Fault Diagnosis Method of Wind Turbine Bearing Based on Improved Intrinsic Time-scale Decomposition and Spectral Kurtosis

Based on the linear transformation of intrinsic time-scale Decomposition (ITD) method and cubic spline interpolation, this paper proposes an Improved Intrinsic Time-scale Decomposition method (IITD). The IITD method and Spectrum Kurtosis (SK) are combined to realize the intelligent diagnosis of bearing faults. Simulation and experimental results show that the IITD-SK method proposed in this paper successfully extracts the fault feature frequency, and can realize effective diagnosis of bearing faults. Compared with the results of traditional Fourier transform, envelope spectrum analysis and EMD method, this method has a better diagnosis effect.