摘要
针对漏磁技术用于钢轨顶面损伤检测时的漏磁信号去噪问题,提出一种基于变分模态分解的去噪方法,分析钢轨损伤漏磁信号的成分。根据损伤信号和干扰信号的峭度值分布设定阈值,对原始漏磁信号进行变分模态分解。通过对比最高阶和次高阶模态分量之间的相关性确定分解层数;根据峭度阈值提取各阶模态分量的有效信号并进行重构。实验结果表明:该方法能够有效提高信噪比。
In addressing the noise reduction issue in magnetic leakage signals applied to detecting surface damage on rail tracks,a denoising method based on variational mode decomposition is proposed.The components of magnetic leakage signals caused by rail damage are analyzed.Thresholds based on the kurtosis values of damage signals and interference signals are set.The original magnetic leakage signals are decomposed using variational mode decomposition.The number of decomposition levels is determined by comparing the correlation between the highest and second-highest modal components.On the basis of the kurtosis thresholds,the effective signals of each modal component are extracted and reconstructed.Experimental results demonstrate that the proposed method effectively improves the signal-to-noise ratio.
作者
冯晨
王平
FENG Chen;WANG Ping(Key Laboratory of Non-destructive Testing&Monitoring Technology of High-speed Transportation Facilities,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China)
出处
《机械制造与自动化》
2025年第4期150-154,共5页
Machine Building & Automation
基金
国家自然科学基金项目(62073162)。
关键词
变分模态分解
漏磁检测
信号去噪
钢轨顶面损伤
variational mode decomposition
magnetic leakage testing
signal denoising
rail top surface damage
