LI Wen,LI Dejian,MA Yongyue,TIAN Wang,WEN Xin,LI Jie.Research on denoising of joint detection signal of water quality with multi-parameter based on IEEMD[J].Optoelectronics Letters,2024,(2):107-115
Research on denoising of joint detection signal of water quality with multi-parameter based on IEEMD
Author NameAffiliation
LI Wen Institute of Mechanical and Electrical Engineering, North China University of Technology, Beijing 100144, China 
LI Dejian Institute of Mechanical and Electrical Engineering, North China University of Technology, Beijing 100144, China 
MA Yongyue Institute of Mechanical and Electrical Engineering, North China University of Technology, Beijing 100144, China 
TIAN Wang Institute of Mechanical and Electrical Engineering, North China University of Technology, Beijing 100144, China 
WEN Xin Institute of Mechanical and Electrical Engineering, North China University of Technology, Beijing 100144, China 
LI Jie Institute of Mechanical and Electrical Engineering, North China University of Technology, Beijing 100144, China 
Abstract:
      An improved ensemble empirical mode decomposition (IEEMD) is suggested to process water quality spectral signals in order to address the issue that noise interference makes it difficult to extract and evaluate water quality spectral signals. This algorithm effectively solves the problems of modal mixing, poor reconstruction accuracy in the empirical mode decomposition (EMD), and a large amount of calculation in the ensemble empirical mode decomposition (EEMD). Based on EEMD, IEEMD firstly preprocesses the original water quality spectral signals, then performs Savitzky-Golay (S-G) smoothing on the decomposed effective intrinsic mode function (IMF) components, and finally reconstructs them to obtain the denoised signals. Water sample data at different concentrations can be accurately analyzed based on the noise-reduced spectral signals. In this paper, three water quality parameters are used as research objects:benzene (C6H6), benzo(b)fluoranthene (C20H12), and chemical oxygen demand (COD). The original water quality multi-parameter (C6H6, C20H12, COD) spectral signals were subjected to denoising based on the IEEMD and the water quality multi-parameter joint detection technology. The signal-to-noise ratio (SNR) and the correlation coefficient (R2) of the fitted curves obtained from the processing of the IEEMD were compared and analyzed with those obtained from the processing of the EMD and the EEMD. The experimental results show that the SNR of the spectral signals and the R2 of the fitting curve in three water quality parameters have been significantly improved. Therefore, the IEEMD effectively improves the phenomenon of modal mixing, reduces the amount of calculation, improves the reconstruction accuracy, and provides an important guarantee for the effective extraction of multi-parameter spectral signals of water quality.
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