Checking the Status of High Voltage Disconnection Switches Using Siamese Convolutional Neural Networks

Autores

  • Celso Soares Godoy IFES - Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo
  • Marcelo Denadai Marcon IFES - Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo
  • Gustavo Maia de Almeida IFES - Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo
  • Daniel Cruz Cavalieri IFES - Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo
  • Cassius Zanetti Resende IFES - Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo

DOI:

https://doi.org/10.55592/cilamce.v6i06.10146

Palavras-chave:

Power Substation, Disconnection Switches, Siamese Convolutional Neural Network

Resumo

A high voltage power substation is an electrical installation made up of equipment responsible for transmission and distribution of energy for voltages above 69kV and below 230kV. Necessary to keeping our homes and industries running, a substation has various power equipment such as circuits breakers, power transformers and disconnection switches that guarantee its operation. These devices can be controlled locally or remotely way, either through control systems or manually by a human operator.
One of the fundamental pieces of equipment to guarantee the operation of a substation is a disconnection switch. Disconnection switches are electromechanical equipment composed by moving parts, in a conventional substation. This equipment is subject to mechanical efforts, vibration and temperature. The wrong functioning of a disconnection switch can cause major losses for the company, from equipment downtime to a complete lack of power to the plant.
With the aim of contributing to avoiding failures in the operation of an industrial substation, this work proposes the use of artificial intelligence (AI) and machine learning techniques, through computer vision based on the Siamese convolutional neural network to verify the disconnection switches opened and closed status of a power substation in a steel industry.

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Publicado

2024-12-02