ABSTRACT
A new analytical method of analyzing dimethyl ether (DME) content in liquefied petroleum gas (LPG) is proposed in this paper. An unsolved problem about quick detection of the composition of LPG has been settled with this method. A set of precise preparation apparatus for DME/ LPG solution and a set of quickly analytical system of LPG based on near infrared technology were designed. The analytical equipment can be conveniently connected to the sampling cylinder because it can bear 3.5 MPa pressure. Oblique projection algorithm was used to separate the pure spectra of DME from that of the LPG's solutions. The standard curve of the concentration of DME (c) has been built by using the Intensity (I) of pure signal of DME in the LPG solution and the concentrations. The correlation coefficient of the equation is 0.999 4. The result of external validation shows that the relative error is less than 2.0%. The new method has the advantages such as fast, easy and noneed of expensive multivariate modeling.
ABSTRACT
A new rapid quantitative method for the determination of oxygenates and the compounds not included in the national standard in gasoline using near-infrared spectroscopy is raised by this paper. This method combine near-infrared spectroscopy with oblique projection. This experiment choose four different types of gasoline, including reconcile gasoline, FCC refined gasoline, reformed gasoline and desulfurizing gasoline. Prepare series gasoline samples containing different concentrations and different types of compounds. Using FTIR spectrometer to measure those samples and got transmission spectrums. Oblique projection method could separate quantity spectral signal from mixed spectrum signal, and using projection to calculate and analyze the separated signal to obtain the content of measured component. The deviation between this method and the real content is low, the absolute error is less than 0.8 and the relative error is less than 8%. For the actual gasoline samples, compare results of this method with gas chromatography, the absolute error are less than 0.85 and the relative error are less than 6.85%. This method solves the problem of general multivariate calibration methods. It is very significant for the development of rapid detection technology using NIR suitable for on-site and the improvement of the quality of gasoline.
ABSTRACT
A rapid discrimination method of edible oils, KL-BP model, was proposed by attenuated total reflectance infrared spectroscopy. The model extracts the characteristic of classification from source data by KL and reduces data dimension at the same time. Then the neural network model is constructed by the new data which as the input of the model. 84 edible oil samples which include sesame oil, corn oil, canola oil, blend oil, sunflower oil, peanut oil, olive oil, soybean oil and tea seed oil, were collected and their infrared spectra determined using an ATR FT-IR spectrometer. In order to compare the method performance, principal component analysis (PCA) direct-classification model, KL direct-classification model, PLS-DA model, PCA-BP model and KL-BP model are constructed in this paper. The results show that the recognition rates of PCA, PCA-BP, KL, PLS-DA and KL-BP are 59.1%, 68.2%, 77.3%, 77.3% and 90.9% for discriminating the 9 kinds of edible oils, respectively. KL extracts the eigenvector which make the distance between different class and distance of every class ratio is the largest. So the method can get much more classify information than PCA. BP neural network can effectively enhance the classification ability and accuracy. Taking full of the advantages of KL in extracting more category information in dimension reducing and the features of BP neural network in self-learning, adaptive, nonlinear, the KL-BP method has the best classification ability and recognition accuracy and great importance for rapidly recognizing edible oil in practice.
Subject(s)
Plant Oils/analysis , Models, Theoretical , Neural Networks, Computer , Plant Oils/classification , Principal Component Analysis , Spectrophotometry, InfraredABSTRACT
A set of rapid analysis system for hydrocarbon composition of heavy oils was designed using attenuated total reflection FTIR spectrometer and chemometrics to determine the hydrocarbon composition of furfural extract oils. Sixty two extract oil samples were collected and their saturates and aromatics content data were determined according to the standard NB/SH/T0509-2010, then the total contents of resins plus asphaltenes were calculated by the subtraction method in the percentage of weight. Based on the partial least squares (PLS), calibration models for saturates, aromatics, and resin+asphaltene contents were established using attenuated total reflection FTIR spectroscopy, with their SEC, 1.43%, 0.91% and 1.61%, SEP, 1.56%, 1.24% and 1.81%, respectively, meeting the accuracy and repeatability required for the standard. Compared to the present standard method, the efficiency of hydrocarbon composition analysis for furfural extract oils is significantly improved by the new method which is rapid and simple. The system could also be used for other heavy oil analysis, with excellent extension and application foreground.
Subject(s)
Furaldehyde/chemistry , Hydrocarbons/analysis , Plant Oils/chemistry , Spectrophotometry, Infrared , Calibration , Least-Squares Analysis , Spectroscopy, Fourier Transform InfraredABSTRACT
In the spectral analysis, a large-scale application of the traditional multivariate analysis methods has been limited by both high cost and poor applicability of the calibration models. A new multivariate analysis method was proposed for multicomponent systems in the present paper. Determining MTBE content in gasoline solution by infrared spectroscopy was studied. The spectra of five kinds of gasoline and their 50 narrow distillation fractions were used to build the background library. The oblique projection algorithm was applied to the spectra of MTBE gasoline solution samples to extract the purespectral signal of MTBE in the solution. A unary linear regression curve was built between the pure spectral signals of MTBE and their concentrations with a correlation coefficient of 0.995 2 and an intercept of 0.025. Compared with the orthogonal projection algorithm method and PLS model method, a large amounts of calibration samples and complex model are no longer needed by the new method which is simpler, more accurate and with better applicability.
ABSTRACT
In the present paper, a new correction method of baseline drift of discrete spectrum is proposed by combination of cubic spline interpolation and first order derivative. A fitting spectrum is constructed by cubic spline interpolation, using the datum in discrete spectrum as interpolation nodes. The fitting spectrum is differentiable. First order derivative is applied to the fitting spectrum to calculate derivative spectrum. The spectral wavelengths which are the same as the original discrete spectrum were taken out from the derivative spectrum to constitute the first derivative spectra of the discrete spectra, thereby to correct the baseline drift of the discrete spectra. The effects of the new method were demonstrated by comparison of the performances of multivariate models built using original spectra, direct differential spectra and the spectra pretreated by the new method. The results show that negative effects on the performance of multivariate model caused by baseline drift of discrete spectra can be effectively eliminated by the new method.
ABSTRACT
A new quantitative method to determine the NH4H2PO4 in ABC powder extinguishing agent and to distinguish between ABC and BC powder extinguishing agents using near infrared diffuse reflectance spectroscopy is proposed. A PLS calibration model for the NH4H2PO4 content in extinguishing agent powder was established, with RMSECV = 2.1, RMSEP = 2.4. An identification model for ABC and BC powder extinguishing agents was built by SIMCA and the identification accuracy rate is 100%. This method, compared to the present standard method, has the characteristics of rapidness and easy operation, whichis fit for the quantitative analysis and type distinguishing of the fire products on site.