Abstract
The paper presents an image-based method for monitoring glass melting process in a glass furnace. To ensure the high reliability of the monitoring system and compliance with the industrial conditions, a robust vision head module was designed and integrated with the cooling and refraction systems. The vision system structure was verified in the course of long-term tests, which allowed for the identification of the risk factors and impact of operating conditions. Based on the images recorded during the operation, algorithms for determining selected process parameters were implemented. Additionally, self-diagnostics algorithms were proposed to identify potential undesired system behaviours in the future operation. The integration into the glassworks network and knowledge database was also an important element of the described system. The article ends with the presentation of the benefits of an ongoing image-based monitoring of glass melting processes and of the capabilities of the statistical data analysis employing a machine learning technology.
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Garbacz, P., Czajka, P. (2022). Image-Based Monitoring of Glass Melting Process. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2022: New Solutions and Technologies for Automation, Robotics and Measurement Techniques. AUTOMATION 2022. Advances in Intelligent Systems and Computing, vol 1427. Springer, Cham. https://doi.org/10.1007/978-3-031-03502-9_30
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DOI: https://doi.org/10.1007/978-3-031-03502-9_30
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