Identification of steel billets marking at rolling shop no. 1 of JSC "A. A. Ugarov Oskol electrometallurgical plant" using neural networks

The report is about the solution of a steel billet identification problem before its loading into the methodical furnace of a rolling shop of a metallurgical plant. The task is to develop an automated system that allows one to relieve the loading control station operator from the task of manual identification of each billet. The article considers such approaches to solve the problem in question as application of additional markings to the billets for the purpose of further automatic identification, and development of a system for recognition of the existing markings, which is based on the neural networks. An experiment on marking of the “gray” and “light” billets is conducted with the help of the laser markers of different power. The readability of the obtained codes is evaluated. The conclusion is made that laser marking can be applied only on clean rolling metal (without oxide scale). Therefore, the method is proposed to develop a neural network-based system for identification of the existing marking and implement it. The system is successfully introduced into production and allows one to achieve approximately 90