Saint Petersburg Mining University, Saint Petersburg, Russia:

A. V. Boykov, Project Supervisor at the Research and Training Centre for Digital Technology, Associate Professor, Candidate of Technical Science, e-mail: boykov_av@pers.spmi.ru
V. A. Payor, Postgraduate Student of the Department of Process and Plant Automation, e-mail: s215025@stud.spmi.ru

Machine vision-based optical non-destructive monitoring systems are widely used in different industries. Optical systems are able to measure a variety of parameters at high speed and at a distance (in a contactless manner), and all this makes them efficient. Due to the development of computer hardware, optical monitoring techniques can be automated and integrated into process control systems utilized by non-ferrous metals producers. This paper describes a machine vision system that can be used to monitor the melt in the coil of an electromagnetic levitation furnace. Using a case study of levitation melting of aluminium test pieces, the authors describe the result of testing an algorithm designed to track the melt moving in the coil.
Support for this research was provided under Grant No. 22-71-00029 by the Russian Science Foundation, https://rscf.ru/project/22-71-00029/.

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