Recognition of pollution layer location in 11 kV polymer insulators used in smart power grid using dual-input VGG Convolutional Neural Network

This paper portrays the application of a Partial Discharge (PD) signal combined with the dual-input VGG Convolution Neural Network (CNN) to predict the location of the pollution layer on 11 kV polymer insulators subjected to alternating current for smart grid applications. First, a non-uniform pollu...

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Detalles Bibliográficos
Autores principales:	B. Vigneshwaran, R.V. Maheswari, L. Kalaivani, Vimal Shanmuganathan, Seungmin Rho, Seifedine Kadry, Mi Young Lee
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Dual-input CNN Convolution Neural Network Bayesian optimization Feature fusion Training optimizer High voltage insulator Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/db1f6ec7a0df4bef991a0e487ca9daf5
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Recognition of pollution layer location in 11 kV polymer insulators used in smart power grid using dual-input VGG Convolutional Neural Network

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