Neural networks for real time determination of radiated power in JET

TitleNeural networks for real time determination of radiated power in JET
Publication TypeJournal Article
Year of Publication2002
AuthorsO. Barana, A. Murari, P. Franz, L.C Ingesson, G. Manduchi
JournalReview of Scientific Instruments
Volume73
Number5
Pagination2038-2043
Date PublishedMay
Type of ArticleArticle
ISBN Number0034-6748
Accession NumberISI:000175194200009
KeywordsRFX
Abstract

This article describes the use of neural networks (NNs) for the on-line computation of the radiated power in JET. The NNs have been trained using a database of about 120 discharges, for which the emitted power had been calculated via tomographic inversion of JET bolometric signals. In addition to the bolometric data, elongation and triangularity have been used as input to the NN, since these provide useful complementary information. Dedicated NNs have been designed for the determination of the total radiated power, the power from the bulk, and from the divertor region. All the NNs have been tested with a set of about 30 discharges with positive results. Moreover, the NNs can operate at full sampling speed and are therefore suited to follow edge localized modes and other rapid phenomena. The sensitivity of the NNs to failures in the input signals has also been tested, proving their robustness. Their possible use in feedback applications is finally briefly discussed. (C) 2002 American Institute of Physics.

URL<Go to ISI>://000175194200009
Division

Fusion Physics

Department

Instrumentation development

PID

45958c7bc8e4c6905648bcfd32d829a1

Alternate TitleRev. Sci. Instrum.

Go back one page.