Bearing Fault Diagnosis Using Lightweight and Robust One-Dimensional Convolution Neural Network in the Frequency Domain

The massive environmental noise interference and insufficient effective sample degradation data of the intelligent fault diagnosis performance methods pose an extremely concerning issue. Realising the challenge of developing a facile and straightforward model that resolves these problems, this study...

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Detalles Bibliográficos
Autores principales: Hakim, Mohammed, Omran, Abdoulhadi A. Borhana, Inayat-Hussain, Jawaid I., Ahmed, Ali Najah, Abdellatef, Hamdan, Abdellatif, Abdallah, Gheni, Hassan Muwafaq
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371231/
https://www.ncbi.nlm.nih.gov/pubmed/35957359
http://dx.doi.org/10.3390/s22155793

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9371231/
https://www.ncbi.nlm.nih.gov/pubmed/35957359
http://dx.doi.org/10.3390/s22155793

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