CNN-based real-time video detection of plasma instability in nuclear fusion applications

P. Arena, A. Basile, L. Fortuna, G. Mazzitelli, A. Rizzo, M. Zammataro

Research output: Contribution to conferencePaper

2 Citations (Scopus)

Abstract

In this paper a real-time detection of plasma instabilities, called MARFEs, is performed through a real-time image processing on plasma video sequences. These sequences are recorded by a vision system based on a CCD camera installed at Frascati Tokamak Upgrade (FTU). The strategy used to perform the task is based on a new family of nonlinear analog processors, digitally programmable, implemented into the so-called Cellular Neural Network Universal Machine (CNN-UM). The detection system allows to carry out safer nuclear fusion experiments, preventing the plant from excessive mechanical and thermal stress which occurs during plasma instability phenomena (i.e. disruptions). Experimental results, obtained on the FTU machine, are fully satisfactory.
Original languageEnglish
Publication statusPublished - 2004
Externally publishedYes
Event2004 IEEE International Symposium on Cirquits and Systems - Proceedings - , Canada
Duration: 1 Jan 2004 → …

Conference

Conference2004 IEEE International Symposium on Cirquits and Systems - Proceedings
CountryCanada
Period1/1/04 → …

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Arena, P., Basile, A., Fortuna, L., Mazzitelli, G., Rizzo, A., & Zammataro, M. (2004). CNN-based real-time video detection of plasma instability in nuclear fusion applications. Paper presented at 2004 IEEE International Symposium on Cirquits and Systems - Proceedings, Canada.