Cargando…
A Novel Image-Based Diagnosis Method Using Improved DCGAN for Rotating Machinery
Rotating machinery plays an important role in industrial systems, and faults in the machinery may damage the system health. A novel image-based diagnosis method using improved deep convolutional generative adversarial networks (DCGAN) is proposed for the feature recognition and fault classification...
Autores principales: | Gao, Yangde, Piltan, Farzin, Kim, Jong-Myon |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9570832/ https://www.ncbi.nlm.nih.gov/pubmed/36236633 http://dx.doi.org/10.3390/s22197534 |
Ejemplares similares
-
A Novel Hybrid Deep Learning Method for Fault Diagnosis of Rotating Machinery Based on Extended WDCNN and Long Short-Term Memory
por: Gao, Yangde, et al.
Publicado: (2021) -
A Hybrid Leak Localization Approach Using Acoustic Emission for Industrial Pipelines
por: Gao, Yangde, et al.
Publicado: (2022) -
Bearing Fault Diagnosis Using an Extended Variable Structure Feedback Linearization Observer
por: Piltan, Farzin, et al.
Publicado: (2018) -
Bearing Fault Diagnosis by a Robust Higher-Order Super-Twisting Sliding Mode Observer
por: Piltan, Farzin, et al.
Publicado: (2018) -
Bearing Fault Diagnosis Using a Hybrid Fuzzy V-Structure Fault Estimator Scheme
por: Piltan, Farzin, et al.
Publicado: (2023)