Remaining Useful Life Prognosis for Turbofan Engine Using Explainable Deep Neural Networks with Dimensionality Reduction.

Hong, Chang Woo; Lee, Changmin; Lee, Kwangsuk; Ko, Min-Seung; Kim, Dae Eun; Hur, Kyeon

Hong, Chang Woo; Lee, Changmin; Lee, Kwangsuk; Ko, Min-Seung; Kim, Dae Eun; Hur, Kyeon.

Afiliación

Hong CW; School of Electrical & Electronic Engineering, Yonsei University, 50 Yonsei-Ro Seodamun-Gu, Seoul 03722, Korea.
Lee C; School of Electrical & Electronic Engineering, Yonsei University, 50 Yonsei-Ro Seodamun-Gu, Seoul 03722, Korea.
Lee K; School of Electrical & Electronic Engineering, Yonsei University, 50 Yonsei-Ro Seodamun-Gu, Seoul 03722, Korea.
Ko MS; School of Electrical & Electronic Engineering, Yonsei University, 50 Yonsei-Ro Seodamun-Gu, Seoul 03722, Korea.
Kim DE; School of Electrical & Electronic Engineering, Yonsei University, 50 Yonsei-Ro Seodamun-Gu, Seoul 03722, Korea.
Hur K; School of Electrical & Electronic Engineering, Yonsei University, 50 Yonsei-Ro Seodamun-Gu, Seoul 03722, Korea.

Sensors (Basel) ; 20(22)2020 Nov 19.

Article en En | MEDLINE | ID: mdl-33228051

Palabras clave

deep neural network; dimensionality reduction; explainable artificial intelligence; feature selection; prognostics and health monitoring; turbofan engine

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2020 Tipo del documento: Article Pais de publicación: Suiza

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