Fault Diagnosis Method of Offshore Wind Turbine Gearbox Bearing Based on MCKD
The gearbox of offshore wind turbines features a complex structure that is susceptible to faults.Additionally,the characteristic signals of bearing faults are challenging to extract due to significant noise interference during wind turbine operation.To tackle these challenges,a fault diagnosis method based on Maximum Correlation Kurtosis Deconvolution(MCKD)is proposed.The MCKD algorithm is used to denoise and enhance the feature of the vibration signal,and the enhanced envelope spectrum is used to extract the fault characteristic frequency of the bearing,so as to realize the fault diagnosis of the bearing.The method is applied to the analog signal and the measured signal of the gearbox bearing of the offshore wind turbine.The results show that the method has a good effect on the feature extraction and diagnosis of the gearbox bearing fault in a strong noise environment.
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