基于LightGBM的EAST杂质破裂预警

对全超导托卡马克核聚变实验装置东方超环(EAST)运行放电期间发生的杂质破裂进行预测对未来的聚变装置的长脉冲稳态放电有重要意义. 根据杂质破裂的物理特性筛选出的2018年的334炮杂质破裂炮数据以及2021年的1628炮非破裂炮作为训练炮, 再由等离子体平衡、密度、电流以及辐射等8种诊断信号组成的训练样本以LightGBM算法训练出杂质破裂预测模型. 实验结果表明LightGBM算法模型可以对杂质破裂进行准确预测(成功预测率96.29%), 非破裂炮的误判率6.87%. 研究结果证明利用LightGBM进行EAST等离子体杂质破裂预警是可行的方案.

Prediction of EAST Impurity Disruption Using LightGBM

The prediction of impurity disruption during the discharge period of experimental advanced superconducting tokamak (EAST) is of great significance for the long-pulse steady-state discharge of future EAST. According to the physical characteristics of impurity disruption, the data of 334 impurity disruptive discharges in 2018 and 1 628 non-disruptive discharges in 2021 are selected as training discharges. Then, the training samples composed of eight diagnostic signals, including plasma equilibrium, density, current, and radiation signals, are used to train the impurity disruption prediction model by LightGBM. The test results reveal that the LightGBM model can accurately predict the impurity disruption, with a success rate of 96.29%, while for non-disruptive discharges, the false positive rate is 6.87%. The research results indicate that it is feasible to use LightGBM to predict plasma impurity disruption of EAST.