Aiming at the problem of extracting effective components in the signal of power station with strong background noise,a de-noising method combining the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)and the cross-correlation analysis is proposed and verified in this paper.The main steps are as follows.Firstly,the signal of power station is effectively decomposed by the CEEMADN,and all the components of intrinsic mode functions(IMFs)are obtained.Afterwards,the above components are effectively distinguished based on the cross-correlation coefficients,and the IMFs dominated by the useful signals are obtained.The de-noised signal can be reconstructed by summing these IMFs.Finally,the evaluation indexes of de-noising are used to evaluate the de-noising effect.The results show that compared with the de-noising methods based on the empirical mode decomposition and the ensemble empirical mode decomposition,the de-noised signal based on the proposed method in this paper has a higher signal to the noise ratio,a smaller root mean square error,a larger correlation coefficient and a better smoothness,indicating that the denoising effect is better.
关键词
信号降噪/经验模态分解/集合经验模态分解/完全自适应噪声集合经验模态分解/互相关分析
Key words
Signal de-noising/Complete ensemble empirical mode decomposition with adaptive noise/Empirical mode decomposition/Ensemble empirical mode decomposition/Cross-correlation analysis
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