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Variational mode decomposition (VMD) method has been widely used in the field of signal processing with significant advantages over other decomposition methods in eliminating modal aliasing and noise robustness. The number (usually denoted by  K ) of intrinsic mode function (IMF) has a great influence on decomposition results. When dealing with signals including complex components, it is usually impossible for the existing methods to obtain correct results and also effective methods for determining  K  value are lacking. A method called center frequency statistical analysis (CFSA) is proposed in this paper to determine  K  value. CFSA method can obtain  K  value accurately based on center frequency histogram. To shed further light on its performance, we analyze the behavior of CFSA method with simulation signal in the presence of variable components amplitude, components frequency, and components number as well as noise amplitude. The normal and fault vibration signals obtained from a bearing experimental setup are used to verify the method. Compared with maximum center frequency observation (MCFO), correlation coefficient (CC), and normalized mutual information (NMI) methods, CFSA is more robust and accurate, and the center frequencies results are consistent with the main frequencies in FFT spectrum.

A Method for Determining Intrinsic Mode Function Number in Variational Mode Decomposition and Its Application to Bearing Vibration Signal Processing