%A WANG Ren-jie, FENG Peng, YANG Xing, AN Le, HUANG Pan, LUO Yan, HE Peng, TANG Bin
%T A Denoising Algorithm for Ultraviolet-Visible Spectrum Based on
CEEMDAN and Dual-Tree Complex Wavelet Transform
%0 Journal Article
%D 2023
%J SPECTROSCOPY AND SPECTRAL ANALYSIS
%R 10.3964/j.issn.1000-0593(2023)03-0976-08
%P 976-983
%V 43
%N 03
%U {https://www.gpxygpfx.com/CN/abstract/article_13224.shtml}
%8 2023-03-01
%X The essence of measuring water quality COD by UV-vis absorption spectrometry is to model a large number of spectral data, and then introduce the measured spectral data to predict the process. However, there are two characteristic absorption peaks in the measured COD standard solution of potassium hydrogen phthalate at 200～300 nm, and the peak and peak values of the standard solution are also different at different concentrations. This feature is used to select the characteristic wavelength of this band and use it to characterize the spectral information, which reduces the data redundancy and improves the prediction accuracy. Because the measured water quality spectral signal is easily disturbed by the internal and external interference, resulting in a large number of non-stationary noise in the spectral data, and the characteristic absorption peak and its adjacent signal frequency is high, conventional denoising algorithms directly abandon high-frequency signals and can not accurately judge the limits of signal-to-noise components, resulting in the lack of effective signals. A joint denoising algorithm based on fully adaptive noise set empirical mode decomposition CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise) and dual-tree complex wavelet transform DT-CWT (The Dual-Tree Complex Wavelet Transform) is proposed. The algorithm uses CEEMDAN to decompose the signal into intrinsic mode function IMF (Intrinsic Mode Function). It makes linear correlation analysis through normalized autocorrelation function and cross-correlation number to determine the boundary between high-frequency noise components and low-frequency signal components. Then the DT-CWT threshold denoising algorithm is used to process the noisy high-frequency IMF component, and the IMF high-frequency component after DT-CWT processing is reconstructed from the IMF low-frequency component demarcated by CEEMDAN, and the final denoised signal is obtained. The experimental results show that the denoising algorithm based on CEEMDAN combined with dual-tree complex wavelet transform is suitable for data processing of UV-Vis spectrum water quality detection. For potassium hydrogen phthalate solution whose chemical oxygen demand (COD) standard solution is 100 mg·L^{-1}, the denoising effect of SNR=24.201 5 dB, RMSE=0.024 0, NCC=0.999 4 and PSNR=37.573 6 denoised by the combined algorithm is significantly better than that of CEEMDAN and double-tree complex wavelet threshold algorithm. Moreover, it effectively retains the characteristic absorption peak of the original COD standard solution, suppresses the translation sensitivity and improves the smoothness of the reconstructed signal. The quality of the reconstructed signal is improved. It provides a new data pre-processing method for detecting water quality COD by UV-Vis spectrum.