In order to solve the problem of nonlinear and nonstationary signal de-noising

a novel de-noising method is proposed by combining the principal component analysis(PCA) and empirical mode decomposition(EMD).The method removes noise of intrinsic mode functions(IMFs) using PCA

after the noisy signal is decomposed by EMD.Firstly

the signal details of the first IMF are extracted by using 3

criterion

and the noise energy of each level IMF is estimated.Secondly

the PCA is implemented on each IMF

and the part of principle components are selected to reconstruct the IMF according to noise energy of IMFs

then the noise of IMF is removed efficiently.Numerical simulation and real data test were carried

out to evaluate the performance of the proposed method.The experimental results showed that the proposed method outperformed the Bayesian wavelet threshold de-noising algorithm and mode cell EMD de-noising algorithm.So it is an effective signal de-noising method.