Abstract: Ladle bottom blowing is an important component of steelmaking production and plays a positive role in improving the quality of molten steel. A ladle bottom blowing online intelligent control system based on thermal imaging temperature measurement technology and a multi parameter bottom blowing flow prediction and control model was designed and developed to address the significant fluctuations in flow rate during on-site bottom blowing control, combined with the practical experience of on-site operators. Based on the multi parameter ladle bottom blowing flow rate model, the current bottom blowing flow rate can be accurately determined. During the strong blowing stage, the calculated value of the model is slightly lower than the actual value by 20-100 L/min, which can still meet the on-site bottom blowing needs. The use of an online thermal imaging monitoring model to monitor and analyze the stirring of molten steel in the ladle can achieve real-time monitoring of the bottom blowing of the ladle, and calculate the ratio of the exposed area of the molten steel to the measured area. When the area ratio P_s is 0, 15%-20%, or greater than 60%, it can ensure the effect of stopping blowing, weak blowing, and strong blowing. A multi parameter prediction and control model for ladle bottom blowing flow rate was used and combined with an online thermal imaging monitoring model to calculate the ratio of bare leakage area of molten steel, the system has achieved precise control of on-site ladle bottom blowing flow rate. After the system was put into operation, the outlet-temperature fluctuation of the ladle was relatively uniform, and the proportion of furnaces below 1 550 ℃ decreased from 69% to 27.5%, the number of inclusions in the steel billet has been significantly reduced, accounting for about 80% of the amount before the system was put into operation. The occurrence of submerged nozzle clogging has also reduced, the bottom blowing effect was significantly improved, and at the same time, it assisted in efficiently completing the ladle bottom blowing stirring work on site, reducing personnel labor intensity.

Key words: ladle furnace, bottom blowing stirring, thermal imaging, bottom blowing flow, intelligent control