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