Cargando…
Protection of Superconducting Industrial Machinery Using RNN-Based Anomaly Detection for Implementation in Smart Sensor
Sensing the voltage developed over a superconducting object is very important in order to make superconducting installation safe. An increase in the resistive part of this voltage (quench) can lead to significant deterioration or even to the destruction of the superconducting device. Therefore, dete...
Autores principales: | Wielgosz, Maciej, Skoczeń, Andrzej, De Matteis, Ernesto |
---|---|
Lenguaje: | eng |
Publicado: |
2018
|
Materias: | |
Acceso en línea: | https://dx.doi.org/10.3390/s18113933 http://cds.cern.ch/record/2648043 |
Ejemplares similares
-
Protection of Superconducting Industrial Machinery Using RNN-Based Anomaly Detection for Implementation in Smart Sensor †
por: Wielgosz, Maciej, et al.
Publicado: (2018) -
The model of an anomaly detector for HiLumi LHC magnets based on Recurrent Neural Networks and adaptive quantization
por: Wielgosz, Maciej, et al.
Publicado: (2017) -
Recurrent Neural Networks for anomaly detection in the Post-Mortem time series of LHC superconducting magnets
por: Wielgosz, Maciej, et al.
Publicado: (2017) -
Using LSTM recurrent neural networks for monitoring the LHC superconducting magnets
por: Wielgosz, Maciej, et al.
Publicado: (2016) -
RNN- and LSTM-Based Soft Sensors Transferability for an Industrial Process
por: Curreri, Francesco, et al.
Publicado: (2021)