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An Effective Method on Reducing Measurement Noise Based on Hilbert-Huang Transform

机译:基于希尔伯特 - 黄变换降低测量噪声的有效方法

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For non-stationary signal in ultrasonic inspection, an effective denoising method based on Hilbert-Huang transform (HHT) is presented and a few key questions using the HHT method are discussed. The overall scheme of HHT includes two parts which are empirical mode decomposition (EMD) algorithm and a sum of intrinsic mode functions (IMF). Through the EMD process, individual IMF can be found. The IMF coefficients are preceded in useful signal dominative layers using a soft threshold method and finally those IMF coefficients are reconstructed. The results show that the usage of HHT method is reasonable at removing the measurement noise than the wavelet transform.
机译:对于超声检查中的非静止信号,提出了一种基于希尔伯特 - 黄变换(HHT)的有效去噪方法,并讨论了使用HHT方法的一些关键问题。 HHT的整体方案包括两部分,该部分是经验模式分解(EMD)算法和内在模式功能(IMF)的总和。通过EMD流程,可以找到个别IMF。使用软阈值方法,IMF系数在有用的信号主导层之前,最后重建那些IMF系数。结果表明,HHT方法的使用在除去比小波变换的测量噪声时是合理的。

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