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ArticleName Complex control of the state of steel pins in Soderberg electrolytic cells by using computer vision systems
DOI 10.17580/tsm.2018.03.04
ArticleAuthor Bazhin V. Yu., Kulchitskiy A. A., Kadrov D. N.

Saint-Petersburg Mining University, Saint Petersburg, Russia:

V. Yu. Bazhin, Dean of Chemical and Metallurgical Faculty, e-mail:
A. A. Kulchitskiy, Assistant Professor of a Chair of Automation of Technological Processes and Productions, e-mail:
D. N. Kadrov, Post-Graduate Student of a Chair of Automation of Technological Processes and Productions


Our study describes the problem of automated diagnostics of the state of anode steel pins in Soderberg electrolytic cells with a top current supply as it is the key component of metallurgic unit’s current lead. We proposed a non-contact control over the shape and dimensions of current lead pin’s working component by electro-optical projection technique and usage of a computer vision camera. The received combination of current lead pin’s sections images enables an estimation of its geometric parameters. The assessment is performed for 0.3 Мpx and 5 Мpx cameras with min and max resolution parameters, which are used in the majority of industrial computer vision systems. The investigation was performed on possibility of installing a remote control system to assess wear out of NOEL crane’s pins. The respective tasks of determining current lead pins’ geometry and controlling their instalment on the planned horizon in the anode forming were further combined. The contributing errors of an electro-optical current lead pin controlling system were determined. The main attention is paid to analysis of the system’s instrumental errors, such as background noise, object surface reflection, object positioning as regards the computer vision camera, computer vision camera position as regards the reference point — electrolytic cell, optical system aberration, optical medium refraction in workshop conditions with relevant numerical evaluation. To make the assessment more convenient, the results of accuracy analysis are specified in the table, enabling the estimation of determination errors: the shape of current lead pin and errors parameters, its radius and instalment on the planned horizon. The performed estimation allowed us to establish recommended parameters for a computer vision camera and its position to solve the task of a complex control of current lead pins in electrolytic cells with self-baking anodes.

keywords Aluminum electrolytic cell, self-baking anodes, electro-optical monitoring, computer vision, current lead pins monitoring, loader cranes with computerized numerical control, electro-optical system errors

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