The invention discloses a galloping early warning method for a wind
turbine generator group in the same offshore
wind field, and the method comprises the following steps: 1, obtaining the operation data of a certain group of offshore wind
turbine generators, carrying out the data preprocessing,
correlation analysis and
feature screening, and obtaining a
data set; 2, constructing an XGBoost model, and carrying out training until the
model prediction effect is optimal, so as to obtain an optimal XGBoost model; and step 3, through the optimal XGBoost model, predicting the average generator speed of the group of offshore wind
turbine generators, and monitoring the difference value between a predicted value and a true value to complete galloping early warning of the group of offshore wind turbine generators. And 4, performing
data filling through a
GAIN network, and migrating the data to other offshore wind turbine generators of the same wind farm by utilizing migration learning to realize galloping early warning of all the offshore wind turbine generators of the whole wind farm. The galloping early warning and monitoring accuracy can be improved, and the galloping monitoring hidden danger and early warning cost of the offshore wind turbine generator can be reduced.