炼钢 ›› 2025, Vol. 41 ›› Issue (2): 47-52.

• 炉外精炼 • 上一篇    下一篇

120 t钢包底吹在线智能调控系统开发与应用

董晓雪1,韩  啸1,乔西亚1,李  晶2,于学渊3,赵  阳3   

  1. 1.辽宁省化学冶金工程重点实验室,辽宁 鞍山 114051;
    2.北京科技大学 绿色低碳钢铁冶金全国重点实验室,北京 100083; 
    3.建龙集团抚顺新钢铁有限责任公司 炼钢厂,辽宁 抚顺 113001
  • 出版日期:2025-04-05 发布日期:2025-04-02

Development and application of online intelligent control system for bottom blowing in 120 t ladle

  • Online:2025-04-05 Published:2025-04-02

摘要: 钢包底吹是炼钢生产中重要的精炼手段,对提高钢液质量发挥着积极作用。为了保证底吹效果的一致性,结合现场操作人员的实际经验,设计开发了一套基于热成像测温技术与多参数底吹流量调控模型相结合的钢包底吹在线智能调控系统。基于多参数钢包底吹流量模型可以较为准确地确定当下底吹流量,强吹阶段时模型计算值比实际值略低20~100 L/min,仍能满足现场底吹需求;采用在线热成像监测模型对钢包钢液搅拌情况进行监控分析可以实现钢包底吹的实时监测,并计算钢液裸露面积占所测区域面积比值,面积比值Ps分别为0、15%~20%、大于60%时,可以保证停吹、弱吹、强吹效果;采用多参数钢包底吹流量预测调控模型并结合在线热成像监测模型计算求出的钢液裸漏面积比值,系统实现了现场钢包底吹流量的精准综合调控。系统投用后,钢包出站温度波动较为均匀,低于1 550 ℃的炉次占比从69%减少到27.5%;钢坯中的夹杂物数量大幅减少,约为投用前的80%,且浸入式水口结瘤减少,底吹效果明显提高,同时协助现场高效地完成了钢包底吹搅拌工作,降低了人员劳动强度。

关键词: 钢包, 底吹搅拌, 热成像, 底吹流量, 智能调控

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 Ps 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