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Prediction Flashover Voltage on Polluted Porcelain Insulator Using ANN

Ali Salem1, Rahisham Abd-Rahman1, Waheed Ghanem2,*, Samir Al-Gailani3,4, Salem Al-Ameri1

1 Faculty of Electrical and Electronic Engineering, University Tun Hussein Onn Malaysia, Johor, 86400, Malaysia
2 Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, Kuala Terengganu, 21030, Malaysia
3 School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, 14300, Malaysia
4 Department of Electrical and Electronics Engineering, Faculty of Engineering, Al-Madinah International University, Kuala Lumpur, 57100, Malaysia

* Corresponding Author: Waheed Ghanem. Email: email

Computers, Materials & Continua 2021, 68(3), 3755-3771. https://doi.org/10.32604/cmc.2021.016988

Abstract

This paper aims to assess the effect of dry band location of contaminated porcelain insulators under various flashover voltages due to humidity. Four locations of dry bands are proposed to be tested under different severity of contamination artificially produce using salt deposit density (SDD) sprayed on an insulator. Laboratory tests of polluted insulators under proposed scenarios have been conducted. The flashover voltage of clean insulators has been identified as a reference value to analyze the effect of contamination distribution and its severity. The dry band dimension has been taken into consideration in experimental tests. The flashover voltage has been predicted using an artificial neural network (ANN) technique based on the laboratory test data. The ANN approach is constructed with five input data (geometry the insulator and parameters of contamination) and flashover voltage as the output of the model. Results indicated that the pollution distribution based on the proposed scenario has a significant influence on the flashover voltage performances. Validation of the ANN model reveals that the relative error values between the experimental results and the prediction appeared to be within 5%. This indicates the significant efficiency of the ANN technique in predicting the flashover voltage insulator under test.


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APA Style
Salem, A., Abd-Rahman, R., Ghanem, W., Al-Gailani, S., Al-Ameri, S. (2021). Prediction flashover voltage on polluted porcelain insulator using ANN. Computers, Materials & Continua, 68(3), 3755-3771. https://doi.org/10.32604/cmc.2021.016988
Vancouver Style
Salem A, Abd-Rahman R, Ghanem W, Al-Gailani S, Al-Ameri S. Prediction flashover voltage on polluted porcelain insulator using ANN. Comput Mater Contin. 2021;68(3):3755-3771 https://doi.org/10.32604/cmc.2021.016988
IEEE Style
A. Salem, R. Abd-Rahman, W. Ghanem, S. Al-Gailani, and S. Al-Ameri "Prediction Flashover Voltage on Polluted Porcelain Insulator Using ANN," Comput. Mater. Contin., vol. 68, no. 3, pp. 3755-3771. 2021. https://doi.org/10.32604/cmc.2021.016988

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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