在线拉曼分析系统关键技术研究与工业应用
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摘要
在线分析仪器越来越广泛地进入到工业过程的各个生产装置。它所提供的及时、准确的分析数据为稳定生产、优化操作、节能降耗起到了不可替代的作用。在线拉曼光谱分析具有可测量多种形态的样品、灵活的采样方式、无需样本预处理等优势,是过程分析技术(Process Analytical Technology, PAT)的重要组成。本文就在线拉曼技术中的多项关键技术进行了研究,开发了PX装置在线拉曼分析系统并投入工业应用,具体包括：
1、在线拉曼分析系统中采用的背照式CCD阵列光谱仪具有干涉信号问题,本文提出了基于非特定荧光物质的干涉信号校正方法,并将其应用于某炼油厂催化重整装置的在线拉曼分析中。根据工业现场数据,与标准校正方法进行了对比,结果表明,随着仪器连续运行,光谱仪的部分特性发生改变,标准校正方法无法获得变化信息,未能实现对干涉信号的校正,本文提出的基于非特定荧光物质的干涉信号校正方法对干涉信号的去除更准确,并且能准确跟踪CCD固定模式的变化,对在线拉曼分析系统的长期稳定运行起到了重要作用。
2、为了提高拉曼光谱基线校正的准确性,在现有方法的基础上提出了迭代加权最小二乘的基线校正算法。该算法将基线以多项式形式表示,将一阶微分计入加权系数,通过迭代求取加权最小二乘的方式得到基线方程,实现基线校正。结合仿真数据和实验数据的处理,结果表明：提出的算法在全谱范围内具有最低的光谱畸变；此外,相比其它多项式基线校正方法,该方法对多项式阶数选择的依赖程度最低。
3、针对在线分析应用中的多类型定量分析问题,提出了一种结合支持向量机分类与回归的混合模型。由于光谱定量分析模型的准确度依赖于建模样本的选取,该模型对待测样本进行预分类,再选取局部样本建模分析属性值。应用该模型,对多类别汽油的辛烷值进行了拉曼光谱分析,实验对比结果验证了所提出模型的有效性。
4、针对复杂体系中某特定组分的分析问题,在间接强建模方法的基础上,提出了扩展谱峰解析算法用于拉曼光谱的谱峰解析。该方法采用了Voigt函数快速算法,提高了最优化结果的稳定性；对于谱峰不存在非线性变化的组分光谱,直接以数值向量形式表示,降低了优化复杂度。同时通过迭代优化的方式将基线估计与谱峰解析分离,避免了高阶多项式参数优化可能带来的结果不一致。该方法已成功地应用于汽油中苯、甲苯含量的分析。实验结果表明,在少量建模样本下,扩展谱峰解析算法能有效提取特定组分的光谱特征,与光谱分析中常用的多元校正方法相比,大幅度提高了分析精度。
5、以中石化镇海炼化PX装置模拟移动床色谱C8芳烃分离过程的在线拉曼分析仪为例,系统阐述在线拉曼光谱分析仪的工作原理、系统组成、模型分析方法与现场应用,并且给出了多个测量指标的现场实际运行趋势。在定量模型分析中,研究了C8芳烃混合物中各组分相对拉曼截面随浓度的变化规律,提出了基于扩展谱峰分解和拉曼截面校正的定量分析方法。该方法所需建模样本量少,与现有的PLS模型和基于恒定拉曼截面假设的多元线性回归方法相比具有更高的精度。该在线分析系统已在工业现场连续运行近一年,经现场连续运行表明,该在线拉曼仪具有分析速度快、分析精度高、维护工作量少等优势。其重复分析误差不超过±0.1%,各指标与标准色谱分析结果的误差不超过±0.5%,获得了用户的认可,并已经在厂方逐步取代常规气相色谱分析,为实现先进控制与实时优化提供关键测量信息。
Online analytical instruments are widely used in the industrial process. It provides timely and accurate analysis for optimizing operation, playing an irreplaceable role in saving energy. The capacity of online Raman spectroscopy to measure samples of a variety of forms with flexible sampling and without sample pretreatment makes it an important component of the Process Analytical Technology (PAT). In this thesis, several key technologies of online Raman technology are present; the development of online Raman system for the PX plants is described, which have been put into industrial applications. This thesis specifically including:
1、Online Raman system using a back-illuminated CCD array spectrometer with interference signal, this thesis proposes a signal correction method based on the interference of non-specific fluorescent substance. The method was applied to monitoring an oil refinery catalytic reforming unit. In continuous operation, part of the characteristics of the spectrometer changed. The standard relative intensity correction method can not get the information and failed to achieve the correction of the interference signal, leading to the problem of spectrum distortion. The proposed interference signal correction method based on non-specific fluorescent substance can accurately track the changes, achieving an effective solution for on-line Raman system using back-illuminated CCD.
2、A major problem in Raman spectroscopy is that the spectrum is often suffered from intrinsic fluorescence which is orders of magnitude greater than the Raman signal. Background subtraction is essential for further analysis, particularly for quantitative analysis using multivariate calibration. In this thesis, we propose a background removal algorithm which approximates the background by a polynomial and estimates the polynomial coefficients by iterative weighted least squares. The performance of the algorithm accompanied with two comparative methods are evaluated both on simulated and real Raman spectra. The results show that the proposed algorithm provides the best result using R2between the actual and extracted Raman peaks. It also improves the performance of background removal in quantitative Raman spectroscopy. Further more, the algorithm is least dependent on the choice of polynomial order.
3、In the multivariate calibration, the model performance not only depends on the structure and parameters, but also influenced by the calibration sample distribution. In practical application, the calibration samples often distribute unevenly in space. Modeling based on the whole calibration set degrades the performance. To address the limitation, a new hybrid model based on support vector classification and regression is proposed in this thesis. The classification decision tree with the form of the binary tree is firstly built by least-squares support vector classifier; then the least-squares support vector regression is used to construct the regression model for each class. This model is applied to Raman spectral analysis of gasoline octane number. The result shows that the proposed model has greatly improved the accuracy of quantitative analysis.
4、Based on Indirect hard modeling method, an extended peak resolution algorithm is proposed. A fast algorithm of the Voigt function is applied in the method, which improves the stability of the optimization results. By using numerical vector form for component spectrum without non-linear changes, it reduced the optimization complexity. Moreover, by alternating iterative optimization, the baseline estimation and peak resolution is separated, which improves the stability of parametric optimization with high order polynomial. The extended peak resolution algorithm is applied to Raman spectroscopy for quantitative analysis of benzene, toluene content in gasoline. The experimental results show that the proposed algorithm can effectively extract the spectral characteristics. Compared with the multivariate calibration methods, the proposed algorithm is of higher accuracy in quantitative analysis.
5、Development of on-line Raman system for the PX plants and putting into industrial applications. For the online analysis of the PX plants in petrochemical factory, the thesis described details of the on-line Raman analyzer including the principle, system compostion, model-based analysis and field application. The quantative analysis of the mixture of C8aromatics components is based on the extended peak resolution algorithm. The on-line Raman analyzer has been successfully applied to the composition analysis of the C8aromatics at the feed of adsorption tower in PX plants. According to the result of field operation, the repeatability error does not exceed±0.1%and the accuracy is±0.5%, which fully meets the requirements of the adsorption and separation processes. Moreover, the factory is gradually replacing the conventional gas chromatographic analysis. The Raman analyzer provided key information for the real-time process optimization.
1、在线拉曼分析系统中采用的背照式CCD阵列光谱仪具有干涉信号问题,本文提出了基于非特定荧光物质的干涉信号校正方法,并将其应用于某炼油厂催化重整装置的在线拉曼分析中。根据工业现场数据,与标准校正方法进行了对比,结果表明,随着仪器连续运行,光谱仪的部分特性发生改变,标准校正方法无法获得变化信息,未能实现对干涉信号的校正,本文提出的基于非特定荧光物质的干涉信号校正方法对干涉信号的去除更准确,并且能准确跟踪CCD固定模式的变化,对在线拉曼分析系统的长期稳定运行起到了重要作用。
2、为了提高拉曼光谱基线校正的准确性,在现有方法的基础上提出了迭代加权最小二乘的基线校正算法。该算法将基线以多项式形式表示,将一阶微分计入加权系数,通过迭代求取加权最小二乘的方式得到基线方程,实现基线校正。结合仿真数据和实验数据的处理,结果表明：提出的算法在全谱范围内具有最低的光谱畸变；此外,相比其它多项式基线校正方法,该方法对多项式阶数选择的依赖程度最低。
3、针对在线分析应用中的多类型定量分析问题,提出了一种结合支持向量机分类与回归的混合模型。由于光谱定量分析模型的准确度依赖于建模样本的选取,该模型对待测样本进行预分类,再选取局部样本建模分析属性值。应用该模型,对多类别汽油的辛烷值进行了拉曼光谱分析,实验对比结果验证了所提出模型的有效性。
4、针对复杂体系中某特定组分的分析问题,在间接强建模方法的基础上,提出了扩展谱峰解析算法用于拉曼光谱的谱峰解析。该方法采用了Voigt函数快速算法,提高了最优化结果的稳定性；对于谱峰不存在非线性变化的组分光谱,直接以数值向量形式表示,降低了优化复杂度。同时通过迭代优化的方式将基线估计与谱峰解析分离,避免了高阶多项式参数优化可能带来的结果不一致。该方法已成功地应用于汽油中苯、甲苯含量的分析。实验结果表明,在少量建模样本下,扩展谱峰解析算法能有效提取特定组分的光谱特征,与光谱分析中常用的多元校正方法相比,大幅度提高了分析精度。
5、以中石化镇海炼化PX装置模拟移动床色谱C8芳烃分离过程的在线拉曼分析仪为例,系统阐述在线拉曼光谱分析仪的工作原理、系统组成、模型分析方法与现场应用,并且给出了多个测量指标的现场实际运行趋势。在定量模型分析中,研究了C8芳烃混合物中各组分相对拉曼截面随浓度的变化规律,提出了基于扩展谱峰分解和拉曼截面校正的定量分析方法。该方法所需建模样本量少,与现有的PLS模型和基于恒定拉曼截面假设的多元线性回归方法相比具有更高的精度。该在线分析系统已在工业现场连续运行近一年,经现场连续运行表明,该在线拉曼仪具有分析速度快、分析精度高、维护工作量少等优势。其重复分析误差不超过±0.1%,各指标与标准色谱分析结果的误差不超过±0.5%,获得了用户的认可,并已经在厂方逐步取代常规气相色谱分析,为实现先进控制与实时优化提供关键测量信息。
Online analytical instruments are widely used in the industrial process. It provides timely and accurate analysis for optimizing operation, playing an irreplaceable role in saving energy. The capacity of online Raman spectroscopy to measure samples of a variety of forms with flexible sampling and without sample pretreatment makes it an important component of the Process Analytical Technology (PAT). In this thesis, several key technologies of online Raman technology are present; the development of online Raman system for the PX plants is described, which have been put into industrial applications. This thesis specifically including:
1、Online Raman system using a back-illuminated CCD array spectrometer with interference signal, this thesis proposes a signal correction method based on the interference of non-specific fluorescent substance. The method was applied to monitoring an oil refinery catalytic reforming unit. In continuous operation, part of the characteristics of the spectrometer changed. The standard relative intensity correction method can not get the information and failed to achieve the correction of the interference signal, leading to the problem of spectrum distortion. The proposed interference signal correction method based on non-specific fluorescent substance can accurately track the changes, achieving an effective solution for on-line Raman system using back-illuminated CCD.
2、A major problem in Raman spectroscopy is that the spectrum is often suffered from intrinsic fluorescence which is orders of magnitude greater than the Raman signal. Background subtraction is essential for further analysis, particularly for quantitative analysis using multivariate calibration. In this thesis, we propose a background removal algorithm which approximates the background by a polynomial and estimates the polynomial coefficients by iterative weighted least squares. The performance of the algorithm accompanied with two comparative methods are evaluated both on simulated and real Raman spectra. The results show that the proposed algorithm provides the best result using R2between the actual and extracted Raman peaks. It also improves the performance of background removal in quantitative Raman spectroscopy. Further more, the algorithm is least dependent on the choice of polynomial order.
3、In the multivariate calibration, the model performance not only depends on the structure and parameters, but also influenced by the calibration sample distribution. In practical application, the calibration samples often distribute unevenly in space. Modeling based on the whole calibration set degrades the performance. To address the limitation, a new hybrid model based on support vector classification and regression is proposed in this thesis. The classification decision tree with the form of the binary tree is firstly built by least-squares support vector classifier; then the least-squares support vector regression is used to construct the regression model for each class. This model is applied to Raman spectral analysis of gasoline octane number. The result shows that the proposed model has greatly improved the accuracy of quantitative analysis.
4、Based on Indirect hard modeling method, an extended peak resolution algorithm is proposed. A fast algorithm of the Voigt function is applied in the method, which improves the stability of the optimization results. By using numerical vector form for component spectrum without non-linear changes, it reduced the optimization complexity. Moreover, by alternating iterative optimization, the baseline estimation and peak resolution is separated, which improves the stability of parametric optimization with high order polynomial. The extended peak resolution algorithm is applied to Raman spectroscopy for quantitative analysis of benzene, toluene content in gasoline. The experimental results show that the proposed algorithm can effectively extract the spectral characteristics. Compared with the multivariate calibration methods, the proposed algorithm is of higher accuracy in quantitative analysis.
5、Development of on-line Raman system for the PX plants and putting into industrial applications. For the online analysis of the PX plants in petrochemical factory, the thesis described details of the on-line Raman analyzer including the principle, system compostion, model-based analysis and field application. The quantative analysis of the mixture of C8aromatics components is based on the extended peak resolution algorithm. The on-line Raman analyzer has been successfully applied to the composition analysis of the C8aromatics at the feed of adsorption tower in PX plants. According to the result of field operation, the repeatability error does not exceed±0.1%and the accuracy is±0.5%, which fully meets the requirements of the adsorption and separation processes. Moreover, the factory is gradually replacing the conventional gas chromatographic analysis. The Raman analyzer provided key information for the real-time process optimization.
引文
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