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    TAN Huifen, ZHANG Yu, CHEN Tao, PAN Yaoyi, PAN Qiaoming, CHEN Zhishan. Prediction of 3 Components in Water Phase from Reverse Osmosis Composite Membrane Production Line with Models Based on Near-Infrared Spectroscopy[J]. PHYSICAL TESTING AND CHEMICAL ANALYSIS PART B:CHEMICAL ANALYSIS, 2021, 57(11): 999-1004. DOI: 10.11973/lhjy-hx202111006
    Citation: TAN Huifen, ZHANG Yu, CHEN Tao, PAN Yaoyi, PAN Qiaoming, CHEN Zhishan. Prediction of 3 Components in Water Phase from Reverse Osmosis Composite Membrane Production Line with Models Based on Near-Infrared Spectroscopy[J]. PHYSICAL TESTING AND CHEMICAL ANALYSIS PART B:CHEMICAL ANALYSIS, 2021, 57(11): 999-1004. DOI: 10.11973/lhjy-hx202111006

    Prediction of 3 Components in Water Phase from Reverse Osmosis Composite Membrane Production Line with Models Based on Near-Infrared Spectroscopy

    • Models based on near-infrared spectroscopy were used for predicting 3 components, including m-phenylenediamine, triethylamine and sodium dodecyl benzene sulfonate in water phase from the reverse osmosis composite membrane production line. The samples were analyzed with near infrared spectrometer. The raw near-infrared spectroscopy was pretreated by Savitziky-Golay smoothing-second order differential method, and used to build models of m-phenylenediamine, triethylamine and sodium dodecyl benzene sulfonate by partial least squares method (PLS) at wavelength ranges of 1 630-1 699 nm, 1 699-1 733 nm and 1 662-1 690 nm, respectively. The PLS factor numbers were chosen as 3, 4, 3 for m-phenylenediamine, triethylamine and sodium dodecyl benzene sulfonate, respectively. Correlation coefficients of the models of 3 water phase components were 0.999 3, 0.986 3, 0.999 8, and corrected root mean square errors (RSMEC) were 0.119, 0.239 and 0.095, respectively. The proposed models were used for the analysis of the prediction set samples (mixed standard solution series), and predicted values and known values were linearly fitted, and correlation coefficients of 3 water phase components obtained were greater than 0.980 0, and root mean square errors (RMSEP) of the prediction were 0.144, 0.169 and 0.114, respectively.
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