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铁矿氧化球团链篦机—回转窑模拟模型和控制指导专家系统的研究
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摘要
为适应大型化高炉对炉料结构的要求,铁品位高、还原性好,粒度均匀、成分稳定、冶金性能优良的球团矿日益受到青睐,本世纪以来我国球团矿产量持续攀升。链篦机-回转窑工艺作为我国氧化球团主导工艺,具有大型、连续、高温、封闭等特点,目前生产自动化水平仍然较低。本论文针对链篦机-回转窑生产参数检测困难、控制复杂等问题,进行了氧化球团链篦机-回转窑模拟模型和控制指导专家系统的研究,并开发了系统软件,实现了生产过程透明化和实时生产控制指导。
     为实现难检生产信息的在线软测量,根据传热学、流体力学、反应动力学和热力学原理,建立了链篦机、回转窑、环冷机温度场模型,实现了生产过程中链篦机运行方向和料层高度方向任意位置球团料层温度分布、回转窑轴向温度分布以及环冷机运行方向球团温度分布的在线软测量;建立了链篦机干燥段水分迁移模型,实现了生产过程中沿链篦机运行方向和料层高度方向任意位置球团料层水分实时分布状态透明化和球团水分蒸发速率的在线软测量,以及过湿带产生、移动和球团料层干燥效果的实时监测;建立了链篦机预热段磁铁矿氧化模型,实现了生产过程中沿链篦机运行方向和料层高度方向任意位置球团料层磁铁矿氧化率实时分布及预热球团FeO含量的在线软测量。采用气体温度检测值进行了模型验证,链篦机和回转窑模型准确率分别达到90.25%和92.25%。
     根据质量和能量守恒原理,建立了链篦机-回转窑-环冷机系统物料、气流和热量平衡模型,对系统能量分配情况和利用水平进行生产在线评判。针对我国球团生产中存在的原料和生产计划等主动调整,提出了基于平衡的生产状态预测方法,并结合专家系统给出调整措施,以稳定和优化球团生产。
     利用领域专家经验和球团基本原理,建立了链篦机-回转窑生产过程控制专家系统,实现了生产过程控制指导。针对链篦机-回转窑生产过程提出了以回转窑球团焙烧温度和链篦机预热Ⅱ段烟罩气体温度为核心的控制策略;针对环冷机球团冷却过程提出了以成品球团矿卸料温度为核心的控制策略;针对链篦机漏风异常,设计了异常位置判断方法。根据“参数状态判断→原因分析→措施选取"的推理过程,制定了多级推理策略。
     采用Visual C++开发了链篦机-回转窑生产控制指导系统软件。软件运行稳定,界面友好,操作简单。该系统在国内某球团厂投入生产应用,链篦机-回转窑系统生产运行稳定率从91.0%提高到了94.2%;球团矿产质量指标改善,FeO含量下降了0.05%,抗压强度提高了86N/P,转鼓强度提高了0.09%,耐磨指数下降了0.1%,筛分指数下降了1.04%,一级品率提高了2.54%;产质量提高和能耗降低综合经济效益可达749.5万元/年。
In order to meet the burden structure requirement of large-scale blast furnace, iron ore oxide pellet with high grade, good reducibility, homogeneous particle size, stable composition and favorable metallurgical performance is becoming popular. The output of pellet has been keeping rising since the turn of this century. As the dominant process in China, the characteristics of large-scale equipments, continuous process, severe environment and close system make grate-kiln process hard for parameter detection and difficult to control. The accuracy and normalization of grate-kiln process control need to be improved. Therefore, research on simulation models and control guidance expert system of grate-kiln process was carried out and software was developed to make the production process transparent and realize real time control guidance.
     Mathematical models were developed based on heat transfer theory, fluid mechanics, reaction thermodynamics and kinetics. Models of temperature distribution were developed to obtain pellet temperature at any point of grate, along axial direction of kiln and running direction of cooler during pellet production. Model of moisture distribution in drying section was developed to detect pellet moisture and water evaporation rate at any point of pellet bed, and monitor emergence and migration of over-wet zone as well as the drying results. Model of oxidation degree distribution in preheating section was developed for online detection of oxidation degree of magnetite and FeO content of preheated pellet at any point of pellet bed. These models were validated with detected gas temperature. The accuracies of grate model and kiln model were90.25%and92.25%, respectively.
     Mass balance model, gas flow balance model and heat balance model of grate-kiln-cooler process were developed under the law of conservation of mass and energy. With the combination of instrumental detection and model calculation, on-line estimation of heat distribution and utilization level can be implemented. To solve the control difficulties caused by initiative change of raw material structure or daily output plan, a balance based method for production status prediction was put forward. And supplementary measures can be provided by expert system for production stabilization and optimization.
     Expert system for grate-kiln process control was developed for real time production control guidance, using the summary of decades of operational experience and fundamental principles of pelletizing. The "roasting temperature of pellet in kiln&gas temperature in gas hood of preheating section" dominated control strategy was put forward for grate-kiln process, while "pellet temperature at discharging end of cooler" was chosen to be control core for cooler process. More over, rules were established to detect the location of air leakage anomalies in grate. A multistage reasoning strategy was put forward based on the reasoning process of "estimation of parameter status-reason analysis-adjustment measure selection".
     Software was developed with Visual C++. It is stable, user-friendly, and easy operated. This system was put into practice in a domestic pellet plant. The application results show that the stability rate of production is increased from91.0%to94.2%. Quality indexes of pellet product are improved, for FeO content of finished pellet is0.05%lower, compressive strength is86N/P higher, tumbler strength is increased by0.09%, abrasion resistance index and screening index are0.1%and1.04%lower respectively, while first grade rate of pellet is increased by2.54%. The total economic benefit is about7.5million RMB per year.
引文
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