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加热炉加热过程的智能优化控制

Intelligent Optimization Control in Furnace Production Process

【作者】 朱传清

【导师】 李胜利; 李伯群;

【作者基本信息】 辽宁科技大学 , 材料加工工程, 2012, 硕士

【摘要】 钢坯加热是轧钢生产过程中一个重要的环节,直接影响着产品质量、产品成本和生产设备安全等多项生产过程指标。因此,建立先进且实用的加热炉控制系统,对于钢铁企业来说,有着十分重要的现实意义。目前,轧钢企业的加热炉通常为推钢式或步进式加热炉,其主要控制目标是加热炉生产出的钢坯在满足轧制工艺要求的前提下有高的钢坯加热效率,节能降耗,降低企业成本,减少钢坯表面的氧化烧损和脱碳,延长设备的使用寿命。由于轧钢加热炉是一个比较复杂的工业系统,其中包括化学、热力学和物理上的各种过程,其控制具有大滞后、多变量、强耦合、非线性、大惯性等特点,对其进行准确的建模非常困难,而且炉内钢坯温度分布不能直接测量、外界扰动因素多,加热过程受多种生产工艺因素的制约,因此采用传统的优化控制方法难于收到理想的效果。目前,大部分加热炉的生产还只能依靠操作人员凭经验调节底层控制回路的设定值,当工况发生变化时,总是出现过氧燃烧或缺氧燃烧现象,既浪费了大量的能源,又降低了钢坯的加热质量。针对以上情况,本文做了如下工作:(1)钢坯加热工艺的制定。以金属学原理为基础,分析了金属的加热温度、加热速度和加热制度,结合鞍钢厚板厂的生产实际,对加热钢坯进行了分类,对每一类钢种在炉内各段的加热温度和加热速度分别进行了设定。(2)加热炉控制策略的设计。根据控制系统自身的特点,同时结合生产实际,对加热炉的炉膛温度、煤气与空气流量及其炉膛压力分别设计一套控制系统。(3)加热炉炉温的优化设定。以加热炉的能耗最小、钢坯氧化烧损最小、钢坯断面温差最小为约束条件,建立优化目标函数,并采取优化算法对该函数进行求解,获得最优炉温分布曲线,同时根据专家经验知识对最优炉温分布进行修正,以满足实际生产过程的要求。(4)采用耐高温温度测试记录装置对Q345A钢的加热过程进行在线测试,检验加热炉控制系统的运行状况,同时获得钢坯温度随时间变化的曲线,为加热制度的优化提供了可靠的数据支持。

【Abstract】 Heating slab process is an important part in steel rolling production process, which not only affects directly product performance, but also influences product cost and safety of production equipment in production process. So it is very important to steel makers by using advanced control means.At present, most of furnace is pusher-type or walking beam type, the main content of furnace control system is on the premise of that slab met the demands of rolling can be produced in the furnace, to improve heating efficiency of slab, to save energy consumption, to reduce oxidation burning loss and decarburization of slab surface, and to prolong service life of equipment. But furnace is a typical complex industry controlled object, in which all kinds of chemical, thermodynamic and physical process are contained. Furnace system has characteristics of pure hysteresis, multivariable, compact coupling, nonlinear and big inertia. It is very difficult to make an accurate mathematical model. The temperature in furnace can not be measured directly because of much disturbance outside. Heating process is constrained by many kinds of production technology factor. So it is difficult to reach a satisfied controlled effect by applying classical optimization control method. Now, most production of furnace only depends on operators by experience to control base loop set-point value. When operating condition is changed, under heating or overheating will occur, which not only wastes resource, but also decreases production quality. According to the above things, main work is done in the paper as follows.(1) A heating process was set. Based on the metallography principle, analyzed the metal heating temperature, heating speed and heating schedule, combined with the Heavy Plate Plant of Anshan Iron and Steel production situation, classified the reheating billet, each type of steel’s reheating temperature and heating rate in the furnace are set.(2) Designed an automatic control strategy of reheating furnace. According to the characteristics of control system and the production condition of reheating furnace, the control system of furnace temperature, gas and air flow rate and pressure of furnace were respectively designed.(3) The optimization of the heating furnace temperature was set in this paper. In order to realize minimum energy consumption, minimum billet oxidation burning loss, minimum billet temperature difference between billet surface and center, the optimal target function was established, the function was solved by optimization algorithm. In the last we got the optimal temperature distribution curve. According to the furnace operators’experience and knowledge, the optimal furnace temperature distribution was modified, to meet the needs of practical production process.(4) Using high thermo stability temperature testing device, we actually measured the on-line temperature of Q345A steel in the reheating process, to check the running state of automatic control strategy. Meanwhile, the steel temperature changing curve was obtained, which could provide dependable data for the optimizing of reheating schedule.

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