Cargando…
Towards Precise Interpretation of Oil Transformers via Novel Combined Techniques Based on DGA and Partial Discharge Sensors
Power transformers are considered important and expensive items in electrical power networks. In this regard, the early discovery of potential faults in transformers considering datasets collected from diverse sensors can guarantee the continuous operation of electrical systems. Indeed, the disconti...
Autores principales: | Ward, Sayed A., El-Faraskoury, Adel, Badawi, Mohamed, Ibrahim, Shimaa A., Mahmoud, Karar, Lehtonen, Matti, Darwish, Mohamed M. F. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8005011/ https://www.ncbi.nlm.nih.gov/pubmed/33810187 http://dx.doi.org/10.3390/s21062223 |
Ejemplares similares
-
Reliable Industry 4.0 Based on Machine Learning and IoT for Analyzing, Monitoring, and Securing Smart Meters
por: Elsisi, Mahmoud, et al.
Publicado: (2021) -
Promising MPPT Methods Combining Metaheuristic, Fuzzy-Logic and ANN Techniques for Grid-Connected Photovoltaic †
por: Ali, Mahmoud N., et al.
Publicado: (2021) -
Deep Learning-Based Industry 4.0 and Internet of Things towards Effective Energy Management for Smart Buildings
por: Elsisi, Mahmoud, et al.
Publicado: (2021) -
Influence of Oil Status on Membrane-Based Gas–Oil Separation in DGA
por: Chen, Tunan, et al.
Publicado: (2022) -
Proposed ANFIS Based Approach for Fault Tracking, Detection, Clearing and Rearrangement for Photovoltaic System
por: Bendary, Ahmed F., et al.
Publicado: (2021)