Wind Turbine Fault Diagnosis Based on Adaptive High-frequency Harmonics LMD

To solve the mode mixing problem of local mean decomposition (LMD) in actual applications, an adaptive high-frequency harmonics LMD was proposed. The effect of abnormal events on the envelope function and mean function was analyzed, and the adaptive high-frequency harmonics were constructed and added into the signal to deal with the mode mixing problem by changing the distribution of extreme points of the original signal. Simulation comparison was made to signals containing typical abnormal events between adaptive high-frequency harmonics LMD (AHLMD) and ensemble LMD (ELMD), illustrating the effectiveness and superiority of AHLMD, which was subsequently applied to fault diagnosis for the drive train system of a wind turbine. Results show that the mode mixing situation can be improved significantly and the shaft unbalance characteristics can be extracted successfully via the method, which therefore may serve as a reference for fault diagnosis of wind turbines.