3D Kısmi Deşarj Sinyal Grafikleri ile Yüksek Gerilim Ekipmanlarının Dielektrik Analizi

Year 2021, Issue: 28, 684 - 689, 30.11.2021

Tuba Nur Serttaş , Fatih Serttaş

https://doi.org/10.31590/ejosat.1010151

Abstract

Kısmi deşarj (PD), yüksek voltaj mühendisliği için çok kritik bir olgudur. Güvenilir bir elektrik sistemine sahip olmak için doğru ölçümler ve PD'lerin ayrıntılı analizi gereklidir. Bu nedenle, PD sinyallerinin grafiklerini elde etmenin amacı, trend noktalarını çözmek ve analiz etmek için PD'leri görselleştirmektir. Filtrelenmemiş ve saçılmış kısmi deşarj sinyalleri, titizlikle ölçülüp hesaplansa bile yanlış gözlemlere neden olur. Konvansiyonel grafik elde etme yöntemlerinin, trend alanlarını belirlemede önemli olan yoğunluk alanlarının göz ardı edilmesi, birbirini takip eden ardışık kısmi deşarj sinyallerini yanlış temsil etmesi ve yüksek maliyetlere neden olması gibi bazı dezavantajları vardır. Bu bağlamda, bu makale, pahalı yöntem ve araçlara ihtiyaç duymadan çok paradigmalı sayısal hesaplama programlama dilini kullanan gelişmiş ve pratik bir yöntem önermektedir. Yüksek voltajlı güç kabloları, dijital zamana dayalı PD sinyallerini kaydetmek için laboratuvarda test edilir. Önerilen teknikle deneysel olarak ölçülen PD verileri 2B ve 3B grafiklere dönüştürülür. Bu kapsamda 2D ve 3D grafikler karşılaştırılmakta ve 3D grafik oluşturma süreci anlatılmaktadır. Sonuç olarak, yöntem kullanılarak elde edilen 3 boyutlu grafiklerle verilerin anlaşılması ve tanımlanması kolay hale gelmektedir.

Keywords

Kısmi deşarj, 3D analiz, Yüksek gerilim, Güç kablosu, Grafik modelleme

Dielectric Analysis of High Voltage Equipment via 3D Partial Discharge Signal Graphics

Abstract

Partial discharge (PD) is a very critical phenomenon for high voltage engineering. Accurate measurements and detailed analysis of PD's are necessary to have a reliable electrical system. Therefore, the aim of obtaining graphics of PD signals is to visualize PD's to solve and analyze trend points. Unfiltered and scattered partial discharge signals cause false observations even though these are rigorously measured and calculated. Conventional graphic obtaining methods have some drawbacks, such as ignoring intensity areas that are significant to identify trend areas, misrepresenting the sequential partial discharge signals following each other, and causing high costs. In this sense, this paper proposes an improved and practical method using a multi-paradigm numerical computing programming language without needing expensive methods and tools. High voltage power cables are tested in the laboratory to record digital time-based PD signals. The experimentally measured PD data are converted into 2D and 3D graphics with the proposed technique. In this context, 2D and 3D graphics are compared, and the process of creating 3D graphics is explained. Consequently, the data becomes easy to understand and define with 3D graphics obtained using the method.

Keywords

Partial discharge, 3D analysis, High voltage, Power cable, Graphical modeling.

References

• Fan, Z., Cai, M., & Wang, H. (2012). An improved denoising algorithm based on wavelet transform modulus maxima for non-intrusive measurement signals. Measurement Science and Technology, 23(4), 045007.
• Farahani, M., Borsi, H., Gockenbach, E., & Kaufhold, M. (2005). Partial discharge and dissipation factor behavior of model insulating systems for high voltage rotating machines under different stresses. IEEE Electrical Insulation Magazine, 21(5), 5-19.
• Ferreira, A. J., & Fantuzzi, N. (2020). Bernoulli 3D Frames. In MATLAB Codes for Finite Element Analysis (pp. 123-139). Springer, Cham.
• Forssén, C. (2008). Modelling of cavity partial discharges at variable applied frequency (Doctoral dissertation, KTH).
• Franses, P. H. (2016). A note on the mean absolute scaled error. International Journal of Forecasting, 32(1), 20-22.
• Fruth, B., & Niemeyer, L. (1992). The importance of statistical characteristics of partial discharge data. IEEE Transactions on Electrical Insulation, 27(1), 60-69.
• Kania, M., Fereniec, M., & Maniewski, R. (2007). Wavelet denoising for multi-lead high resolution ECG signals. Measurement science review, 7(4), 30-33.
• Macedo, E. C. T., Araujo, D. B., Da Costa, E. G., Freire, R. C. S., Lopes, W. T. A., Torres, I. S. M., ... & Glover, I. A. (2012, May). Wavelet transform processing applied to partial discharge evaluation. In Journal of Physics: Conference Series (Vol. 364, No. 1, p. 012054). IOP Publishing.
• Negm, T. S., Refaey, M., & Hossam-Eldin, A. A. (2016, December). Modeling and simulation of internal Partial Discharges in solid dielectrics under variable applied frequencies. In 2016 Eighteenth International Middle East Power Systems Conference (MEPCON) (pp. 639-644). IEEE.
• Qian, Z., Ju, T., Yunqing, B., Yanbin, X., & Ming, T. (2006, October). Mathematical model of four typical defects for UHF partial discharge in GIS. In 2006 International Conference on Power System Technology (pp. 1-8). IEEE.
• Quizhpi-Cuesta, M., Gómez-Juca, F., Orozco-Tupacyupanqui, W., & Quizhpi-Palomeque, F. (2017, March). An alternative method for Partial Discharges measurement using digital filters. In 2017 10th International Symposium on Advanced Topics in Electrical Engineering (ATEE) (pp. 92-97). IEEE.
• Satish, L., & Nazneen, B. (2003). Wavelet-based denoising of partial discharge signals buried in excessive noise and interference. IEEE Transactions on Dielectrics and Electrical Insulation, 10(2), 354-367.
• Schwarz, R., Muhr, M., & Pack, S. (2005, June). Partial discharge detection in oil with optical methods. In IEEE International Conference on Dielectric Liquids, 2005. ICDL 2005. (pp. 245-248). IEEE.
• Todorova, M., & Parvanova, R. (2017, June). Filtration of deteriorated signals used in the control systems by orthogonal wavelets. In 2017 15th International Conference on Electrical Machines, Drives and Power Systems (ELMA) (pp. 395-399). IEEE.
• Yiğit, E., Özkaya, U., Öztürk, Ş., Singh, D., & Gritli, H. (2021). Automatic Detection of Power Quality Disturbance Using Convolutional Neural Network Structure with Gated Recurrent Unit. Mobile Information Systems, 2021.