Design of an artificial neural network for the estimation of the flashover voltage on insulators

This work attempts to apply an artificial neural network in order to estimate the critical flashover voltage on polluted insulators. The artificial neural network uses as input variables the following characteristics of the insulator: diameter, height, creepage distance, form factor and equivalent s...

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Bibliographic Details
Published in:	Electric power systems research Vol. 77; no. 12; pp. 1532 - 1540
Main Authors:	Kontargyri, V.T., Gialketsi, A.A., Tsekouras, G.J., Gonos, I.F., Stathopulos, I.A.
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 01-10-2007 Elsevier
Subjects:	Applied sciences Artificial neural network Connection and protection apparatus Critical flashover voltage Electrical engineering. Electrical power engineering Exact sciences and technology High voltage insulators Insulators Materials Polluted insulators Various equipment and components High voltage insulators Critical flashover voltage Artificial neural network Polluted insulators Performance evaluation Dielectric materials High voltage insulator Neural network Critical voltage Electric discharge Learning Salt Electric insulating material Electrical flashover Mathematical model Train Form factor
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