WITHDRAWAL

Abstract

AbstractIn order to reduce the noise of TEM signal, a denoising method, in which based on the Variational Mode Decomposition of parameters optimized in sections and Huber Loss Function Curve fitting (SOP‐GWOVMD‐CFH), is proposed in this paper. According to the characteristics of TEM signal changing rate and signal‐to‐noise ratio varying with time, a segmented signal processing method is proposed and the segmented criterion is given. On the basic of different segmentation signals, the Grey Wolf Optimization algorithm is used to optimize the parameters of VMD, and the IMF1 after the optimization decomposition is took as the filtered signal. To further improve the SNR of late‐time attenuation signal, Huber loss function was used to perform exponential curve fitting of Intrinsic Mode Function (IMF1) late data to improve the filtering robustness. Then the data are spliced to obtain the filtered transient electromagnetic curve by the endpoint continuation method. The Simulation and experimental results show that the proposed method can effectively remove the noise in the signal and restore TEM signal with the absolute error less than 0.1μv, which proves the effectiveness of the proposed method, and the denoising effect of the proposed method has better performance than that of other common methods.This article is protected by copyright. All rights reserved