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ORIGINAL RESEARCH article

Front. Signal Process.
Sec. Signal Processing Theory
Volume 5 - 2025 | doi: 10.3389/frsip.2025.1518558

ICEEMDAN-VMD Denoising Method for Enhanced Magnetic Memory Detection Signal of Micro-Defects

Provisionally accepted
Shouhong Ji Shouhong Ji Jie Yan Jie Yan Yang Liu Yang Liu *Guojun He Guojun He
  • National Pipeline Network Group Zhejiang Natural Gas Pipeline Network Co. Ltd, Hangzhou, China

The final, formatted version of the article will be published soon.

    Ferromagnetic materials are extensively utilized in industrial settings, where the early detection and repair of defects is paramount for ensuring industrial safety. During the enhanced magnetic memory detection of microdefects, many interference signals appear in the detection signal, which makes it difficult to accurately extract the characteristics of the micro-defect signals and significantly affects the detection effectiveness. When the improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN) is employed independently for signal denoising, the noise and feature signals of the transition components will be retained or removed. When variational mode decomposition (VMD) is employed independently for signal denoising, the denoising effect is restricted because of the difficulty in determining the penalty factor  and the number of decomposition layers m.To solve these problems, a denoising method for enhanced magnetic memory detection signals based on ICEEMDAN and VMD, called ICEEMDAN-VMD, is proposed in the paper. First, a comprehensive index (CI) combining information entropy (IE) and correlation coefficient R was proposed, then the signal components obtained by performing decomposition with the ICEEMDAN method are divided into noise-dominant components, transition components, and useful signal components based on the CI. Subsequently, VMD is employed to perform secondary decomposition on the transition components obtained from the ICEEMDAN method and calculate the correlation coefficients. Ultimately, the optimal VMD components and useful signal components obtained by the ICEEMDAN method are selected for signal reconstruction to obtain a denoised signal. To validate the effectiveness of the proposed method, the denoising effects of the ICEEMDAN-VMD, ICEEMDAN, and VMD methods were compared based on the signal-to-noise ratio (SNR) and fuzzy entropy (FE). The comparison indicated that the ICEEMDAN-VMD denoising method significantly enhanced the denoising effect, and the SNRs of the components of the magnetic field signal could be increased by up to 69.426%. The SNR of each gradient component of the magnetic field signal could be improved by up to 10 times, and the FEs of the signal components and their corresponding gradient components could be reduced by 24.198-81.011%, respectively.

    Keywords: Enhanced magnetic memory detection, Micro-defects, Signal denoising, ICEEMDAN, VMD

    Received: 28 Oct 2024; Accepted: 07 Jan 2025.

    Copyright: © 2025 Ji, Yan, Liu and He. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Yang Liu, National Pipeline Network Group Zhejiang Natural Gas Pipeline Network Co. Ltd, Hangzhou, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.