Comparative Research on Noise Reduction of Transient Electromagnetic Signals Based on Empirical Mode Decomposition and Variational Mode Decomposition. Issue 10 (6th October 2021)

• Record Type: Journal Article
• Authors: Wei, Huiru; Qi, Tingye; Feng, Guorui; Jiang, Haina
• Is Part Of: Radio science. Volume 56:Issue 10(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-10-06
• Subjects: transient electromagnetic signal -- variational mode decomposition -- electromagnetic noise -- signal denoising; Radio meteorology -- Periodicals; Radio wave propagation -- Periodicals; 621.38405
• DOI: 10.1029/2020RS007135
• Languages: English
• ISSNs: 0048-6604

Abstract

Abstract: Transient electromagnetic (TEM) detection has been widely used in the fields of mineral resources exploration, hydrogeological survey and engineering survey, but electromagnetic interference can lead to late signal distortion, so it has become an urgent problem to suppress the electromagnetic noise of TEM signal and improve the interpretation accuracy of TEM signal. For the first time, this paper introduces the approach of variational mode decomposition (VMD) into the field of TEM signal‐noise reduction. The half homogeneous space model and the three‐layer earth model were constructed to compare the noise reduction effect of the empirical mode decomposition (EMD) approach and the VMD approach on the three main noises (random noise, power frequency noise, and sferics noise) in the TEM signal. The results are compared with the wavelet threshold denoising approach to verify the superiority of the VMD approach relative to the EMD approach. The results show that the VMD approach is better than the decomposition result of the EMD approach in the signal‐noise separation of TEM signals. In addition, the VMD approach is applied to the measured TEM data in a region in southern Shanxi Province, which effectively improves the quality of TEM signals. This indicates that the VMD approach is expected to be used for signal interference suppression in the field of TEM detection in the future. Key Points: Denoising of transient electromagnetic signals Variational mode decomposition Improving of signal quality