Transformer surface temperature based on VMD-BiGRU-MHA prediction method research

Increase Accuracy of Transformer Ground Temperature Prediction, this paper proposes a new approach to forecast transformer earth temperature using Variable Mode Decay (VMD), two-way gated recurrence (BGRU) and multi-attention mechanism (MHA). In the VMD-BiGRU-MHA model, firstly, an environmental monitoring device is built to obtain the weather data near the transformer and eliminate the weakly correlated parameters, and then the raw data are decomposed into several sub-sequences using VMD to get the more stable individual components, which are then inputted into BiGRU for training, and then finally, MHA is introduced to mine the features of the time-series long-range data of the transformer surface temperature. Thus, prediction precision is increased. Comparison between BiGRU and VMD-BiGRU indicates that the predicted error is smaller than that of VMD-BiGRU.