Investigating the feasibility of using near-infrared spectroscopy for inline monitoring of the salt content in industrial process water

Kasper Borg Damkjær, K. Sørensen, S. Engelsen
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Abstract

Author Summary: Fast real-time monitoring of water quality can help facilitate reuse of industrial process water. Near-infrared spectroscopy is a well-established process monitoring tool within the pharma and food industry. Utilising near-infrared spectroscopy as one of the pieces in the puzzle for optimising water reuse is therefore attractive. Partial least squares regression models were computed on 286 near-infrared spectra of mono salt solutions of KCl, K2SO4, KNO3, CaCl2, CaSO4 and Ca(NO3)2. Concentrations ranging from 0 ppm to 1000 ppm (w/w) in steps of 100 ppm were measured at 10, 25 and 40 °C. Analysis showed that the concentration of salt could be predicted independently from temperature resulting in a root mean squared error of cross validation, RMSECV, of 186 ppm and an R2 of 0.67. A global temperature model and an individual model on K2SO4 at 25 °C cross validated by leave-one-concentration-out resulted in RMSECV values of 181 ppm and 115 ppm and R2 values of 0.68 and 0.87. The limit of detection and limit of quantification for K2SO4 was estimated to be 140 ppm and 400 ppm.
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探讨了用近红外光谱法在线监测工业生产用水含盐量的可行性
作者摘要:快速实时监测水质有助于促进工业工艺用水的回用。近红外光谱在制药和食品行业是一种完善的过程监控工具。因此,利用近红外光谱作为优化水再利用的难题之一是有吸引力的。对KCl、K2SO4、KNO3、CaCl2、CaSO4、Ca(NO3)2等单盐溶液的286个近红外光谱进行了偏最小二乘回归模型计算。浓度范围从0 ppm到1000 ppm (w/w),以100 ppm的步骤在10、25和40°C下测量。分析表明,盐的浓度可以独立于温度预测,交叉验证的均方根误差RMSECV为186 ppm, R2为0.67。对25°C下K2SO4的全球温度模型和单个模型进行了留一浓度交叉验证,RMSECV值为181 ppm和115 ppm, R2值为0.68和0.87。K2SO4的检出限和定量限分别为140 ppm和400 ppm。
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