电弧炉冶炼过程行进控制方法的研究与应用
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摘要
电弧炉炼钢是用来生产特殊钢和高合金钢的主要方法。同转炉炼钢相比较，电弧炉具有钢液温度能灵活掌握、热效率高、炉内气氛可以控制、设备简单、工艺流程短等优点，再加上充足的废钢资源以及环保意识的加强，因而世界各国都在稳步地发展电炉炼钢。有效地操作、高效、优质、节能降耗、低成本的运行对钢铁工业是至关重要的。冶炼过程的自动控制系统是电弧炉的一个重要组成部分，直接影响产品的质量和产量。本文以经济指标和工艺指标两条主线，研究了先进控制技术在电弧炉过程控制中的应用，主要内容如下：
(1) 基于经济指标的电弧炉冶炼过程优化设定
为了实现质量稳定可靠和低成本的系统控制目标，围绕终点控制这一基本主线，提出了基于经济指标的生产过程中工艺设定值优化操作思想。对过程参数进行了分析，提出了冶炼工艺优化目标并确定了优化设定值。通过对冶炼过程的能量需求与损失的分析与计算，通过对需氧量、冶炼周期、能量平衡等的分析，建立了以工序效益最大化为目标的工艺模型，对废钢、铁水、吹氧量、电能输入量以及喷碳量等进行优化。通过建立基于模糊数的优化配料计算模型、基于整数混合非线性规划的供电模型，以及基于灰色合金元素收得率校正的合金控制模型，实现了以降低冶炼成本为目标的终点控制的优化设定。
(2) 利用案例推理方法对电弧炉炼钢进行终点预报
采用案例推理的方法建立终点预报的模型。文中给出了求解案例相似度的方法、案例重用的方法。为弥补案例推理方法的不足，结合增量模型终点预报的方法，给出了基于多支持向量机的补偿建模方法，以提高案例推理终点预报的精度。仿真结论表明，基于案例推理和多支持向量机补偿的终点预报方法具有较为理想的预报精度。
(3) 利用分段控制策略对电弧炉炼钢进行终点控制
依据电弧炉冶炼工艺上的阶段划分，建立了分段控制的方法。熔化期采用静态控制方法，以追求冶炼成本的降低；氧化期为提高冶炼钢水的质量，采用智能控制方法，采用T-S模型建立供电量和吹氧量的预设定模型，为提高精度，在终点预报的基础上，采用模糊技术建立了校正模型，提高了终点控制的命中率。
The electric arc furnace (EAF) steelmaking is the main method used to produce special steel and alloy steel. Compare with basic oxygen furnace (BOF) steelmaking, the EAF have advantages such as the temperature of steel liquid can be grasped flexibly, thermal efficiency is high, the atmosphere in the furnace can be controlled, the equipment is simple and the technological process is short. In addition, because of the rich craft resources and the enhanced environmental consciousness, the countries all over the world are developing steelmaking of the electric stove steadily. The effectively operation, high efficiency and high quality, saving energy and reducing the cost are essential to the steel and iron industry. The automatic control system, that influences the quality and output of the products directly, is an important part of an EAF process. The key research of this thesis is the application of advanced control technology in the EAF, and the main content is as follows:
(1) Economic objective-based optimizing setting for the smelting process of EAF
In order to realize the systematic control goal of reliable and steadily quality and lowest cost, an optimal method of process parameters setting values during production has been proposed based on the economic objective in this thesis. Analyzed to the process parameters of EAF, We propose the smelting optimizing goal and determine the optimization setting value. A technological model aimed at the maximum of the process benefit is established based on the analysis of the energy demanded by EAF and the lost, the demand for oxygen and the period of smelt process. The quantity of craft, molten iron, oxygen, powdered carbon and electric power can be optimized by this model, In addition, the linear programming model based on the fuzzy number for craft mating optimization, the power supply model based on the Mixed Integer nonlinear programming and the alloy component control model based on the grey model which is used for correcting the element yield are established to decrease the cost of the smelting process.
(2) Endpoint prediction of EAF smelting process based on the case-based reasoning (CBR)
An endpoint prediction model based on the CBR technology is established in this thesis. A case similarity measuring method and a case utilization method are proposed. In order to remedy the deficiency of the CBR, combining the advantages of the increment model, a compensation modeling method of multiple support vector machines (SVM) is proposed to correct the prediction result of CBR which can improve the precision of the endpoint prediction. The emulation conclusion shows that the CBR model compensated by multiple
(1) 基于经济指标的电弧炉冶炼过程优化设定
为了实现质量稳定可靠和低成本的系统控制目标，围绕终点控制这一基本主线，提出了基于经济指标的生产过程中工艺设定值优化操作思想。对过程参数进行了分析，提出了冶炼工艺优化目标并确定了优化设定值。通过对冶炼过程的能量需求与损失的分析与计算，通过对需氧量、冶炼周期、能量平衡等的分析，建立了以工序效益最大化为目标的工艺模型，对废钢、铁水、吹氧量、电能输入量以及喷碳量等进行优化。通过建立基于模糊数的优化配料计算模型、基于整数混合非线性规划的供电模型，以及基于灰色合金元素收得率校正的合金控制模型，实现了以降低冶炼成本为目标的终点控制的优化设定。
(2) 利用案例推理方法对电弧炉炼钢进行终点预报
采用案例推理的方法建立终点预报的模型。文中给出了求解案例相似度的方法、案例重用的方法。为弥补案例推理方法的不足，结合增量模型终点预报的方法，给出了基于多支持向量机的补偿建模方法，以提高案例推理终点预报的精度。仿真结论表明，基于案例推理和多支持向量机补偿的终点预报方法具有较为理想的预报精度。
(3) 利用分段控制策略对电弧炉炼钢进行终点控制
依据电弧炉冶炼工艺上的阶段划分，建立了分段控制的方法。熔化期采用静态控制方法，以追求冶炼成本的降低；氧化期为提高冶炼钢水的质量，采用智能控制方法，采用T-S模型建立供电量和吹氧量的预设定模型，为提高精度，在终点预报的基础上，采用模糊技术建立了校正模型，提高了终点控制的命中率。
The electric arc furnace (EAF) steelmaking is the main method used to produce special steel and alloy steel. Compare with basic oxygen furnace (BOF) steelmaking, the EAF have advantages such as the temperature of steel liquid can be grasped flexibly, thermal efficiency is high, the atmosphere in the furnace can be controlled, the equipment is simple and the technological process is short. In addition, because of the rich craft resources and the enhanced environmental consciousness, the countries all over the world are developing steelmaking of the electric stove steadily. The effectively operation, high efficiency and high quality, saving energy and reducing the cost are essential to the steel and iron industry. The automatic control system, that influences the quality and output of the products directly, is an important part of an EAF process. The key research of this thesis is the application of advanced control technology in the EAF, and the main content is as follows:
(1) Economic objective-based optimizing setting for the smelting process of EAF
In order to realize the systematic control goal of reliable and steadily quality and lowest cost, an optimal method of process parameters setting values during production has been proposed based on the economic objective in this thesis. Analyzed to the process parameters of EAF, We propose the smelting optimizing goal and determine the optimization setting value. A technological model aimed at the maximum of the process benefit is established based on the analysis of the energy demanded by EAF and the lost, the demand for oxygen and the period of smelt process. The quantity of craft, molten iron, oxygen, powdered carbon and electric power can be optimized by this model, In addition, the linear programming model based on the fuzzy number for craft mating optimization, the power supply model based on the Mixed Integer nonlinear programming and the alloy component control model based on the grey model which is used for correcting the element yield are established to decrease the cost of the smelting process.
(2) Endpoint prediction of EAF smelting process based on the case-based reasoning (CBR)
An endpoint prediction model based on the CBR technology is established in this thesis. A case similarity measuring method and a case utilization method are proposed. In order to remedy the deficiency of the CBR, combining the advantages of the increment model, a compensation modeling method of multiple support vector machines (SVM) is proposed to correct the prediction result of CBR which can improve the precision of the endpoint prediction. The emulation conclusion shows that the CBR model compensated by multiple
引文
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