Abstract
An empirical mode decomposition (EMD) denoising method based on principal component analysis (PCA) is proposed for the denoising of nonlinear and non-stationary signals. Based on the decomposition characteristics of EMD, PCA is used to remove the noise in intrinsic mode function (IMF) decomposed by EMD nonlinear and non-stationary signals. Firstly, detailed information of the first IMF layer is extracted by using the “three σ rules”, and the energy of noise in each IMF layer is estimated. Then the IMF is transformed by PCA and the appropriate number of principal components are selected to be reconstructed according to noise energy in IMF layers so as to remove the noise.
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