An adaptive seismic signal denoising method based on variational mode decomposition. (June 2021)

• Record Type: Journal Article
• Authors: Yao, Xinyi; Zhou, Qiuzhan; Wang, Cong; Hu, Jikang; Liu, Pingping
• Is Part Of: Measurement. Volume 177(2021)
• Publication Date: 2021-06
• Subjects: Unattended ground sensor system -- Seismic signal -- Adaptive denoising method -- VMD -- Wavelet threshold denoising; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2021.109277
• Languages: English
• ISSNs: 0263-2241

Abstract

Abstract: In this paper, we study the denoising method for unattended ground sensor (UGS) systems that are composed of seismic sensors. Seismic sensors are used for collecting the seismic signals generated by targets. The collected signals are polluted by noises during propagation, which will influence the performance of UGS systems. Thus, it is necessary to suppress the noises in the collected signals. This paper proposes a denoising method based on variational mode decomposition (VMD) and wavelet threshold denoising. This method decomposes raw seismic signal to several modes. Correlation coefficient and the Euclidean distance are combined to determine the cut-off points of the modes needed to be processed. Finally, the denoised signal is reconstructed. We evaluate the method on the basis of computer-synthesized and real-world seismic signals. The results show that the proposed method can effectively reduce noise components and retain effective components in raw seismic signals, which indicates a good performance. Highlights: VMD is introduced to construct the denoising method for the seismic signals in UGS. Correlation coefficient and the Euclidean distance are used to distinguish the modes. The evaluation bases on computer-synthesized and real-world seismic signals. VMDWTD has adaptability to different seismic signals and different environment.