An Approach to Condition Assessment of High-Voltage Insulators by Ultrasound and an Ensemble of Convolutional Neural Networks

This paper proposes an approach and proof of concept for evaluating the condition of high-voltage insulators of power distribution networks (up to 145 kV) using ultrasonic tests provided by a probe equipment in a methodology based on an ensemble of convolutional neural networks and robust pre-proces...

Full description

Saved in:

Bibliographic Details
Published in:	2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT) pp. 1 - 5
Main Authors:	De Souza Pereira Gomes, Gabriel, Araujo, Daniel Carrijo Polonio, De Campos, Arthur Franklim Marques, Da Silva, Frederico Dourado, Fehlberg, Rafael Prux, Sardinha, Bruno Fernandes, Rabelo, Danilo Amorim, Flauzino, Rogerio Andrade
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-02-2020
Subjects:	CNN Condition Assessment Distribution Networks Flowcharts Fourier Insulators Neural networks Power systems Smart grids Training Ultrasonic imaging
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	This paper proposes an approach and proof of concept for evaluating the condition of high-voltage insulators of power distribution networks (up to 145 kV) using ultrasonic tests provided by a probe equipment in a methodology based on an ensemble of convolutional neural networks and robust pre-processing techniques. It presents the laboratory tests and the conditions in which several real situations were simulated. Next, pre-processing, the neural network architectures and the flowchart of the insulation condition analysis methodology are detailed. Finally, the results of the diagnostics from the methodology with the training, validation and test sets are presented and discussed. The proposed methodology achieved 100% accuracy in validation and test data.
ISSN:	2472-8152
DOI:	10.1109/ISGT45199.2020.9087701