高炉炉缸内衬的温度场设计及其状态与寿命研究

根据高炉炉缸在实际生产中的情况,将炉缸内衬划分为有限单元,采用能量平衡原理建立炉缸内衬温度分布模型,并应用于高炉炉缸内衬设计,进而对炉缸的工艺设计做必要的调整优化,以此获得合理的炉缸内衬温度分布。在此基础上,通过实际生产中的内衬温度推测炉缸内衬侵蚀程度,对炉缸内衬的寿命进行预测。研究结果表明:采用了温度场分布设计技术优化的碳砖-陶瓷杯炉缸内衬的高炉,陶瓷杯侵蚀速率很缓慢,推测蒜头状部位的陶瓷杯使用时间可达10 a以上。     

沸煮法处理平炉及电炉渣工艺条件研究

通过现场试验,验证了沸煮法处理平炉及电炉渣的可行性,利用正交试验得出了沸煮法处理上海第三钢铁厂平、电炉渣的最佳工艺条件。     

Numerical Prediction of Iron Flow and Bottom Erosion in the Blast Furnace Hearth

The blast furnace (BF) campaign life, which is limited by the hearth erosion, will be decisive for the process to maintain its dominance in ore‐based iron production, so timely prediction of the hearth erosion and proper measures to protect the hearth are important issues. The erosion at the hearth bottom has not received much attention, even though the region is believed to be the most vulnerable part of the hearth. A computational fluid dynamic (CFD) model has been developed to deepen the understanding of iron flow and refractory erosion at the bottom of the hearth. Key boundary and internal conditions, such as slag–iron interface and dead man state, are provided by a BF drainage model which reproduces the tapping process. Simulations with the CFD model illustrate how different factors affect the flow pattern, hearth erosion profile, and bottom breakage ratio. It is shown that the dead man state plays an important role for the flow behavior and erosion conditions in the hearth. The model is demonstrated to predict two erosion types that are commonly encountered in practice.     

转底炉工艺系统基本化学反应的热力学分析

转底炉工艺是直接还原中煤基还原的一种,其内部的热力学反应主要包括含碳球团的自还原反应、含碳球团与氧化性气体间的氧化反应、含碳球团的脱碳反应、含碳球团排出气体的燃烧反应及喷吹焦炉煤气对直接还原的影响等5个部分。对转底炉内部温度、气氛、配煤比的控制,是转底炉直接还原工艺的关键。     

高炉炉缸长寿认识及维护治理实践

炉缸寿命长短直接决定了高炉的一代炉役寿命,至关重要。结合京唐2座有效容积5 500 m 3 高炉的炉缸 构造及对2号高炉炉缸局部温度升高后的治理,浅谈对高炉炉缸长寿及维护的认识。     

高炉炉缸炉底侵蚀模型的研究与开发

采用边界元方法建立某一大型高炉炉缸炉底的侵蚀推测二维模型,能够推定高炉炉缸炉底侵蚀线的位置和形状,及时了解炉衬侵蚀状态。从计算所得的侵蚀图来看,侵蚀轮廓是比较合理的,与实际侵蚀情况非常相近。     

CFD Modeling and Analysis of The Flow,Heat Transfer and Mass Transfer in a Blast Furnace Hearth

Understanding the complex phenomena in the BF hearth is essential to increasing furnace productivity and to extending furnace campaign. Numerical modeling provides a cost‐effective tool to obtain such knowledge. We have developed several continuum‐based mathematical/numerical models to simulate the flow, heat transfer and mass transfer in the lower part of BF and in the hearth. These models have generated an improved insight into the mechanisms for liquid drainage efficiency, lining erosion and wall protection in BF hearth under operational conditions. The current paper provides an overview of these studies, as well as dealing with three specific aspects: (a) Gas flow and pressure on the liquid surface, and its effect on the drainage characteristics; (b) Flow and temperature distributions of liquid iron in the hearth, and the temperature distribution in the refractories; and (c), Titania injection to form Ti(C,N)‐rich scaffolds on the hearth refractory surface, to protect the hearth from erosion.     

太钢新建4350 m~3高炉长寿炉缸炉底研究

以太钢新建4 350m3高炉为例,论述了为实现高炉炉缸炉底的长寿,从高炉的设计、选材和砌筑等方面采取的一系列措施。炉缸设计采用"传热法",炉底设计采用"隔热法",炉缸炉底整体设计采用了"扬冷避热梯度布砖法"。炉缸选材使用优质高导热系数的碳砖,为了克服冷却壁与碳砖之间捣打料带来较大热阻,砌筑过程中碳砖采用顶砌冷却壁方式,并且严格控制砖衬宽度;炉壳与冷却壁采用分段灌浆。通过建立炉缸炉底传热数学模型,进一步表明了该高炉炉缸炉底优良的性能,投产后1 150℃等温线位于炉缸砖衬热面附近,有利于渣铁壳的形成;同时碳砖内部温度普遍低于750℃,温度梯度较小,碳砖脆化及热应力对砖衬的破坏作用较轻,为日后实现长寿炉缸炉底创造了必要的条件。     

高炉炉缸炉底烧穿事故分析及解决对策

介绍了近年来国内高炉炉缸炉底烧穿事故及其处理方法,分析了烧穿的原因,从高炉长寿高效目标出发,提出改进对策,期望迅速扭转烧穿事故频发的局面。     

基于神经网络预测模型的高炉喷煤操作模式优化

针对高炉冶炼过程中喷煤量通常根据炉长经验总结而出、过程建模困难、生产过程工艺指标波动较大的问题,提出了一种喷煤量操作模式匹配的智能优化方法。该方法以高炉喷煤量为研究对象,以某钢厂高炉大量的实际工业运行数据为基础,首先对不可实时检测变量[Si]含量建立了BP神经网络预测模型,以对当前[Si]含量进行预测;然后基于专家标准挑选出优良模式集,采用模糊C均值聚类的方法对优良模式集进行分类;最后以综合工艺指标评判为前提,对当前输入条件采用基于相似度的方法,从优良操作模式库中寻出与当前输入条件距离最小的操作模式,从而完成模式匹配,进而实现喷煤过程优化控制,对高炉冶炼喷煤过程具有很好的指导作用。     

唐钢4~#高炉风口破损原因分析及对策

对唐钢4#高炉近期风口大量破损的原因进行分析,发现风口破损的主要原因是焦炭质量波动、炉缸不活、热制度及造渣制度波动以及送风后慢风时间较长所致。通过提高焦炭质量改善炉缸工作状态、改变出铁制度等措施均可预防休风时的风口大量破损,从而为后续炉况恢复奠定基础。     

2500m~3高炉炉缸活跃实践

新疆八钢A高炉(2500m3)受原燃料条件得限制,炉缸工作状况恶化,炉芯温度持续下降,侧壁温度上升,通过对炉底温度分布的分析,采取适当空吹铁口,三个铁口出铁,炉缸工作得到了改善。     

改进的BP算法在中小型高炉炉温预测上的应用

本研究应用人工神经网络方法对高炉炉温进行预测,确定了三层前向网络结构。针对基于梯度下降法的BP网络存在的学习效率低、收敛速度慢、易陷于局部极小状态、网络的泛化及适应能力较差等缺陷,采用了附加动量法及自适应学习率、合理选择激励函数等策略对算法中的缺陷给出了改进措施,取得了较好的应用效果。     

高炉-转炉区段物流过程解析

通过对高炉一转炉区段物流过程的、提出该区段经历3次大的发展,形成2种典型布局.简要论述了各工序功能;着重阐述了该区段流程布局的变化及工序间衔接、匹配的重要性;总结出流程布局发展的必然性和本质特点。     

Model of Hot Metal Silicon Content in Blast Furnace Based on Principal Component Analysis Application and Partial Least Square

 In blast furnace (BF) iron-making process, the hot metal silicon content was usually used to measure the quality of hot metal and to reflect the thermal state of BF. Principal component analysis (PCA) and partial least-square (PLS) regression methods were used to predict the hot metal silicon content. Under the conditions of BF relatively stable situation, PCA and PLS regression models of hot metal silicon content utilizing data from Baotou Steel No6 BF were established, which provided the accuracy of 884% and 892%. PLS model used less variables and time than principal component analysis model, and it was simple to calculate. It is shown that the model gives good results and is helpful for practical production.     

钢包精炼炉元素收得率的影响因素分析及预报

 不能及时获得收得率影响因素的检测数据是钢包精炼炉元素收得率预报的难点之一。为了解决该问题,首先通过机制分析,在可测变量中选取并创建可以间接表达收得率影响因素的变量,然后将这些变量作为模型的输入,使用支持向量机方法建立元素收得率预报模型。在试验中,将本方法与已有方法进行了比较,比较结果表明本方法所建模型有较高的预报精确度与命中率,更适合于在生产中使用。     

Simulation and Prediction of Alkalinity in Sintering Process Based on Grey Least Squares Support Vector Machine

The prediction of the alkalinity is difficult during the sintering process. Whether or not the level of the alkalinity of sintering process is successful is directly related to the quality of sinter. There is no very good method for predicting the alkalinity by now owing to the high complexity, high nonlinearity, strong coupling, high time delay, and etc. Therefore, a new technique, the grey squares support machine, was introduced. The grey support vector machine model of the alkalinity enabled the development of new equation and algorithm to predict the alkalinity. During modelling, the fluctuation of data sequence was weakened by the grey theory and the support vector machine was capable of processing nonlinear adaptable information, and the grey support vector machine has a combination of those advantages. The results revealed that the alkalinity of sinter could be accurately predicted using this model by reference to small sample and information. The experimental results showed that the grey support vector machine model was effective and practical owing to the advantages of high precision, less samples required, and simple calculation.     

高炉煤气干法除尘技术发展现状及宝钢应用前景

在对高炉煤气干法除尘技术应用现状进行综合分析的基础上结合宝钢实际，提出宝钢应用此技术的相关建议。