Research on EAST-NBI Experimental Data Analysis System Based on Neural Networks

The mismatch of the operating parameters of the NBI ion source of the nuclear fusion experimental device will lead to the instability of the plasma, and maybe cause breakdown in the ion source, which will limit the operation of the NBI long pulse and high power. To stabilize the plasma in the NBI ion source, data from multiple rounds of experiments along with a priori information obtained from a predictive plasma model are used. For the problem of low accuracy of the existing key-values extraction algorithms for experimental data, the OPTICS (Ordering Point To Identify the Cluster Structure) algorithm is used to improve the accuracy of the experimental data extraction, and provide a reference for the failure analysis during the experimental operation. A method based on self-organizing feature map (SOM) and BP neural network is adopted. By training historical data, the pulse width of the NBI ion source beam extraction process is estimated under given parameters to adjust the operating parameters.