Determination of Asphalt Cement Properties by Near Infrared Spectroscopy and Chemometrics

In the present study, near infrared (NIR) spectroscopy and chemometrics techniques have been combined to predict some properties used to characterize and to classify asphalt cement grade. Principal Components Regression (PCR) and Partial Least Squares Regression (PLSR) were employed to develop linear models to predict penetration value, absolute viscosity at 60°C, kinematic viscosity at 135°C and flash point of asphalt cements. The good correlation between NIR pretreated spectra and the properties investigated, measured by values of correlation coefficients and root mean squared errors of both calibration and prediction are here discussed. It was concluded that the combination of both techniques can be used to predict properties of asphalt cement to be delivered after on-line blending of hard and soft binders stocked in refineries.     

近红外光谱法测定柴油中的芳烃含量

研究了采用近红外光谱测定柴油中芳烃含量的方法。通过高效液相色谱分离、移动丝氢火焰检测器检测获得柴油中芳烃的基础数据。在５０００～１００００ｃｍ－１波长范围内,应用傅立叶变换近红外光谱仪,交互检验偏最小二乘方法对使用的光谱范围进行优化。所得校正模型对训练集样品预测的平均偏差为０２３％,对未知样品将近红外预测结果与ＨＰＬＣ的测定结果比较,平均偏差为０２７％。作为一种快速分析技术,近红外光谱测定柴油中的芳烃含量是简便可靠的方法。     

近红外光谱快速测定成品罐汽油的有关性质

在标准方法测定数据的基础上 ,建立了厂内成品罐汽油的组成和性质的近红外光谱校正模型 ,并用常规分析方法验正模型的准确性。实验表明 ,近红外光谱法测定的准确性达到标准方法对测定结果的要求。近红外光谱技术能在 5min内快速、准确、简便地一次测定成品罐汽油的辛烷值、芳烃、烯烃、苯     

The Determination of a Diesel Solidifying Point by Near Infrared Spectroscopy

A total of 86 representative samples of diesel oil were selected to determine the solidifying point. These samples covered a wide range and the concentration is more evenly distributed. The near infrared spectroscopy (NIR) method to determine the diesel solidifying point was successfully designed. Multiple linear regression method was chosen to establish the calibration model. The regression coefficients, partial regression sum of squares, partial correlation coefficients, the total estimated standard deviation, correlation coefficient, residual sum of squares, and other model parameters were calculated. The repeatability of the NIR method is better than the standard method. It can be seen that this NIR method to determine the diesel solidifying is feasible and repeatable.     

The Determination of Diesel Density and Refractive Index by Near Infrared Spectroscopy

In this work, the near infrared spectroscopy method has been successfully designed to determine the diesel density and refractive index by use of 93 representative diesel samples. The multiple linear regression method was chosen to establish the calibration model, and 17 samples were used to verify the calibration model. It was observed that the paired t test statistic (refractive index 1.03, density 0.10) is less than the significance level of 0.05 t distribution (2.12). The repeatability of the near infrared spectroscopy method is better than the standard method. Therefore the near infrared spectroscopy method to determine the diesel density and refractive index is feasible.     

红外光谱法测定洗涤剂醇的羟值

建立了傅立叶红外光谱法测定Ｃ１２～Ｃ１５的洗涤剂醇羟值的方法。考察了方法的最佳积分方式、精密度和准确性。并对现场样品进行了分析。结果表明，测定１．０～１．９ｇ／２５ｍＬ的标样时，其误差为１．０％～３．４％。对现场Ｃ１２～Ｃ１５洗涤剂醇样品进行５次平行分析，相对标准偏差为０．５３％，回收率为９７．２％。     

近红外光谱法在线分析重烷基苯

采用近红外光谱技术建立一种能够同时测量重烷基苯的馏程、烷基苯含量和相对分子质量等性质的分析方法。实验结果表明,5%馏程、95%馏程、烷基苯含量及相对分子质量的近红外校正模型的交互验证标准差分别为1.5℃,1.8℃,0.82%,1.7;外部验证标准差分别为2.4℃,3.3℃,1.10%,3.0;馏程、烷基苯含量及相对分子质量的分析精密度分别为±0 4℃、±0.4%和±1。近红外光谱法测定的结果明显优于常规分析方法,表明利用近红外光谱法分析重烷基苯的馏程、烷基苯含量和相对分子质量是可行的。该方法具有快速、多通道的优点,为实现重烷基苯生产过程的质量在线监测提供了手段。     

近红外光谱快速测定重整汽油详细族组成

采用近红外光谱和化学计量学方法建立了快速、准确测定重整汽油详细族组成 (C3～C+ 9链烷烃、C5～C+ 8环烷烃、C3～C7烯烃、C6 ～C+ 9芳烃 )的分析方法。试验表明 ,该方法分析速度快、重现性好、成本低 ,特别适用于中间控制分析。     

红外分光光度法测定车间空气中油雾的研究

通过现场采样和实验室模拟加标实验,确立了利用红外光谱法测定车间空气中油雾浓度的方法,并比较了玻璃纤维滤膜和聚四氟乙烯滤膜的采样性能。经研究发现,玻璃纤维滤膜的加标回收率为80.5%~95.7%,聚四氟乙烯滤膜的加标回收率为84.9%~96.7%;相对标准偏差结果均在5%以内。气体采样体积100 L,萃取体积10 m L,检出限为0.05 mg/m3。实验结果表明,红外分光光度法具有良好的准确性和检出限,适用于车间环境油雾含量的检测。     

Determination of Octane Number of Gasoline Using Near Infrared Spectroscopy and Genetic Multivariate Calibration Methods

Abstract

The feasibility of rating the octane number of gasoline using near infrared (NIR) spectroscopy and three different genetic algorithm-based multivariate calibration methods was demonstrated. The three genetic multivariate calibration methods are genetic regression (GR), genetic classical least squares (GCLS), and genetic inverse least squares (GILS). The sample data set was obtained from the ftp address (ftp://ftp.clarkson.edu/pub/hopkepk/Chemdata/) with the permission of Professor. J. H. Kalivas. This data set contains the NIR spectra of 60 gasoline samples collected using diffuse reflectance as log (1/R) with known octane numbers and covers the range from 900 to 1700 nm in 2 nm intervals. Of these 60 spectra, 20 were used as the calibration set, 20 were used as the prediction set, and 20 were reserved for the validation purposes. Several calibration models were built with the three genetic algorithm-based methods, and the results were compared with the partial least squares (PLS) prediction errors reported in the literature. Overall, the standard error of calibration (SEC), standard error of prediction (SEP), and standard error of validation (SEV) values were in the range of 0.15–0.32 (in the units of motor octane number) for the GR and GILS, which are comparable with the literature. However, GCLS produced relatively large results (0.36 for SEC, 0.39 for SEP and 0.52 for SEV) when compared with the other two methods.     

红外光谱鉴定直升机润滑脂

通过红外光谱分析,确定了某直升机在用润滑脂的牌号。     

甲基叔丁基醚含量对近红外光谱法测定汽油族组成的影响

建立了快速分析汽油族组成的近红外光谱法,研究了汽油近红外光谱随甲基叔丁基醚(MTBE)含量变化的规律,建立了不含MTBE汽油和含MTBE汽油的混合校正模型,评价了MTBE对近红外光谱分析校正模型预测的影响。研究结果表明,MTBE含量对汽油的近红外光谱的影响较大,随着MTBE含量的增加,汽油试样的近红外光谱向短波方向平移。混合校正模型的预测准确性不受MTBE含量的影响。近红外光谱法测定汽油族组成的结果与GB/T 11132—2002《液体石油产品烃类测定法(荧光指示剂吸附法)》测定的结果一致。近红外光谱法快速、准确,可用于在线分析。     

近红外光谱法快速测定加氢物料的双烯含量

采用国产CCDNIR-3000型近红外光谱仪和化学计量学光谱分析软件，在700～1100nm波长范围内．运用数据预处理方法建立了测定制苯生产过程中间加氢物料控制双烯值的分析模型。通过对加氢物料双烯值的测定，验证了近红外光谱方法测定结果与化学分析方法无显著性差异。与化学分析方法相比，近红外光谱方法重复性再现性好，分析快速，准确，操作简单，降低了环境污染，特别适用于生产中间物料控制分析，是一种满足工艺控制的质量监控方法。     

红外光谱法分析SBS改性沥青的影响因素探讨

准确地测定改性沥青中SBS的掺量对工程中控制改性沥青的质量至关重要。选取六种不同的基质沥青、五种不同的SBS改性剂制备改性沥青,然后对其进行红外光谱测试及分析。通过对基质沥青、SBS以及改性沥青红外光谱图的吸收峰分析可以得出,基质沥青的种类、SBS的种类不同均不会对改性沥青吸收峰出现的位置造成影响。同时分析结果表明,基质沥青种类、SBS种类均不会对965cm~(-1)处的吸收峰峰高造成影响,而SBS的掺量对改性沥青965 cm~(-1)处的吸收峰的峰高具有显著的影响。根据改性沥青红外光谱中965cm~(-1)处的吸收峰峰高及其峰高的影响因素分析,说明红外光谱法检测改性沥青中SBS掺量是可行的。     

Near Infrared Spectroscopic Determination of Diesel Fuel Parameters Using Genetic Multivariate Calibration

The use of full spectral region from near infrared spectroscopic analysis does not always end up with a good multivariate calibration model as many of the wavelengths do not contain necessary information. Due to the complexity of the spectra, some of the wavelengths or regions may, in fact, disturb the model-building step. Genetic algorithms are one of the useful tools for solving wavelength selection problems and may improve the predictive ability of conventional multivariate calibration methods. This study demonstrates application of genetic algorithm-based multivariate calibration to near infrared spectroscopic determination of several diesel fuel parameters. The parameters studied are cetane number, boiling and freezing point, total aromatic content, viscosity, and density. Multivariate calibration models were generated using genetic inverse least squares (GILS) method and used to predict the diesel fuel parameters based on their near infrared spectra. For each property, a different data set was used and in all cases the number of samples was around 250. Overall, percent standard error of prediction (%SEP) values ranged between 2.48 and 4.84% for boiling point, total aromatics, viscosity, and density. However, %SEP results for cetane number and freezing point were 11.00% and 14.86%, respectively.     

红外光谱分析在润滑油中的应用

红外光谱是一种高效的分析方法。通过几个案例,介绍了红外光谱分析在润滑油中的应用。每种分子都有独特的红外吸收光谱,红外吸收光谱法就是利用分子对红外光的特征吸收频率,判断分子中是否存在某种官能团,从而进行分析和鉴定。红外光谱分析以其快速,样品量少,提供信息量多,用途广而在润滑油行业得到广泛应用。利用红外光谱分析可以对在用油进行监测,为换油提供依据;通过对比正常油和问题油的红外图谱,可以找出导致油品使用中产生问题的原因,找到污染物质以及进行油品打假等。     

Near Infrared Spectroscopic Determination of Diesel Fuel Parameters Using Genetic Multivariate Calibration

Abstract

The use of full spectral region from near infrared spectroscopic analysis does not always end up with a good multivariate calibration model as many of the wavelengths do not contain necessary information. Due to the complexity of the spectra, some of the wavelengths or regions may, in fact, disturb the model-building step. Genetic algorithms are one of the useful tools for solving wavelength selection problems and may improve the predictive ability of conventional multivariate calibration methods. This study demonstrates application of genetic algorithm-based multivariate calibration to near infrared spectroscopic determination of several diesel fuel parameters. The parameters studied are cetane number, boiling and freezing point, total aromatic content, viscosity, and density. Multivariate calibration models were generated using genetic inverse least squares (GILS) method and used to predict the diesel fuel parameters based on their near infrared spectra. For each property, a different data set was used and in all cases the number of samples was around 250. Overall, percent standard error of prediction (%SEP) values ranged between 2.48 and 4.84% for boiling point, total aromatics, viscosity, and density. However, %SEP results for cetane number and freezing point were 11.00% and 14.86%, respectively.     

润滑油黏度可见/近红外光谱快速无损检测方法

 提出了一种应用可见/近红外光谱技术进行汽车润滑油黏度快速无损检测的新方法。对150个润滑油样本进行光谱扫描和平滑、变量标准化等预处理,比较了不同建模方法的检测精度。采用主成分分析法(PCA)和连续投影算法(SPA) 2种方法提取的特征变量作为模型输入变量,分别建立了偏最小二乘模型(PLS)、多元线性回归模型(MLR)和人工神经网络模型(BPNN)。结果表明,PCA-BPNN和SPA-BPNN模型的预测效果远优于其它模型(PCA-PLS、PCA-MLR、SPA-PLS和SPA-MLR),预测相关系数(r)分别为0.971和0.964。表明BPNN模型可以很好地利用光谱数据中的非线性信息,同时也表明SPA是一种有效的特征波长提取方法,选取的特征波长有利于汽车润滑油黏度快速检测仪器的开发。     

傅里叶变换红外光谱法测定丁基橡胶的不饱和度

建立了傅里叶变换红外光谱法测定丁基橡胶不饱和度的分析方法。研究结果表明,该分析方法不仅制样方法简单、测定速度快,而且具有较好的准确性,特别适用于丁基橡胶这种黏度大、不饱和度低试样的测定,为丁基橡胶工业生产及时提供不饱和度数据,为产品质量监控提供方便。     

Web近红外光谱原油快评技术开发与应用

开发了Web版原油快评软件,在软件构架层面,由原油快评系统用户应用模块、原油快评近红外光谱库管理模块、原油快评建模模块、原油快评模型库管理模块和用户管理模块构成。该软件实现了模型库的统一维护和统一发布、光谱数据库和评价数据库的统一管理,对现有的原油快评算法进行了升级,经过对升级算法的综合调试使用,可明显提高预测结果的计算速度和识别准确率。收录石化企业A、B常加工原油并分别建立了石化企业A、B原油近红外光谱数据库,将石化企业原油近红外光谱数据库与中国石化石油化工科学研究院原油近红外光谱数据库进行合并,建立快评分析模型,对常加工油种进行监测分析,结果表明近红外光谱快评结果较为准确。