This invention discloses a method for judging and correcting the flattening phenomenon of wind
turbine blade root load, comprising the following steps: acquiring real-time blade load data under grid-connected operation of the wind
turbine; judging whether the blade root oscillation load data in the real-time blade load data has a flattening phenomenon; judging whether it needs to be merged into a single flattening segment based on the interval between each flattening segment, and calculating the cumulative duration of the flattening segment; judging whether the cumulative duration is not greater than a preset cumulative duration threshold; extracting features of the normal segment located in the previous cycle of each flattening segment from the blade root oscillation load data; generating replacement loads for the flattening segment based on the features and performing segment-by-sine replacement on each flattening segment, while smoothly connecting the start and end points of the flattening segment to complete the correction of the flattening phenomenon of wind
turbine blade root load. This invention corrects flattening through
feature extraction and sinusoidal
load generation, meeting the
load testing accuracy requirements, avoiding long-term wind turbine shutdowns, and reducing power generation losses.