Machine Learning Technique to Predict Flashover Voltage of Nanocomposite Materials

Authors

  • Shaymaa Qenawy Electrical Power Engineering and Control Department, Pyramids Higher Institute for Engineering and Technology, Giza, Egypt
  • Eid Aldawsri Electrical Engineering Department, Alexandria University, Alexandria, Egypt
  • Ahmed Hossam-Eldin Electrical Engineering Department, Alexandria University, Alexandria, Egypt
  • Loai Nasrat Electrical Engineering Department, Aswan University, Aswan, Egypt
  • Hossam Kotb Electrical Engineering Department, Alexandria University, Alexandria, Egypt

DOI:

https://doi.org/10.15379/ijmst.v10i1.2763

Keywords:

Epoxy Resin, Nanocomposites, Swelling Effect, Flashover Voltage, Machine Learning Algorithm

Abstract

Epoxy resin is frequently employed in medium- and high- voltage transmission insulation, because of its low dielectric losses and excellent temperature resistance. At low temperatures, epoxy resin has high chemical resistance. Epoxy resin insulated types have largely superseded the conventional, paper-insulated varieties in numerous cable sectors owing to several advantages. Numerous studies have been conducted to enhance the properties of epoxy resin. With the addition of silicon dioxide (SiO2) nanofiller, the electrical and physical properties of epoxy resin are intended to be improved in this research. Epoxy resin composites with SiO2 filler were created with lengths of 5, 10, 15, and 20 mm and concentrated at 7wt%. Subsequently the key findings of this research are outlined, highlighting the significance of this study's focus on polymer utilized in the highly competitive and technologically advanced power industry, which is used globally.

Downloads

Download data is not yet available.

Downloads

Published

2023-10-18

How to Cite

[1]
S. . Qenawy, E. . Aldawsri, A. . Hossam-Eldin, L. . Nasrat, and H. . Kotb, “Machine Learning Technique to Predict Flashover Voltage of Nanocomposite Materials”, ijmst, vol. 10, no. 1, pp. 1125-1134, Oct. 2023.