Algorithm for applying regression analysis to determine the concentration of the main component in mineral raw materials by X-ray fluorescence method

¹ Siberian Federal University, Krasnoyarsk, Russia
² Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia
³ Krasnoyarsk State Agrarian University, Krasnoyarsk, Russia
⁴ China Aviation Industry General Aircraft Zhejiang Institute Co., Ltd, China
⁵ Bukhara Engineering-Technological Institute, Bukhara, Uzbekistan
⁶ Sochi State University, Sochi, Russia
⁷ FSBEE HE Siberian Fire and Rescue Academy EMERCOM of Russia, Zheleznogorsk, Russia

^* Corresponding author: kovalev.fsu@mail.ru

Abstract

X-ray fluorescence analysis (XRF) is currently in high demand in such branches of science and technology as metallurgy and geology. Today, it is important to create such methods of X-ray fluorescence analysis that would provide high accuracy of the results obtained along with a short execution time. The basic work is a technique, the essence of which is the use of regression analysis to determine the content of gold, as the main component in jewelry alloys. The technique uses a training sample that contains correlated radiation intensities of sample components with their gold content, determined by the assay method of analysis. In this paper, it is proposed to apply a similar approach to the analysis of mineral raw materials. Raw materials from the same deposit may have a similar composition, which allows you to collect enough statistical data to apply regression analysis. The paper proposes an enlarged algorithm for the development of such methods of X-ray fluorescence analysis. Such methods are of limited use, since they depend on the representativeness of the training sample and therefore can only be used to analyze materials of the same type, but their strengths are high accuracy and low time costs.