Wavelet-based multifractal analysis of large scale wind turbine main bearing

Abstract

The fault vibration signals of wind turbine are non-linear and non-stationary, thus it is difficult to obtain the obvious fault features. In this study, a multifractal method based on the wavelet transform modulus maxima (WTMM) method is used to investigate the main bearing incipient fault of large scale wind turbine. The real vibration signals are analyzed using the multifractal spectrum. The spectrum of the vibration signals is quantified by spectral characteristics including its range and the Hölder exponent corresponding to the maximum dimension. We find that the range of Hölder exponent of normal bearing is narrower than that of the bearing with incipient fault. And the results also indicate that the fault features are different at various wind turbine rotational frequencies. The results demonstrate that the multifractal spectrum obtained from WTMM method is effective to extract the incipient fault features of main bearing of large scale wind turbine.