Accurate oscillation mode recognition and stability analysis based on big data are critical for the safe operation of wind turbine systems. This paper utilizes modern statistical and machine learning methodology to analyze the correlation between monitored wind turbine operation data and oscillation phenomena, and a system oscillation analysis and diagnosis method is proposed based on an improved association rule mining (ARM) model. Firstly, the oscillation modes in the power data are measured by the synchronous extraction transform. By improving the ARM model, a thorough study is conducted on...
