (CEIDP), Ann Arbor, MI, USA, pp 832–835

  13. Umemoto T, Kainaga S, Muto Tsurimoto H, Yoshida T, Kozako SM, Hikita M (2014) Characteristics of partial discharge in the oil gap separated by pressboard barrier in oil/pressboard composite ınsulation system. In: IEEE 18th ınternational conference on dielectric liquids (ICDL), Bled, Slovenia, pp 1–4

  14. Yoshida S, Kozako M, Hikita M, Umemoto T, Kainaga S, Muto H, Tsurimoto T (2014) Characteristics of discharge generation across ınsulation barrier in the oil/pressboard composite ınsulation system. In: Proceedings of 2014 ınternational symposium on electrical ınsulating materials, Niigata, Japan, pp 225–228

  15. Atalar F, Uzunoğlu CP, Cekli S, Ugur M (2020) Statistical analysis of induced magnetic fields on oil-impregnated insulation pressboards. Electr Eng 102:2095–2107. https://doi.org/10.1007/s00202-020-01012-8

    Article  Google Scholar 

  16. Kleinbaum DG, Klein M (2011) Survival Analysis, a self-learning text, Third Edition”, Springer, ISBN 978–1–4419–6646–9

  17. Mishiro Y, Sakagami M, Kitahara T, Kondoh K, Okumura S (2008) The investigation of the recurrence rate of cholesteatoma using kaplan-meier survival analysis. Otol Neurotol 29(6):803–806. https://doi.org/10.1097/MAO.0b013e318181337f

    Article  Google Scholar 

  18. Sanders DS, Carter MJ, D’Silva J, James G, Bolton RP, Bardhan KD (2000) Survival analysis in percutaneous endoscopic gastrostomy feeding: a worse outcome in patients with dementia. Am J Gastroenterol 95(6):1472–1475. https://doi.org/10.1016/S0002-9270(00)00871-6

    Article  Google Scholar 

  19. Bartel AFP, Thomas SR (2015) Total ankle replacement survival rates based on kaplan-meier survival analysis of national joint registry data. Clin Podiat Med Surg 32(4):483–494. https://doi.org/10.1016/j.cpm.2015.06.012

    Article  Google Scholar 

  20. Chuang SK, Tian L, Wei LJ, Dodson TB (2001) Kaplan-Meier analysis of dental implant survival: a strategy for estimating survival with clustered observations. J Dent Res 80(11):2016–2020. https://doi.org/10.1177/00220345010800111301

    Article  Google Scholar 

  21. Zhu HP, Xia X, Yu CH (2011) Application of weibull model for survival of patients with gastric cancer. BMC Gastroenterol 11:1. https://doi.org/10.1186/1471-230X-11-1

    Article  Google Scholar 

  22. Jean-Francois C, Saleh JH (2009) Satellite and satellite subsystems reliability: statistical data analysis and modeling. Elsevier Reliab Eng Syst Safety 94(11):1718–1728. https://doi.org/10.1016/j.ress.2009.05.004

    Article  Google Scholar 

  23. Jardine AKS, Anderson PM, Mann DS (1987) Application of the weibull proportional hazards model to aircraft and marine engine failure data. Wiley Quality Reliable Eng Int 3(2):77–82. https://doi.org/10.1002/qre.4680030204

    Article  Google Scholar 

  24. Djamel D, Bachir R (2020) Weibull analysis of fatigue test in jute reinforced polyester composite material, composites communications 17:pp123–128. ISSN 2452–2139. https://doi.org/10.1016/j.coco.2019.11.016.

  25. Zhai LY, Lu WF, Liu Y, Li X, Vachtsevanos G (2013) Analysis of time-to-failure data with weibull model in product life cycle management. In: Nee A, Song B, Ong SK (eds) Re-engineering manufacturing for sustainability. Springer, Singapore. https://doi.org/10.1007/978-981-4451-48-2_114.

  26. Qing Z, Cheng H, Guanghua X (2014) A Mixture weibull proportional hazard model for mechanical system failure prediction utilising lifetime and monitoring data. Mech Syst Signal Process. 43(1–2):103–112. ISSN 0888–3270. https://doi.org/10.1016/j.ymssp.2013.10.013.

  27. Gayle M (1987) Ecological use of failure time analysis. Ecol Soc Am 67(1). https://doi.org/10.2307/1938524

  28. David AP, John NT (1986) Statistical analysis of survival and removal rate experiments. Ecol Soc Am 67(1). https://doi.org/10.2307/1938523.

  29. Caesar AJ (2003) Synergistic interaction of soilborne plant pathogens and root-attacking insects in classical biological control of an exotic rangeland weed. Biol Control 28(3):144–153

    Article  Google Scholar 

  30. Michael CN, Michael SA (1992) Enhancing toxicity data interpretation and prediction of ecological risk with survival time modeling: an illustration using sodium chloride toxicity to mosquitofish (Gambusia Holbrooki). Aquatic Toxicol 23(2):85–96. https://doi.org/10.1016/0166-445X(92)90001-4

    Article  Google Scholar 

  31. Ishak KJ, Kreif N, Benedict A, Noemi M (2013) Overview of parametric survival analysis for health-economic applications. Pharmacoeconomics 31:663–675. https://doi.org/10.1007/s40273-013-0064-3

    Article  Google Scholar 

  32. Evrensel AY (2008) Banking crisis and financial structure: a survival-time analysis. Int Rev Econ Finance 17(4):589–602. https://doi.org/10.1016/j.iref.2007.07.002

    Article  Google Scholar 

  33. Meyer BD (1990) Unemployment insurance and unemployment spells. Econometrica 58(4):757–782. https://doi.org/10.2307/2938349

    Article  Google Scholar 

  34. Kaplan EL, Meier P (1958) Nonparametric estimation from incomplete observations. J Am Stat Assoc 53(282):457–481

    Article  MathSciNet  MATH  Google Scholar 

  35. Govind SM, Deo KS, Georgia DK (1996) A generalization of the weibull distribution with application to the analysis of survival data. J Am Stat Assoc 91(436):1575–1583. https://doi.org/10.1080/01621459.1996.10476725

    Article  MathSciNet  MATH  Google Scholar 

  36. Kevin JC (2003) On the use and utility of the weibull model in the analysis of survival data. Controlled Clin Trials 24(6):682–701. https://doi.org/10.1016/S0197-2456(03)00072-2

    Article  Google Scholar 

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Acknowledgements

This work was supported by the Turkish-German University Research Fund with the Project Code 2019BM0002. The authors would like to thank the Turkish-German University Research Fund for this financial support.

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Istanbul University-Cerrahpaşa, 34320, Avcılar, Istanbul, Turkey

    Fatih Atalar

  2. Department of Electrical and Electronics Engineering, Turkish-German University, 34820, Beykoz, Istanbul, Turkey

    N.Özben Önhon

  3. Department of Robotics and Intelligent Systems, The Institute of Graduate Studies in Science and Engineering, Turkish-German University, 34820, Beykoz, Istanbul, Turkey

    Mukden Uğur

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  1. Fatih Atalar
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  3. Mukden Uğur
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FA contributed to experiments, writing and literature search; ÖÖ contributed to statistical analysis and writng; MU contributed to checking, examine analysis and supervising.

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Correspondence to Fatih Atalar.

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Atalar, F., Önhon, N. & Uğur, M. Investigation of the effect of layered structure on partial discharges in transformer pressboard insulator. Electr Eng 105, 3459–3467 (2023). https://doi.org/10.1007/s00202-023-01903-6

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