利用经验模态分解方法增强雷电电场信号

Huo Yuanlian, Qiao Yongfeng
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引用次数: 3

摘要

本文提出了一种基于经验模态分解(EMD)降噪算法的雷电电场信号去噪方法,该方法广泛应用于分析非线性和非平稳数据。通过对仿真和实测数据的分析,将该方法与传统FIR低通滤波器进行比较。结果表明,基于EMD的雷电电场信号去噪方法具有较好的降噪效果,且优于FIR滤波方法。
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Enhancement of lightning electric field signals using empirical mode decomposition method
In this paper, a new lightning electric field signals denoising approach based on noise reduction algorithms in empirical mode decomposition(EMD) which was widely used for analyzing nonlinear and nonstationary data was applied. The data from the simulation and measurements were analyzed to evaluate this method comparing with the traditional FIR low-pass filter. The results showed that the denoising methods based on EMD provides very good results for denoising lightning electric field signals and it was effective and superior to the FIR filter method.
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