经验模态分解去噪技术及其在兰姆波检测中的应用

EMD Denoising Method and Its Application in Lamb Wave Detection

经验模态分解(EMD)是一种新出现的处理非线性、非稳态数据的信号分析方法,通过三次样条包络分离数据的高阶成分和趋势。利用EMD的这种特性对超声兰姆波检测中的实测信号作去噪处理,并与小波去噪结果进行了对比,表明EMD去噪具有更强的自适应能力,且需知的原信号先验信息更少。

Empirical Mode Decomposition （EMD） is a new method for analyzing nonlinear and non-stationary data. This method can separate higher order signals from the original data by using cubic spline, and is employed here to eliminate noise from measured Lamb wave signals. By comparison with the wavelet analysis method, it is shown that the EMD has better adaptive ability in decomposing noise-polluted signals and less empirical information is required in the denoising process.