Page 259 - 《应用声学》2025年第2期

第 44 卷 第 2 期 Vol. 44, No. 2
2025 年 3 月 Journal of Applied Acoustics March, 2025

⋄ 研究论文 ⋄

用于电磁超声检测信号的联合降噪方法 ∗

杨 斌 易朋兴 † 郝峥旭

(华中科技大学机械科学与工程学院 武汉 430074)

摘要：为自适应地滤除电磁超声检测信号中的低频偏置与高频噪声，降低噪声对后续信号特征分析的影响，提
出了一种将变分模态分解与改进阈值的小波变换相结合的二级框架降噪算法。该方法首先使用变分模态分解
对信号进行分解并使用评价系数选择合适的模态函数分量对信号进行重构，之后使用改进阈值的小波变换法
进行二次滤波。通过对不同噪声水平的仿真信号进行降噪处理，验证了该方法的优越性，在实际缺陷检测信号
的降噪处理中也表现出了优异的性能。因此，该方法能够用于电磁超声检测信号的降噪。
关键词：电磁超声信号；变分模态分解；小波降噪；阈值函数
中图法分类号: TN911.7 文献标识码: A 文章编号: 1000-310X(2025)02-0519-10
DOI: 10.11684/j.issn.1000-310X.2025.02.028

A combined noise reduction method for electromagnetic ultrasonic
detection signals

YANG Bin, YI Pengxing and HAO Zhengxu

(School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract: To filter out the low-frequency bias and high-frequency noise in the electromagnetic ultrasonic de-
tection signal adaptively, and reduce the influence of noise on the subsequent signal characteristic analysis, a
two-level frame noise reduction algorithm combining variational mode decomposition and improved threshold
wavelet transform was proposed. In this method, the signal is decomposed by variational mode decomposition,
and the signal is reconstructed by selecting the appropriate mode function component with evaluation coeffi-
cient. Then the wavelet transform method with improved threshold is used for the signal secondary filtering.
The superiority of the method is verified by the simulation signal with different noise levels, and the excellent
performance is also shown in the real defect detection signal. Therefore, the method can be used to reduce the
noise of electromagnetic ultrasonic detection signals.
Keywords: Electromagnetic ultrasonic signal; Variational mode decomposition; Wavelet reduction noise;
Threshold function

2023-10-20 收稿; 2023-12-02 定稿
国家自然科学基金项目 (2018YFB2003303)
∗
作者简介: 杨斌 (1999– ), 男, 河南周口人, 硕士研究生, 研究方向: 缺陷检测, 信号与信息处理。
通信作者 E-mail: m202170484@hust.edu.cn
†