Multi-Layer Perceptron para Detecção de Faltas em Aerogeradores Baseados na Máquina de Indução com Rotor em Gaiola

  • Anderson Egberto Cavalcante Salles Departamento de Informática e Matemática Aplicada, Universidade Federal do Rio Grande do Norte, RN
  • Marcio Eduardo Kreutz Departamento de Informática e Matemática Aplicada, Universidade Federal do Rio Grande do Norte, RN
  • Luciano Sales Barros Departamento de Sistemas de Computação, Universidade Federal da Paraíba, PB
Keywords: Multi-Layer perceptron, Wind turbine, Smart grid, Turn-to-ground fault, Turn-to-turn fault

Abstract

In this study a application proposal to develop a classifier using an artificial neural network (ANN) for the problem of detecting internal faults in a wind turbine generator based on an induction machine with a caged rotor, a problem for which there is still no optimal solution. The classifier evaluates a given instance and returns whether the instance comes from a healthy machine or a machine that has a stator coil fault. Synthetic data obtained by simulation was used for training the ANN. The results obtained demonstrate that a simple network with a single intermediate layer already achieves good performance with low computational cost as the memory to store the ANN.
Published
2021-10-20
Section
Articles