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South Asian Research Journal of Engineering and Technology (SARJET)
Volume-2 | Issue-04
Original Research Article
Estimate Electrical Resistivity of Epoxy Insulators Using Artificial Neural Network
L. S. Nasrat, A. A. Ibrahim, W. A. Abdelamgied, S. A. Qenawy
Published : July 9, 2020
DOI : 10.36346/sarjet.2020.v02i04.002
Abstract
Epoxy resin represents a commonly used basis for insulation materials and has been used in many different electrical applications. In this paper, different micro fillers such as Silicone dioxide (SiO2) and Barium iodate (Ba (IO3)2) were added to epoxy resin to improve electrical characteristics in different contaminated conditions. The electrical resistivity (ohm.cm) was carried out. The samples were prepared by mixing micro filler into epoxy with the content of 0, 5, 10, 15, 20 and 25 wt%. The artificial neural network (ANN) technique was used to evaluate electrical resistivity in different contaminated conditions and different fillers concentrations. The results show that the electrical resistivity of epoxy composites is increased with the increase of filler concentration. Maximum electrical resistivity (ohm.cm) value was obtained from micro Barium iodate composite with 25 wt% filler concentration.

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