Abstract：The setting of modal number in the variational mode decomposition is very important for the decomposition results, based on this, a method to obtain the optimal decomposition layer number is proposed. This method is based on amplitude characteristics of the instantaneous frequencies and determines the optimal decomposition parameter by analyzing the relationship between the maximum amplitude (MA) of each component in the VMD decomposition process. The root mean square entropy can reflect the energy of different vibration signals and is used as the characteristic parameter of the fault. And a fault classification model is established by optimized support vector machine to realize fault patterns classification. The fault diagnosis method based on MA-VMD and root mean square entropy is applied to the measured signal of rolling bearings. The results show that the method based on MA-VMD and root mean square entropy can identify rolling bearing running state efficiently and realize rolling bearing fault diagnosis. The recognition accuracy of this method is 98.75%.
2020, Vol. 41 
