Fault Diagnosis of Electric Motors Using Deep Learning Algorithms and Its Application: A Review
Electric motors are used extensively in numerous industries, and their failure can result not only in machine damage but also a slew of other issues, such as financial loss, injuries, etc. As a result, there is a significant scope to use robust fault diagnosis technology. In recent years, interestin...
Guardado en:
Autores principales: | Yuanyuan Yang, Md Muhie Menul Haque, Dongling Bai, Wei Tang |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/0e5aae5a74ea4ff79792e1b994efad83 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
A Novel Lidar Signal Denoising Method Based on Convolutional Autoencoding Deep Learning Neural Network
por: Minghuan Hu, et al.
Publicado: (2021) -
Review of Image Classification Algorithms Based on Convolutional Neural Networks
por: Leiyu Chen, et al.
Publicado: (2021) -
A Convolutional Autoencoder Topology for Classification in High-Dimensional Noisy Image Datasets
por: Emmanuel Pintelas, et al.
Publicado: (2021) -
Using a Hybrid Neural Network Model DCNN–LSTM for Image-Based Nitrogen Nutrition Diagnosis in Muskmelon
por: Liying Chang, et al.
Publicado: (2021) -
Intelligent Fault Diagnosis Method of Wind Turbines Planetary Gearboxes Based on a Multi-Scale Dense Fusion Network
por: Xinghua Huang, et al.
Publicado: (2021)