光谱学与光谱分析, 2017, 37 (9): 2724, 网络出版: 2017-10-16   

水体COD的光谱学在线测量方法-紫外和近红外光谱比较分析

Online Measurement of Water COD-A Comparison between Ultraviolet and Near Infrared Spectroscopies
作者单位
1 北京农业智能装备技术研究中心, 北京市农林科学院, 北京 100097
2 重庆邮电大学, 重庆 400065
摘要
水体COD的光谱学传感技术是现代环境监测的一个重要发展方向, 与传统的分析方法相比, 光谱分析技术更具有可连续监测、 可在线监测和检测快速的明显优势, 适合对环境水样COD的定点实时监测。 分别获取水样的紫外吸收光谱和近红外光谱, 通过不同的光谱预处理方法结合偏最小二乘法、 多元线性回归法建立水样的COD定量预测模型, 对水体COD的紫外和近红外光谱的定量预测及相关模型参数进行分析, 发现用S-G平滑处理后的紫外光谱和近红外光谱建立的PLS模型均得到最佳预测效果, 预测集R2分别为0.992 1和0.987 7, RMSEP分别为10.438 6和5.972 0。 紫外和近红外光谱法的MLR模型预测效果较差, 预测集R2分别为0.928 0和0.957 3。 通过实验结果综合对比分析, 紫外吸收光谱在280~310 nm谱区建模预测性能较好, 近红外光谱在7 250~6 870 cm-1谱区建模预测性能较好, 紫外光谱对应定量预测模型的决定系数较高, 而近红外光谱的稳定性和重复性更好。 研究表明光谱传感技术可用于环境实际水体COD的定量预测分析, 为开发便携式水体检测设备奠定了理论基础。
Abstract
The spectroscopy sensing technology of water COD is an important development direction of modern environmental monitoring. Compared with traditional analytical methods, spectroscopy has more obvious advantages, such as continuous monitoring, online monitoring and fast testing, which is suitable for fixed-point and real-time monitoring of environmental water samples for COD. In this study, the ultraviolet absorption spectrum and the near infrared spectrum of real water samples were collected respectively by ultraviolet absorption spectrometry and near infrared transmission method. The COD prediction model was established by utilizing different spectral pretreatment methods combined with partial least squares regression(PLS) and multiple linear regression(MLR), and then the quantitative prediction and model parameters of ultraviolet and near infrared spectra measurement for COD were analyzed, finding that the Savitzky-Golay (SG) smoothing partial least-squares model had good prediction. Through comparison, the determination coefficients of prediction were 0.992 1 and 0.987 7, respectively, and RMSEP were 10.438 6 and 5.972 0, respectively. Ultraviolet and Near-infrared spectroscopy combined with MLR analysis model had poor prediction, with the determination coefficients of prediction 0.928 0 and 0.957 3, respectively. Through a comprehensive analysis of the experimental results, ultraviolet absorption spectrum prediction model in 280~310 nm spectral region had a good performance. Near infrared spectral spectrum model had the best performance in 7 250~6 870 cm-1 spectral region. Ultraviolet spectrum corresponding to the decision of prediction model was higher, but the near spectrum model had better stability and repeatability. Studies show that the spectrum sensing technology can be used in the quantitative predicted analysis of COD in actual water. The conclusion from the paper laid a theoretical basis for the development of portable water testing equipments.

刘飞, 董大明, 赵贤德, 郑培超. 水体COD的光谱学在线测量方法-紫外和近红外光谱比较分析[J]. 光谱学与光谱分析, 2017, 37(9): 2724. LIU Fei, DONG Da-ming, ZHAO Xian-de, ZHENG Pei-chao. Online Measurement of Water COD-A Comparison between Ultraviolet and Near Infrared Spectroscopies[J]. Spectroscopy and Spectral Analysis, 2017, 37(9): 2724.

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