A New Method for Rapid and Accurate Determination of Aromatics Content in Fuel Oil

Abstract

A new method for rapid and accurate determination of aromatics content in fuel oil, the specific process is as follows: first scan the ultraviolet spectrum of a certain number of fuel oil samples, and use conventional methods to test the content of the target value as a training set. Then, the empirical mode decomposition is performed on the spectral signals of the training set in turn, and a certain number of intrinsic mode functions (IMF) and residual items are obtained. Then, the previous high-frequency IMF is summed to form a high-frequency signal, and the remaining IMF and residual term are summed to form a low-frequency signal. The high-frequency signal and the low-frequency signal are expanded into an extended matrix in the variable direction, and a partial least squares regression model is established between the extended matrix and the target detection value. The same decomposition, addition and expansion are performed on the ultraviolet spectrum of the prediction set, and the content of unknown components can be predicted by substituting it into the model. The advantage of the present invention is that the self-adaptive Hilbert-Huang transformation method is introduced, and at the same time, the unfolding strategy is used for reference, which not only fully utilizes the data information, but also avoids the selection of model parameters.

Description

technical field [0001] The invention of the method belongs to the field of quality detection, and in particular relates to a method for determining the content of aromatic compounds in fuel oil (gasoline / diesel). Background technique [0002] With the acceleration of industrialization, the quality of the air is deteriorating, especially in recent years, the phenomenon of smog has increased, seriously affecting human health and life safety. Among them, the exhaust emission of motor vehicles is an important cause of smog. For example, large vehicles that use diesel are "repeat offenders" that emit fine particles. Although small vehicles that use gasoline emit gaseous pollutants, they are also very serious in foggy days. It is easy to transform into secondary particle pollutants and aggravate smog. Various countries have successively issued environmental protection regulations on air cleanliness, among which the restrictions on the content of olefins, aromatics, benzene and ad...

AI Technical Summary

Problems solved by technology

Direct and simple averaging sometimes results in bad results. Although weighted averaging works better, the selection of weights is a difficult point. The optimized weights are good for the group of data, and the effect of changing the group of data may become worse.

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