Spectral Denoising Based on Peak Extraction Combined with Variational Mode Decomposition for Complex Samples
To address the issue of peak loss when applying variational mode decomposition(VMD)to denoise spectra with sharp peaks,in this study,a method for spectral signal denoising of complex samples called peak extraction variational mode decomposition(PE-VMD)was introduced.Firstly,the spectral signal was subjected to a process of denoising utilising the VMD algorithm.Next,the first order derivatives of the spectral signals were calculated to determine the peak center.Subsequently,the second order derivatives of the spectral signal was calculated to extract the sharp peaks with high signal-to-noise ratio(SNR).Finally,the peak intercepted that lose information after VMD denoising were removed,and the remaining spectrum was sequentially connected with the extracted sharp peaks to obtain the final denoised spectrum.The effectiveness of the method was evaluated by one of simulated signals and X-ray diffraction(XRD)spectrum of MnCo-ISAs/CN catalysts.Furthermore,the method was compared with other denoising techniques,including Savitzky-Golay(SG)smoothing,empirical mode decomposition(EMD)and VMD.The efficacy of the denoising process was then assessed by analyzing the spectrograms and signal-to-noise ratio before and after denoising.The results demonstrated that PE-VMD denoising achieved the greatest SNR and effectively preserved the essential information of the spectral signals.Consequently,PE-VMD exhibited superior denoising capability for spectra with sharp peaks.
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