Diagnóstico de Falhas em Máquinas de Indução Via Imagens Térmicas Utilizando Redes Neurais Convolucionais

Jonathan dos Santos Cruz; Mateus Giesbrecht

doi:10.20906/sbai.v1i1.2562

Jonathan dos Santos Cruz Faculdade de Engenharia Elétrica e de Computação, Universidade Estadual de Campinas, SP
Mateus Giesbrecht Faculdade de Engenharia Elétrica e de Computação, Universidade Estadual de Campinas, SP

DOI: https://doi.org/10.20906/sbai.v1i1.2562

Keywords: Motor, Classification, Machine learning, Operation conditions, Region of interest

Abstract

In this article, an algorithm combining the Region of Interest identification technique and a Convolutional Neural Network model to diagnose faults in an induction motor is introduced. The algorithm developed in PYTHON on the Google Colab platform was applied to classify 10 different failure modes and the healthy operation of an induction motor, presenting a classification accuracy superior than the Decision Tree, Random Forest, Support Vector Machine and K - Nearest Neighbors.