bachelorThesis
Análise de falhas em rotor utilizando deep neural networks
Date
2019-06-24Registration in:
EVANGELISTA, Jonathan José. Análise de falhas em rotor utilizando deep neural networks. 2019. Trabalho de Conclusão de Curso (Bacharelado em Engenharia Elétrica) - Universidade Tecnológica Federal do Paraná, Cornélio Procópio, 2019.
Author
Evangelista, Jonathan José
Institutions
Abstract
More than half of the total energy destined for the industrial sector is consumed by engines. Stopping production to correct motor system failures can generate some risks and also serious losses for a given company. Early determination of these faults can prevent unscheduled maintenance and a halt in the production process. Considering a three-phase induction motor and evaluating its electrical system, we can prevent some rotor-related faults, where this proposal of completion work exposes a study related to the diagnosis of rotor faults of an MIT, using current signals in the field of frequency, where the classification of failures will be made from Deep Neural Network.