Abstract: Aiming at the problem of very weak surface magnetic resonance  signals  and  susceptibility to electromagnetic noise interference, 
we proposed a harmonic noise reduction method for surface magnetic resonance based on variational mode decomposition.  This method adopted an improved variational mode decomposition-based method for power frequency harmonic elimination, and set the mode number and initial center frequency according to spectral analysis, solving the problem of slow computational efficiency caused by  conventional harmonic modeling denoising methods, which could only handle single-acquisition data. The experimental results show that the method achieves good effect of  harmonic component estimation in complex noise scenarios such as  multiple fundamental  frequencies or fundamental frequency variations over time,  and can  quickly and effectively eliminate power frequency  harmonic interference, significantly improving the signal-to-noise ratio of surface  magnetic resonance detection data.

Key words: variational mode decomposition, surface magnetic resonance, harmonic interference, fundamental frequency variation