A de-noising method based on ensemble empirical mode decomposition(EEMD)and permutation entropy is proposed for power station signal in the present paper.The procedure of this method is as follows.Firstly,a typical measured signal of a power station is decomposed by EEMD and the corresponding intrinsic mode functions are obtained.Secondly,the permutation entropy is used to quantitatively evaluate the chaotic degree of the intrinsic mode functions,so as to distinguish the useful signals and the noises in the measured signal.For the latter,they are de-noised by the wavelet threshold de-noising method.Finally,the useful signals filtered by the permutation entropy and the noises de-noised by the wavelet threshold de-noising method are reconstructed to obtain the de-noised signal.In addition,the mainstream empirical mode decomposition and local mean decomposition are also used to process the signal,and the analysis results are compared.The comparison results show that the permutation entropy of the de-noised signal based on the proposed method in the present paper is smaller,indicating that the denoising effect is better than the above two methods.
关键词
信号降噪/经验模态分解/局部均值分解/集合经验模态分解/排列熵
Key words
Signal de-noising/Empirical mode decomposition/Local mean decomposition/Ensemble empirical mode decomposition/Permutation entropy
维普
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