Cargando…
Power Equipment Fault Diagnosis Method Based on Energy Spectrogram and Deep Learning
With the development of industrial manufacturing intelligence, the role of rotating machinery in industrial production and life is more and more important. Aiming at the problems of the complex and changeable working environment of rolling bearings and limited computing ability, fault feature inform...
Autores principales: | Liu, Yiyang, Li, Fei, Guan, Qingbo, Zhao, Yang, Yan, Shuaihua |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9571516/ https://www.ncbi.nlm.nih.gov/pubmed/36236431 http://dx.doi.org/10.3390/s22197330 |
Ejemplares similares
-
Heart energy signature spectrogram for cardiovascular diagnosis
por: Kudriavtsev, Vladimir, et al.
Publicado: (2007) -
Research on Mechanical Equipment Fault Diagnosis Method Based on Deep Learning and Information Fusion
por: Jiang, Dongnian, et al.
Publicado: (2023) -
A Deep-Learning Method for Radar Micro-Doppler Spectrogram Restoration
por: He, Yuan, et al.
Publicado: (2020) -
A Deep Learning Method Approach for Sleep Stage Classification with EEG Spectrogram
por: Li, Chengfan, et al.
Publicado: (2022) -
Deep Learning With EEG Spectrograms in Rapid Eye Movement Behavior Disorder
por: Ruffini, Giulio, et al.
Publicado: (2019)