Keywords
Variational mode decomposition
Genetic algorithm
Adaptive optimization
Submitted : 2023-12-19
Accepted : 2024-01-03
Published : 2024-01-18
Abstract
In order to further analyze the micro-motion modulation signals generated by rotating components and extractmicro-motion features, a modulation signal denoising algorithm based on improved variational mode decomposition (VMD)is proposed. To improve the time-frequency performance, this method decomposes the data into narrowband signalsand analyzes the internal energy and frequency variations within the signal. Genetic algorithms are used to adaptivelyoptimize the mode number and bandwidth control parameters in the process of VMD. This approach aims to obtain theoptimal parameter combination and perform mode decomposition on the micro-motion modulation signal. The optimalmode number and quadratic penalty factor for VMD are determined. Based on the optimal values of the mode numberand quadratic penalty factor, the original signal is decomposed using VMD, resulting in optimal mode number intrinsicmode function (IMF) components. The effective modes are then reconstructed with the denoised modes, achieving signaldenoising. Through experimental data verification, the proposed algorithm demonstrates effective denoising of modulationsignals. In simulation data validation, the algorithm achieves the highest signal-to-noise ratio (SNR) and exhibits the bestperformance.
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