Development of High-Speed Image Acquisition and Processing System for Real-Time Plasma Control on EAST

In order to realize advanced plasma control based on visible cameras, a high-speed image acquisition and processing system has been developed recently on Experimental Advanced Superconducting Tokamak (EAST). This system is optimized in many ways to achieve high-speed, real-time, low-latency performance, and to load multiple acquisition cards simultaneously. The acquisition rate of this system can be close to 10 000 FPS when the frame size is set as 320
$\times240$
and the pixel depth is set as 8 bits. DMA is used for high-speed data transmission; the memory copy function is optimized for reducing the time cost on data memory reading and writing. Besides, the visualization subsystem based on the Python web can communicate with the acquisition machines and also can synthesize data of multiple acquisition machines in real time to perform image fusion and access display. In addition, a thermal event recognition function based on visible imaging is also included in this system. The convolutional neural network (CNN) model of hot spots and multifaceted asymmetric radiation from the edge (MARFE) detection for EAST plasma discharge has been developed so far. The detection results can be visualized in quasi-real time. In terms of data storage, a new data storage format is designed; a GUI for off-line data analysis and processing based on MATLAB is provided.