A Novel Method for Identifying Crack and Shaft Misalignment Faults in Rotor Systems under Noisy Environments Based on CNN.

Zhao, Wang; Hua, Chunrong; Dong, Dawei; Ouyang, Huajiang

Zhao, Wang; Hua, Chunrong; Dong, Dawei; Ouyang, Huajiang.

Afiliación

Zhao W; School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China.
Hua C; School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China.
Dong D; School of Mechanical Engineering, Southwest Jiaotong University, Chengdu 610031, China.
Ouyang H; School of Engineering, University of Liverpool, Liverpool L69 3GH, UK.

Sensors (Basel) ; 19(23)2019 Nov 25.

Article en En | MEDLINE | ID: mdl-31775317

Palabras clave

convolutional neural network; crack; fault identification; noisy environment; shaft misalignment

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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: 2019 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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