Application of the ensemble empirical mode decomposition and Hilbert transform to pedestal looseness study of direct-drive wind turbine

Abstract

The fault signal problems of wind turbine are non-linear and non-stationary, thus it is difficult to obtain the obvious fault features. In this study, a time-frequency method based on EEMD (ensemble empirical mode decomposition) and Hilbert transform is presented to investigate the bearing pedestal looseness fault of direct-drive wind turbine. The real vibration signals are analyzed using IMFs (intrinsic mode functions) extracted by ensemble empirical mode decomposition and Hilbert spectrum in the proposed method. The experimental results indicate that the proposed method is effective to extract the fault features of bearing pedestal looseness of wind turbine. And the results also demonstrate that fault features of front bearing pedestal looseness are different from rear bearing pedestal looseness with the same looseness gap. The fluctuation of rotational frequency increases with the occurrence of front bearing pedestal looseness fault, especially the half rotational frequency and high-frequency components, and the shaft orbit is complex. Besides, we found that when the rear bearing pedestal is loosen, the fluctuation of rotational frequency also increases, and the half rotational frequency component can be found. But for the high-frequency components, it is not obvious, and the shaft orbit is an approximate ellipse. Although the fault features of front and rear bearing pedestal looseness are obvious, the powers generated by wind turbine generator only change slightly.