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.
|Publication status||Published - 2004|
|Event||2004 IEEE International Symposium on Cirquits and Systems - Proceedings - , Canada|
Duration: 1 Jan 2004 → …
|Conference||2004 IEEE International Symposium on Cirquits and Systems - Proceedings|
|Period||1/1/04 → …|
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
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.