The extraction of wind turbine rolling bearing fault features based on VMD and bispectrum

Abstract

Aiming at extracting wind turbine rolling bearing fault feature against the background noise, the method of based on variational mode decomposition and bispectrum were proposed. Firstly, the rolling bearing fault signal was decomposed using VMD. The two components, which had obvious impact features, were extracted and reconstructed using the kurtosis-correlation coefficient criteria. Secondly, the reconstructed signal was analyzed using the bispectrum. The method has good noise suppression capability. Lastly, according to the bispectrum analysis, the fault feature of rolling bearing could be extracted. The analysis of rolling bearing fault simulation signal verifies the effectiveness of the proposed method. And it was applied to extract the fault features of the bearing fault test signal. The different fault features of rolling bearing could be identified effectively. Thus the fault diagnosis can be achieved accurately.