In the context of constructing digital power grid, there has been significant attention on the methods to accurately and promptly obtain the physical field information of power equipment. The numerical methods, such as finite element analysis (FEA), are limited by offline computation and cannot meet the safety and timeliness requirements of the power grid. In this letter, a method based on deep neural networks (DNN) is proposed for rapidly predicting the magnetic field distribution of reactors. After training on magnetic field data generated by FEA simulation, the DNN takes the reactor current...
