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

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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Auteurs principaux: B. Vigneshwaran, R.V. Maheswari, L. Kalaivani, Vimal Shanmuganathan, Seungmin Rho, Seifedine Kadry, Mi Young Lee
Format: article
Langue:EN
Publié: Elsevier 2021
Sujets:
Dual-input CNN
Convolution Neural Network
Bayesian optimization
Feature fusion
Training optimizer
High voltage insulator
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Accès en ligne:https://doaj.org/article/db1f6ec7a0df4bef991a0e487ca9daf5
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https://doaj.org/article/db1f6ec7a0df4bef991a0e487ca9daf5

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