The invention discloses a
voltage transformer error prediction method based on
modal decomposition and a gating circulation unit. The method comprises the following steps: 1, collecting historical error data of a
capacitor voltage transformer to construct a
time sequence data set; 2, dynamically adjusting a
noise amplitude coefficient based on
signal frequency domain characteristics by adopting an improved
modal decomposition method, and performing multiple
decomposition to obtain a mean
modal component; 3, calculating an information entropy value of each component, classifying the components according to the entropy values and the time-frequency graph, and carrying out
noise reduction on the high-entropy components by adopting a self-
adaptive wavelet packet threshold value; 4, designing a non-local attention mechanism enhanced
error signal prediction model, and dynamically fusing local
time sequence features and global context information through a gating coefficient; 5, establishing a sub-modal parallel training framework, performing modeling prediction on each component, and performing fusion output; and 6, performing model performance evaluation and
verification to verify the effectiveness of the method. The method effectively improves the prediction precision of the output
signal of the
voltage transformer, and can effectively meet the
signal prediction requirements under complex working conditions.