2021-07-062021-07-062021-06-03SILVA, William Machado da. Prognóstico de falhas baseado em redes neurais convolucionais: uma análise para estimar a vida útil remanescente de turbinas turbofan. Orientador: Rafael Suzuki Bayma. 2021. 59 f. Trabalho de Curso (Bacharelado em Engenharia Elétrica) – Faculdade de Engenharia Elétrica, Campus Universitário de Tucuruí, Universidade Federal do Pará, Tucuruí, 2021. Disponível em: https://bdm.ufpa.br:8443/jspui/handle/prefix/3372. Acesso em:.https://bdm.ufpa.br/handle/prefix/3372This work proposes a deep learning method for estimating the remaining useful life (RUL) of turbofan turbines. It presents a convolutional neural network (CNN) architecture. The proposed method is applied to a NASA data set for the RUL estimate, by varying the set of sensors and the form of turbine degradation in two models: linear RUL and piecewise linear RUL. Experimental results are compared with each other and with other methods found in the literature; the results show that the proposed piecewise linear RUL method exhibits similar performance found in other published works in terms of root mean squared error and a specific error metric used in competitions.Acesso AbertoAprendizado profundo ( Aprendizado do computador)Redes neurais convolucionaisManutenção e reparosVida útil (Engenharia)CNPQ::ENGENHARIASTrabalho de Curso - Graduação - Monografia