Study on the State Prediction of a Pool-Cooled Large Superconducting Coil Using Machine Learning

Abstract

For the LHD subcooling system composed of pool-cooled large superconducting coils wound with NbTi superconductors, a machine learning technique was introduced to increase the reliability of the system. The machine learning model for the state prediction of the system was developed using the technique, together with the data accumulated in the LHD plasma experimental campaign. Regarding the temperature changes in the system due to coil excitation and discharging, it is possible to make predictions using the model. Especially for the usual coil current waveform in a helical coil operation, which is a trapezoidal waveform, the model achieved high prediction accuracy.