Development of a Method for Optimization of the Process of Extraction of Values of Numerical Characteristics of Oil Feedstock Components from Graphical Data of Chromatographic Analysis

Abstract

A variant of the algorithm has been developed to perform the procedure of automated recovery of numerical values of graphically represented chromatograph signal function, studying the component composition of heavy oil feedstock samples. The problem, which the developed method aims to solve, consists in the poor adaptation of chromatographs to the oil industry: oil is a natural raw material, which is not chemically pure, therefore not all numerical characteristics of the components contained in the investigated sample are fixed within the chromatographic study. In the current configuration of the method, the values from the chromatogram are recorded manually. The developed method takes as input data the images of oil chromatograms obtained in the laboratory, presented in the original black and white colour scheme. The output data of the method is an array of numerical values of coordinates reconstructed with a step of one pixel. The size of the error in the reconstruction of the values by the method is much smaller than the threshold set by the petrochemical laboratory. In addition to automating the indicated task, the array of obtained coordinate values was vectorized in order to use the vector as input data in the Transformer model to solve the problem of predicting the redistribution of hydrocarbon components of heavy oil under the influence of catalysts. As a result of the change in input data representation, the time required to obtain a prediction and the training time were reduced by a multiple, while the value of the average prediction error decreased.