Prognóstico de falhas baseado em redes neurais convolucionais: uma análise para estimar a vida útil remanescente de turbinas turbofan
This 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...
| Autor principal: | SILVA, William Machado da |
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| Grau: | Trabalho de Curso - Graduação - Monografia |
| Idioma: | por |
| Publicado em: |
2021
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| Assuntos: | |
| Acesso em linha: |
https://bdm.ufpa.br:8443/jspui/handle/prefix/3372 |
| Resumo: |
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This 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. |