An Automatic Parameter Setting Variational Mode Decomposition Method for Vibration Signals
Aina Wang, Pan Qin, Xi‐Ming Sun, Yingshun Li
Abstract
Variational mode decomposition (VMD) provides a feasible approach to decompose vibration signals obtained from complex machinery for further applications. The mode frequency bandwidth control parameter and the total number of modes are critical parameters for VMD. Thus, optimally and automatically setting the two parameters is an essential issue for VMD for various practical vibration signal sources. To this end, this work proposes an automatic parameter setting VMD for vibration signals. First, we use the bandwidth evaluation criterion and the mean mode-location distance to evaluate the sparsity of modes; we use the energy loss to evaluate the reconstruction from modes. Then, we synthesize the three criteria into a novel optimization model using logarithmic transformation. Accordingly, a genetic algorithm (GA)-based solver is developed for the optimization model. Finally, the artificial multicomponent signal and the practical rolling bearing vibration signal from Case Western Reserve University (CWRU) Laboratory are used to verify the performance of the proposed optimization method.