A method for reducing transient electromagnetic Noise: Combination of variational mode decomposition and wavelet denoising algorithm. (July 2022)

• Record Type: Journal Article
• Authors: Qi, Tingye; Wei, Xiaoya; Feng, Guorui; Zhang, Fan; Zhao, Dekang; Guo, Jun
• Is Part Of: Measurement. Volume 198(2022)
• Publication Date: 2022-07
• Subjects: Transient electromagnetic method -- Transient electromagnetic noise -- Variational mode decomposition -- Wavelet threshold denoising -- Grey wolf optimization; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2022.111420
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: A New Method for Transient Electromagnetic Noise Reduction:VMD-WTD. Using GWO to optimize the parameters of VMD to realize signal adaptive decomposition. This VMD-WTD method has good applicability in the mined-out area location determination. Abstract: The transient electromagnetic method (TEM) is used to detect mineral resources and mined-out areas, to eliminate the secondary field signal noise interference, this paper proposes an algorithm for denoising the TEM signal based on Variational Mode Decomposition (VMD) and Wavelet Threshold Denoising (WTD) methods. The Grey Wolf Optimization (GWO) algorithm solves the parameter combination ( K, α ) in the VMD, and the K intrinsic mode functions (IMFs) are then obtained using the decomposed TEM signal. Subsequently, all IMFs are analyzed according to the correlation coefficient and divided into signal modes, mixed modes, and invalid modes. Finally, the mixed modes are denoised by WTD, the signal and denoised modes are combined. To validate the effectiveness of the VMD-WTD algorithm, the method was compared in simulations with the Ensemble Empirical Mode Decomposition (EEMD) algorithm and various other methods previously developed to improve the TEM, its performance in a field experiment was also confirmed.