APPLICATION OF MACHINE VISION TO ENSURE SAFETY IN THE VICINITY OF AUTOMATICALLY CONTROLLED VEHICLES IN METALLURGY

1 SIRNÍK Tomáš
Co-authors:
2 BEČKA Miloslav 3 DVORSKÝ Michal 4 ŠVEC Pavel
Institution:
1 VSB - Technical University of Ostrava, Ostrava, Czech Republic, EU, tomas.sirnik.st@vsb.czmiloslav.becka.st@vsb.cz, michal.dvorsky.st@vsb.cz, pavel.svec@vsb.cz
Conference:
31st International Conference on Metallurgy and Materials, Orea Congress Hotel Brno, Czech Republic, EU, May 18 - 19, 2022
Proceedings:
Proceedings 31st International Conference on Metallurgy and Materials
Pages:
868-873
ISBN:
978-80-88365-06-8
ISSN:
2694-9296
Published:
1st November 2022
Proceedings of the conference were published in Web of Science and Scopus.
Metrics:
388 views / 169 downloads
Abstract

The paper deals with the application of automatically controlled vehicles in the metallurgical industry. The aim of the paper is to present a proposal for innovative safety of operating workers in the vicinity of an automatically controlled fire truck during the production of coke. The introductory part of the paper will be devoted to the explanation of the concept of automatically controlled vehicles, their possibilities, areas of their application and specifics in the field of metallurgical operations. The main part of the paper will be devoted to the creation of a proposal to ensure safety in the track area of an automatically controlled fire truck during the production of coke. Security designs using optical barrier fencing and control using PLC Simatic series S7-1200 will be presented. Visualization and control of fencing provided by the visualization program Promotic. The second way of innovative security is the use of a machine vision system using operational cameras on a fire truck. An algorithm based on environment color filtering with subsequent detection of operational workers will be introduced. The algorithm was tested on real camera recordings from the coking plant's operating environment.

Keywords: Automatically controlled vehicles, safety, fire truck, coke plant, machine vision

© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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