Wind turbine generator system fault intelligent diagnosis and early warning method based on random forests

The invention discloses a wind turbine generator system fault intelligent diagnosis and early warning method based on random forests. The wind turbine generator system fault intelligent diagnosis and early warning method based on random forests includes the steps: extracting the historical data of the wind turbine generator system state as the sample data; performing exploratory analysis and preprocessing on the sample data; constructing a wind turbine generator system fault intelligent diagnosis and early warning model based on random forests, and analyzing and evaluating the model according to the model result; utilizing the model after analysis and evaluation to perform real-time diagnosis on wind turbine generator system equipment; and if the diagnosis result is not normal, sending out an alarm information by the model. The wind turbine generator system fault intelligent diagnosis and early warning method based on random forests utilizes the random forest algorithm and considers the overall characteristic