GOALI: Online Dynamic Control of Cooling in Continuous Casting of Thin Steel Slabs

GOALI：薄板坯连铸冷却在线动态控制

• 批准号: 0500453
• 负责人: Brian Thomas
• 金额: $ 37万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-05-01 至 2009-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0500453&HistoricalAwards=false
• 关键词: GOALI; Online; Dynamic; Control; Cooling

The objective of this research is to accurately predict and control temperature in real time during the continuous casting of large, semi-finished steel shapes. The approach is to create a fast, accurate transient computer model of heat transfer during the solidification process that serves as a "software sensor", calibrated in real time through online temperature measurements to provide feedback to a control system, based on algorithms which will be designed specifically for this class of problem. The new software system will continuously read in operating conditions and mold temperatures and continuously adjust the spray-water flow rates in the secondary cooling zone of the caster, in order to maintain the desired temperature profile throughout the steel. This profile will be set by steel plant engineers, in order to minimize the formation of cracks and other defects. The system will be calibrated using thermocouple and optical temperature sensors, tested and implemented at an operating U.S. thin slab caster. This project is important because 96% of the 100 million tons of steel produced in the U.S. each year is continuously cast, and the fraction produced by the new high-speed thin-slab casting process grows every year. This process experiences many defects caused by undesired temperature variations during spray cooling, which are unavoidable using current control systems. Conventional feedback control cannot be used because temperature sensors are too inaccurate and expensive. The model-based predictive control system proposed here must overcome many challenges, including the high speed of the process and increased relative importance of mold solidification. This project will directly benefit the steel industry, allowing it to become more competitive by increasing steel quality and lowering rejects. It will augment the research efforts of the Continuous Casting Consortium at the University of Illinois, which also helps to disseminate new knowledge to its member companies in this industry. In addition, improved understanding of the modeling and control issues will broadly benefit other manufacturing processes. The research will educate students who will take these new technologies into industry.

本研究的目的是精确预测和控制温度在真实的时间在连铸过程中的大型，半成品钢的形状。 该方法是创建一个快速，准确的瞬态计算机模型的热传递在凝固过程中，作为一个“软件传感器”，校准在真实的时间，通过在线温度测量提供反馈给控制系统，基于算法，这将是专为这类问题。 新的软件系统将持续读取操作条件和结晶器温度，并持续调整连铸机二次冷却区的喷水流量，以保持整个钢材的理想温度分布。 该轮廓将由钢铁厂工程师设置，以最大限度地减少裂缝和其他缺陷的形成。 该系统将使用热电偶和光学温度传感器进行校准，并在美国薄板坯连铸机上进行测试和实施。 该项目非常重要，因为美国每年生产的1亿吨钢中有96%是连续铸造的，而且新的高速薄板坯连铸工艺生产的钢比例每年都在增长。 该过程经历了由喷雾冷却期间不期望的温度变化引起的许多缺陷，这是使用当前控制系统不可避免的。 由于温度传感器太不精确和昂贵，不能使用常规的反馈控制。 本文提出的基于模型的预测控制系统必须克服许多挑战，包括工艺的高速化和结晶器凝固的相对重要性的增加。 该项目将使钢铁行业直接受益，通过提高钢材质量和降低废品率来提高其竞争力。 它将加强伊利诺伊大学连铸联盟的研究工作，这也有助于向该行业的成员公司传播新知识。 此外，对建模和控制问题的更好理解将广泛有益于其他制造过程。 这项研究将教育那些将这些新技术带入工业的学生。