Development of an improved CBR model for predicting steel temperature in ladle furnace refining

In the prediction of the end-point molten steel temperature of the ladle furnace, the influence of some factors is nonlinear. The prediction accuracy will be affected by directly inputting these nonlinear factors into the data-driven model. To solve this problem, an improved case-based reasoning model based on heat transfer calculation(CBR-HTC) was established through the nonlinear processing of these factors with software Ansys. The results showed that the CBR-HTC model improves the prediction accuracy of end-point molten steel temperature by5.33% and 7.00% compared with the original CBR model and 6.66% and 5.33% compared with the back propagation neural network(BPNN)model in the ranges of [-3, 3] and [-7, 7], respectively. It was found that the mean absolute error(MAE) and root-mean-square error(RMSE)values of the CBR-HTC model are also lower. It was verified that the prediction accuracy of the data-driven model can be improved by combining the mechanism model with the data-driven model.

Improvement of Service Life of Small Furnace Covers on 150 t Refining Ladles

The factors restricting the life of the refining furnace cover were introduced,including the airflow erosion of the refining dust removal system,the melting loss caused by the arc radiation of the electrode,the chemical erosion and penetration of slag and gas,and the condition of refining slag.The improvement measures are adjusting the material of the small furnace cover from corundum to chrome corundum,using a large shaking table to vibrate,optimizing the size design of the small furnace cover,and appropriately thickening the weak areas in the triangular area.The average service life of the refining furnace cover has been increased from one week to two months,reaching 4 maintenance cycles,which meets the needs of the refining production.

Explainable machine learning model for predicting molten steel temperature in the LF refining process

Accurate prediction of molten steel temperature in the ladle furnace(LF)refining process has an important influence on the quality of molten steel and the control of steelmaking cost.Extensive research on establishing models to predict molten steel temperature has been conducted.However,most researchers focus solely on improving the accuracy of the model,neglecting its explainability.The present study aims to develop a high-precision and explainable model with improved reliability and transparency.The eXtreme gradient boosting(XGBoost)and light gradient boosting machine(LGBM)were utilized,along with bayesian optimization and grey wolf optimiz-ation(GWO),to establish the prediction model.Different performance evaluation metrics and graphical representations were applied to compare the optimal XGBoost and LGBM models obtained through varying hyperparameter optimization methods with the other models.The findings indicated that the GWO-LGBM model outperformed other methods in predicting molten steel temperature,with a high pre-diction accuracy of 89.35%within the error range of±5°C.The model’s learning/decision process was revealed,and the influence degree of different variables on the molten steel temperature was clarified using the tree structure visualization and SHapley Additive exPlana-tions(SHAP)analysis.Consequently,the explainability of the optimal GWO-LGBM model was enhanced,providing reliable support for prediction results.

Steady State Heat Transfer of Ladle Furnace During Steel Production Process

The heat transfer analysis was performed for an industrial ladle furnace （LF） with a capacity of 55-57 t in Turkey. The heat losses by conduction, convection and radiation from outer and bottom surfaces, top and electrodes of LF were determined in detail. Finally, some suggestions about decreasing heat losses were presented.

Rational argon stirring for a 150-t ladle furnace

Based on the principle of similarity, water modeling experiments were carried out for a 150-t ladle furnace. The rational parameters of argon stirring were determined as the optimized positions of nozzles, top area of the porous brick, and gas flow rate. The following results are obtained： 1） the optimized positions of two nozzles are at 0.333R （R refers to the radius of the ladle at bottom） with an angle of 135°; 2） the top diameter of the porous brick should be 130 mm; 3） the flow rate of gas should be 25.0-30.6 m^3/h. The plant trial shows that the improved process is effective in enhancing the cleanliness of round billets. The total oxygen content, microinclusions, and macroinclusions in round billets are reduced by 12.5%, 8.2%, and 20%, respectively.

Improvement of the Structure and the Electromagnetic Characteristics of an Induction Ladle Furnace

Based on a numerical analysis of the alternating electromagnetic field in the process of Steel refining with an induction ladle furnace (ILF), the optimization of the structure of ILF and the electromagnetic field for melting is realized in the present work. The optimization of the ILF by outward extension of inner yokes can decrease the magnitic flux leakage obviously, reduce the eddy current energy loss dramatically and then, decrease the total power consumption.

Direct Current Electric Arc-Electroslag Ladle Furnace

In order to solve the high consumption problem of small capacity ladle furnace (LF), the operation principle and control method of the DC are and electroslag heating ladle furnace are introduced. With only one arcing electrode, the distance between the are and the wall of ladle is enlarged, and consequently the consumption of the ladle refractory is decreased. In the invention, a signal electrode is embedded in the refractory lining of the ladle, which contacts directly with the liquid steel and the ladle shell. Two graphite anode ends are submerged in the slag layer. The signal electrode is used as voltage reference during refining process. The electroslag voltage between anode end and liquid steel is applied to control the depth of anode end in the slag layer during the refining process with this ladle furnace.

LF精炼炉废钢自动加料系统工程实践

基于对废钢资源高效利用的目的,介绍了某企业开发的LF精炼炉废钢自动上料系统项目,分析了在LF精炼炉添加优质废钢的优势,主要包括可以高效利用废钢资源中的合金元素降低生产成本,提高经济效益;LF精炼炉添加废钢可以调整LF炉钢水重量来稳定连铸生产节奏;同时,对废钢上料系统设备进行了介绍,对钢铁企业开发LF精炼炉高废钢比加料项目提供了一定的参考价值。

Multifunctional Refractory-lined Vessel: Ladle Aggregate

A ladle primarily is a container used to transport molten steel from the steelmaking unit to the casting facility.The essential requirements are heat resistant,insulative and strong enough to hold molten steel up to 300 t,with a structure of multilayered refractory lining in a steel shell vessel.When a ladle is assembled with three-phase graphite electrodes,a ladle furnace forms,starting steel refining process with/without the vacuum tank degasser and RH circulating degasser,in order to meet the growing demand on high purity and higher quality steel.The working lining is under aggressive conditions that comprise the chemical reaction with molten steel,the severe corrosion of liquid slag,the disaggregation through oxidation,and the strong stress due to the impacting of the melts and gases and the effects of thermomechanical behaviors.Magnesiacarbon brick is one of the major materials,being indispensable for the slagline of a ladle furnace.Alumina-magnesiacarbon brick has played an important role to substantially increase the service life in the metal zone,from the early lining materials of high alumina and doloma bricks.The permanent lining must assume sufficient responsibility to allow finishing the process of the engaged charge in case of a failure in the working lining.The insulation layer must be as thin as possible in order to maximize the ladle’s capacity,and reduce the shell temperature for saving energy.In this issue,several integrant refractories are reviewed or investigated in order to compile a lining overview,and to contribute a prolonged service life under aggressive working conditions of the ladle furnace.

LF精炼炉钢包回转台驱动系统设计与分析

LF炉是整个钢铁精炼工艺过程中最为重要的设备,具有脱硫、脱氧,微调钢水成分的作用,对提高钢水品质具有重要作用;是每个钢企生产优钢特钢的必备设备。现有LF精炼炉主要结构型式分为双车式、回转台式以及电极旋转式。回转台式LF炉其特点是利用回转台的自转将钢水从等待工位转运钢水至冶炼工位进行冶炼;回转台式LF炉具有占地面积小,使用安全可靠,维护保养工作量小,效率高等优势。回转台作为LF精炼炉的重要组成设备,对整个精炼炉安全运行有着重要的作用;而回转台的平稳运行又取决于驱动装置设计的可靠性。针对回转台的驱动装置设计进行分析。通过对回转台驱动系统基础数据的计算、电机和减速机的选型,提出一个安全、可靠的设计方案,以便其他设计者进行参考。

LF精炼钢水温度预测模型的开发与应用

针对LF工序终点钢水温度预测的问题,基于XGBoost算法建立了LF精炼钢水温度预测模型。在温度预测模型的离线测试阶段,模型在温度误差±5℃、±10℃时的命中率分别为79.8%、98.5%;模型上线运行一段时间后,统计了某段内的180炉数据,得到模型在温度误差±5℃、±10℃时的命中率分别为86.6%、97.8%。该温度预测模型满足钢厂的实际使用需求。

LF钢包用耐火材料的研究进展

随着钢铁产业飞速进步,对钢材品质也有了越来越严苛的要求,钢包从简单的钢水盛装容器转变为具有冶炼功能的多元容器。LF精炼以其设备结构简单、冶金功能丰富及经济效益好等优点,成为冶金过程中不可或缺的环节。钢水、渣及耐火材料三者在整个冶炼过程中是相互作用的。在LF钢包的钢包盖、渣线、包壁、透气砖等位置均需要用到耐火材料。其中渣线位置由于受到的侵蚀最为严重,而且经受了剧烈的温差波动,最常用的耐火材料为MgO-C耐火材料。文章对LF钢包精炼工艺进行了简介,概括了LF钢包各部位对耐火材料的要求和目前使用的耐火材料种类。

LF炉外精炼工艺的优化试验

为去除炉外精炼过程中的有害杂质,提高钢液纯净度以及钢材的质量,提出一种LF炉外精炼工艺优化方案。以某钢厂为研究背景,对钢材生产进行工艺性试验和分析,通过对轴承钢和高档齿轮钢LF炉外精炼工艺的研究,确定适宜的工艺参数,根据成品钢中酸溶铝质量分数为0.020%~0.025%的要求来控制VD炉后喂铝量,以全氧质量分布和轴承钢夹杂物为评价指标,对改进前后的工艺方案进行比较分析,验证了LF炉外精炼优化工艺综合应用效果更优,对钢冶炼技术的改进具有指导意义。

LF精炼炉提高供电效率的研究与实践

根据LF精炼炉不同生产阶段炉渣泡沫化特点,优化精炼辅料和发泡剂的使用,系统研究LF精炼炉供电的电气特性,得出最佳供电功率的供电曲线,实现LF精炼炉动态的低耗高效供电工艺,供电效率提升5.66%,升温效果达到3.92℃/min以上,减少了给电对LF炉电极设备的冲击损坏。

LF精炼过程中硫分配比和脱硫动力学方程研究

通过 ＬＦ精炼脱硫工业实验，确定了在不同条件下熔渣和钢水中的实际硫分配比．在二元碱度较高时，大部分实验数据与经验公式计算值相差近 ２－４倍 此外，用反应平衡计算的值要比实验数据大许多.在本实验条件下，脱硫速率和时间之间有较好的线性关系，脱硫传质系数为 ２．６７×１０－３ｃｍ／ｍｉｎ．该结果为ＬＦ炉生产中脱硫提供了必要的依据.

LF炉合成精炼渣成分优化

通过建立二次回归正交设计模型，考察了合成精炼渣碱度伽（CaO）／w（SiO2），Al2O3和CRF2质量分数对LF深脱硫效果的影响．结果表明，当渣中w（FeO）为0．5％，w（MgO）为9％时，随渣中w（CaO）／w（SiO2）增加，脱硫率均先增大后减小．当伽（CaO）／w（SiO2）不同时，Al2O3和C＆F2质量分数对脱硫效果的影响程度不同，主要原因是渣中有效CaO含量变化引起的．随渣中w（FeO）降低和渣量增加，脱硫率明显增大．实验优化的最佳脱硫渣系组成为w（CaO）／w（Si02）=9-11，w（Al2O3）=27％～29％，w（MgO）=9％，w（CaF2）=8％～10％，w（FeO）小于0．5％．

LF炉精炼过程钢水温度预报技术

基于LF炉精炼过程 ,以钢水和炉渣为研究体系 ,通过对其能量收入和损失的系统分析与计算 ,利用热平衡规律 ,详细推导并建立了钢水升温速率模型·其中钢包包壁的传热机制 (包括包侧壁和包底 )分别采用圆柱坐标下和直角坐标下的一维非稳态导热微分方程及其初始条件和第三类边界条件来描述 ,以有限差分方法求解·编制成计算机程序对实际过程模拟仿真·仿真结果与实际值的误差均在±

宝钢300tLF渣精炼技术的开发与应用

对 L F合成渣脱硫、脱氧技术理论和埋弧精炼基本方法进行了分析。介绍了宝钢 30 0 t L F脱硫合成渣、脱氧合成渣和埋弧精炼技术的开发过程及应用效果。采用所开发的上述技术 ,能够批量生产 [S]≤ 10× 10 - 6的超低硫钢和 T [O]≤ 15× 10 - 6的低氧钢 ,并实现了 L F全程埋弧精炼。

铝镇静钢LF精炼过程中夹杂物行为研究

通过对LF精炼开始3 min、通电化渣和钙处理后3个阶段的钢水进行取样,对夹杂物的数量、形态及成分进行对比分析,来研究铝镇静钢中夹杂物在精炼过程中的变化及钙处理对夹杂物性质的影响。结果表明:钙处理在提高钢水洁净度、夹杂物改性等方面效果显著。当LF炉通电化渣后,夹杂物球化率显著提高;钙处理后,球化率进一步提高。LF精炼开始3 min后,钢中的夹杂物以Al2O3-SiO2-MnO和纯Al2O3夹杂物为主;通电化渣后,钢中夹杂物以Al2O3-CaO(CaS)-SiO2为主;钙处理后,钢中央杂物以Al2O3-CaO为主。

高碱度LF合成精炼渣泡沫化性能研究

在实验室条件下采用钼丝挂渣法测量熔渣发泡高度,以相对发泡高度作为衡量指标,结合理论分析,系统研究了高碱度合成精炼渣的泡沫化性能.结果表明:熔渣相对发泡高度随着黏度的增大、表面张力和密度的减小而增大.在精炼渣成分一定时,随温度升高和吹气量增加,熔渣相对发泡高度都有先增加后降低的趋势.具有较好泡沫化性能的精炼渣组成范围是:ω(CaO)/ω(SiO_2)为5～8,ω(Al_2O_3):27%,ω(CaF_2)为3%～6%,ω(MgO)=8%,ω(FeO)<0.5%.