Increase in efficiency of a continuous casting machine is directly related to reduction of a shutdown period to repair and to eliminate accident consequences. One of the most widespread and severe accidents on the machine is the strand shell breakout under a mold. This article presents results of development and operation of the intelligent system for prediction of liquid metal breakouts under the mold of slab continuous casting machines. The most significant scientific results of the study are: mathematical model of copper mold wall temperatures values distributed on the mold perimeter, diagnostic criteria for strand shell sticking in the mold, and techniques and algorithms of strand shell sticking in the mold. Applying the listed results at development of continuous casting machine automation systems allow to reduce the number of accidents on continuous casting process, what is very important for the steel industry.
Current world economic recession and high competition in the market of ferrous metallurgy products make the issue of improving the efficiency of the steel-making process especially pressing. One of the ways to improve the efficiency of a steel-making unit is to provide the sufficient minimum content of furnace slag in a pouring ladle. It can be achieved by permanent real-time monitoring of the melt stream during tapping from the steel-making unit. The most efficient way to monitor the melt stream is the method based on control of infrared radiation from the steel being tapped. The article offers the analysis of arrays of infrared radiation values from operating steel-making units of the largest smelters of Russia. The authors give some practical design recommendations for monitoring systems of melt stream in the process of tapping from the steel-making unit. They also describe the rule of slag detection in the melt stream.
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