基于荧光光谱的水中矿物油浓度在线智能检测研究
[Study on the concentration of mineral oil in water by online intelligent detection based on fluorescence spectrum].
作者信息
Tang Yuan-he, Liu Qing-song, Ivieng Lei, Liu Han-chen, Liu Qian, Li Cun-xia
出版信息
Guang Pu Xue Yu Guang Pu Fen Xi. 2015 Feb;35(2):424-8.
In order to monitor the oil pollution of water real time and accurately for the environmental protection, an intelligent online detection system for the mineral oil in water is put forward in the present paper, based on the technology of ultraviolet fluorescence and internet of things (IOT). For this system, the resolution can be improved by using the higher precision asymmetric Czemy-Turner monochromator; the impact of light fluctuations on the results of exploration can be corrected by a bunch reference light; the optical system deviation caused by the instrument vibration can be reduced by optical fiber transmission; the coupling efficiency of fiber and output signal can be increased by a special fiber beam; the real-time measurement, data processing and remote control can be achieved by the control module and wireless communication module. This system has characteristics of high integration, high precision and good stability etc. The concentration of the unknown sample can be accurately calculated by the methods of parallel algorithms of chemometric metrology and the calculation errors caused by different components can be reduced by the theory of chemical correction factor analysis. The fluorescence spectra of three kinds of sample solution, diesel, engine and crude oil in preparative concentration of 10, 25, 50 and 100 mg x L(-1) were measured by this system respectively. The absorption wavelengths of the above-mentioned three oils were measured to be 256, 365 and 397 nm by a grating spectrometer; their absorbances were measured to be 0.028, 0.036 and 0.041 by fluorescence spectrophotometer, respectively. Their fluorescence emission wavelengths are 355, 419 and 457 nm respectively. Finally the concentration detection limits of the mineral oil in water of diesel, engine and crude oil were obtained, i.e., 0.03, 0.04 and 0.06 mg x L(-1) respectively. Their relative errors are 2.1%, 1.0% and 2.8% respectively.
为了实现对水体石油污染的实时、准确监测，服务于环境保护工作，本文基于紫外荧光技术和物联网（IOT），提出了一种水中矿物油智能在线检测系统。对于该系统，采用更高精度的非对称 Czemy-Turner 单色仪可提高分辨率；一束参考光可校正光波动对探测结果的影响；光纤传输能减少仪器振动引起的光学系统偏差；特殊的光纤束可提高光纤与输出信号的耦合效率；控制模块和无线通信模块可实现实时测量、数据处理及远程控制。该系统具有高集成度、高精度和良好稳定性等特点。采用化学计量学的并行算法可准确计算未知样品的浓度，化学校正因子分析理论可减少不同成分引起的计算误差。利用该系统分别测量了三种不同样品溶液（柴油、机油和原油）在浓度为 10、25、50 和 100 mg·L⁻¹ 时的荧光光谱。用光栅光谱仪测得上述三种油的吸收波长分别为 256、365 和 397 nm；用荧光分光光度计测得它们的吸光度分别为 0.028、0.036 和 0.041。它们的荧光发射波长分别为 355、419 和 457 nm。最终得出柴油、机油和原油在水中矿物油的浓度检测限分别为 0.03、0.04 和 0.06 mg·L⁻¹。它们的相对误差分别为 2.1%、1.0% 和 2.8%。
Zotero 插件