Memorias de investigación
Ponencias en congresos:
Automatic recognition of plasma relevant events: implications for ITER
Año:2019
Áreas de investigación
  • Inteligencia artificial,
  • Futuros experimentos
Datos
Descripción
This work makes a proposal about the use of big data techniques for the automatic recognition and classification of plasma relevant events in huge databases of nuclear fusion devices. A relevant event can be any kind of anomaly (or perturbation) in the plasma evolution. This is revealed in the temporal evolution signals as (typically) abrupt variations (for instance in amplitude, noise, or sudden presence/suppression of patterns with periodical structure). A general algorithm based on five steps is presented here for the automatic location and unsupervised classification of plasma events: dataset selection, location of anomalies in individual signals, definition of multi-signal patterns, unsupervised clustering of multi-signal patterns and creation of supervised classifiers. It is important to note that the algorithm implementation is for off-line analysis but supervised classifiers could be implemented under real-time conditions.
Internacional
Si
Nombre congreso
12th IAEA Technical Meeting on Control, Data Acquisition and Remote Participation for Fusion Research (CODAC 2019)
Tipo de participación
960
Lugar del congreso
Daejeon
Revisores
Si
ISBN o ISSN
CDP08UPM
DOI
Fecha inicio congreso
13/05/2019
Fecha fin congreso
17/05/2019
Desde la página
1
Hasta la página
20
Título de las actas
Proceedings Online IAEA 2019
Esta actividad pertenece a memorias de investigación
Participantes
  • Autor: Jesus Vega CIEMAT
  • Autor: Rodrigo Castro CIEMAT
  • Autor: Sebastian Dormido-Canto UNED
  • Autor: Giuseppe Ratta CIEMAT
  • Autor: Mariano Ruiz Gonzalez UPM
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Investigación en Instrumentación y Acústica Aplicada (I2A2)
  • Departamento: Ingeniería Telemática y Electrónica