Transient Electromagnetic Data Noise Suppression Method Based on MPA-VMD-SVD

The transient electromagnetic method (TEM) is an efficient physical detection method widely used in underground space detection. However, electromagnetic noise interference poses significant challenges, as the TEM late signal is often submerged in noise, severely impacting the detection accuracy and depth. Therefore, this study proposes a TEM data noise suppression method based on the marine predators algorithm (MPA) to optimize variational mode decomposition (VMD) combined with singular value decomposition (SVD). Firstly, MPA is employed to select the main parameters of VMD. Secondly, the noisy data are decomposed into several intrinsic mode functions using the adaptive variational property of VMD. Finally, the mode containing signal information undergoes SVD to remove residual noise, after which the denoised TEM signal is reconstructed. This study simulates TEM signals with different noise levels for testing. The proposed method is compared to stacking-averaging, wavelet threshold denoising, SVD, empirical mode decomposition, and unoptimized VMD. The results showed that the model exhibits superior noise reduction performance. In addition, measured noise experiments are conducted to verify the practicability of the method. Simulation and field experiments indicated that MPA-VMD-WTD is an effective method for suppressing TEM data noise.