A transient electromagnetic signal denoising method based on an improved variational mode decomposition algorithm. (November 2021)

• Record Type: Journal Article
• Authors: Feng, Guorui; Wei, Huiru; Qi, Tingye; Pei, Xiaoming; Wang, Hong
• Is Part Of: Measurement. Volume 184(2021)
• Publication Date: 2021-11
• Subjects: Transient electromagnetic signal -- Electromagnetic noise -- Variational mode decomposition -- Parameter optimization -- Whale optimization algorithm; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2021.109815
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: The noise in TEM signals is effectively removed by WOA-VMD algorithm. The WOA-VMD algorithm can adaptively determine the optimal parameters and adaptively decompose the TEM signal. The WOA-VMD algorithm has more obvious advantages in anti-noise interference and anti-modal aliasing. The TEM signal denoised by WOA-VMD can more accurately reflect the position of the goaf. Abstract: Transient electromagnetic method (TEM) is often disturbed by surrounding noise in field measurement, which leads to low resolution of data and affects accurate positioning of geological anomalies. In order to solve this problem, an improved variational mode decomposition (VMD) algorithm based on whale optimization algorithm (WOA) is proposed. Firstly, the WOA is used to quickly obtain the optimal parameter combination of the decomposition number K and the penalty factor α of the VMD algorithm. Then, the improved VMD is used to adaptively decompose the signal. Finally, the Bhattacharyya distance algorithm is used to identify the effective mode and noise mode to accurately reconstruct the signal. The simulation comparison test shows that the proposed method has better performance in the noise processing of TEM signals. In addition, in the field experiment, this method successfully filters out the noise modes in the signal, which greatly improves the accuracy of data interpretation and verifies the effectiveness of the algorithm.