钢厂
稀土处理无取向硅钢中的夹杂物与电磁性能变化
结合工业化生产的无取向硅钢,进行了RH精炼添加稀土合金实验。结果表明,1.15%(质量分数)Si钢的脱硫反应,主要发生在添加稀土合金之后的前5min。最佳的稀土合金添加量为0.6~0.9kg/t钢。钢液经过稀土处理后,加入的稀土总量越多,稀土氧硫化物夹杂物的尺寸就越大,但热轧带钢再结晶效果会逐渐变差,成品带钢晶粒尺寸先是快速长大,而后逐渐减小。最佳的钢中存留稀土含量与钢的化学成分有关,应严格控制在2.0×10-3%~6.0×10-3%(质量分数)。在此范围内,钢的铁损先是快速降低,而后缓慢升高,钢的磁感应强度则单调降低。 Based on the industrial production of non-oriented electrical steel,rare earth(RE) alloy treatment during the RH refining process was studied.The results showed that the effects of desulfurization and total concentration of RE remained in steel mainly depended on the chemical compositions of different steel grades.For 1.15wt% Si steel grade,the desulfurization reaction mainly focused on the initial 5min after RE alloy added during the RH refining process.The suitable RE alloy addition was 0.6-0....
高硫硅钢的硫化物析出行为及其微观组织和电磁性能变化
为了弄清楚高硫硅钢中的硫化物析出行为及其对钢的微观组织和电磁性能的影响,以便为工业化生产制定更为合理的硫含量控制标准和采取更为有效措施减轻炼钢生产的硫含量控制压力,结合0.25% Si 无取向硅钢 ,采用非水溶液电解提取 + 扫描电镜/透射电镜观察相结合的方法 ,研究了0.006 8%、0.010 2%、0.025 5% 和 0.035 3% 硫含量条件下,钢中的硫化物夹杂物组成和存在形式及其形貌、种类、尺寸、数量变化,以及相应的热轧、成品试样的微观组织和电磁性能变化。结果表明,随着钢中硫含量的增加,钢中的硫化物逐渐由 MnS→MnS+Cu2S→Cu2S转变,数量逐渐增多,尺寸向高低两个方向发展。相应地,导致热轧再结晶组织劣化和抑制了成品晶粒尺寸长大。随着钢中硫含量的增加,钢的磁感、铁损劣化程度逐渐增大。钢中的硫含量平均每增加 0.01%,涡流损耗、磁滞损耗分别劣化0.24 W/kg 和 0.41 W/kg,而磁感会劣化 0.009 T。但是 ,在硫含量为 0.010 2% 时 ,铁损可以低于 6.0W/kg,而在硫含量为 0.025 5% ... In order to find out the precipitation behavior of sulfide inclusions and the corresponding changes of microstructure and electromagnetic properties of high sulfur silicon steel sheets, so that to design more suitable sulfur concentration controlling limit for industrial manufacture and to release the steel-making difficulty effectively, Based on the change of given sulfur concentration 0.006 8%, 0.010 2%0.025 3% and 0.035 3%, the type and composition, the size and number, and the size distribut...
硅钢级氧化镁反应行为的研究
利用DSC、XRD,结合热焓分析对硅钢级氧化镁和二氧化硅的固相反应行为进行了研究。比较了不同二氧化硅原料及混合方法对硅钢级氧化镁反应性的影响,找到了一种更为有效的硅钢级氧化镁反应性的评估方法,克服了传统柠檬酸活性法在比较不同厂家生产的氧化镁的反应性上的局限性。进一步研究了Na2B4O7添加剂、TiO2添加剂对氧化镁和二氧化硅反应行为的影响,结果表明,Na2B4O7添加剂含量的增加对反应有利,而TiO2添加剂对反应有阻碍作用。 The solid-state reaction behavior between silicon-steel grade MgO and SiO2 was investigated by DSC and XRD combined with enthalpimetric analysis.The influence of different kinds of SiO2 and different preparation methods were studied and a specifical measurement that is more reliable was proposed to evaluate reactivity of silicon steel grade MgO.It overcomes the limitation of the traditional citric acid activity(CAA) method,which can not be used to evaluate the reactivity of...
硅钢常化退火炉辊印缺陷预测分类预警方法研究
针对宝钢硅钢常化退火过程中产生的退火炉辊印缺陷问题,通过实际生产的大数据与产品质量问题相结合,将数据挖掘、数据分析方法应用到实际,一定程度上解决了现场实际生产中的痛点,为现场生产提供决策支撑,避免了以前通过人工识别判定存在疏漏和无法定量判断的问题,形成了一套具有鲁棒性和可操作性的钢铁生产过程数据分析方法。通过智慧决策系统平台获取实际生产和表检仪数据,基于Pearson相关系数算法进行变量挑选和特征工程,并应用随机森林算法对数据建立分类预测模型,实现了质量问题的溯源和监控,通过数据量化预测了炉辊印缺陷是否可通过轧制消除的质量问题,识别准确率达到96.43%。 In views of the normalizing annealing furnace roll marks problem occurred in the process of normalizing annealing of silicon steel in Baosteel,by combining big data from actual production with product quality problems,data mining and data analysis methods were applied to actual production to solve the pain points and provide decision support,a robust and practical data analysis method for the steel production process has been developed,which avoided the previous problems of omission and non-quan...
RH精炼喂CaSi线去除无取向硅钢中的非金属夹杂物
结合工业化生产的无取向硅钢,进行了RH精炼喂CaSi线去除钢中的非金属夹杂物试验研究。针对不同的钙处理条件,分析了CaS夹杂生成热力学,观察了夹杂物的形貌和尺寸分布,确定了夹杂物的类型、数量,探讨了钙处理后钢中夹杂物的变化规律。结果表明,本试验条件下,钙处理可以有效抑制MnS、AlN夹杂物的生成,有效促进钢中微细夹杂物的聚合、上浮、去除,钢质纯净度明显提高。经过合适的钙处理后,钢中的夹杂物以独立存在的CaO为主,同时有少量含CaO、SiO2、MgO的复合夹杂,没有发现CaS夹杂存在。这部分夹杂物的尺寸集中分布在2~20μm,数量约为1.8×105个/mm3。 Experimental study on removal of non-metallic inclusions in non-oriented silicon steel obtained from industrial production by CaSi wire feeding during RH refining process was carried out.The thermodynamics of CaS inclusion formation was analyzed,the morphology and the size distribution of inclusions were observed,and the numbers and types of inclusions were also determined for the steel specimens treated under different calcium treatment conditions.Furthermore,the variation of inclusion characte...
大数据技术在硅钢产品质量管控中的应用实践
磁性能指标是硅钢产品最关键的质量指标之一,但是目前磁性能判定100%依赖于样品的离线实验室检测结果,生产线配置的在线检测仪的测量结果由于精度问题,不宜直接用于成品牌号判级。本文在现有硅钢产品质量管控体系基础上,利用大数据技术对生产数据进行分析与建模,构建不同磁性能指标在线检测模型,并在现有信息系统上完成模型库的集成部署,实现硅钢产品全长、多指标磁性能结果的拟合数据输出,支撑取样优化、精准分切、辅助综合判定等功能应用,进一步优化硅钢产品质量管控体系。 The magnetic performance index of silicon steel products is one of the most critical quality indexes.However,at present,100%determination of magnetic performance depends on the offline laboratory test results of samples,and the measurement results of the online detector configured in the production line cannot be applied in practice due to the accuracy problem.Based on the existing quality control system of silicon steel products,big data technology was used to analyze and model the production d...
国内外中低牌号无取向硅钢夹杂物控制效果解析
选用国内外无取向硅钢标杆企业A、B、C的产品,采用非水溶液电解提取+SEM(EDS)方法,分析了其典型牌号对应成品试样中的夹杂物。结果表明,从磁性能控制角度而言,受钢的化学成分及生产工艺影响,A、B、C企业成品试样的夹杂物尺寸、种类、数量存在差异,这些差异对其磁性能产生显著影响;从夹杂物控制角度而言,A、B、C企业对应成品试样的夹杂物,以MnS、CuxS复合或者AlN、MnS、CuxS复合为主,其中1.0μm以下的夹杂物数量分别为2.34×107个/mm3、2.98×107个/mm3和11.98×107个/mm3,1.0μm以上夹杂物数量均很少,夹杂物的平均尺寸从大到小依次为A企业、B企业、C企业。 According to the production of three benchmarking manufacture enterprises A,B and C of non-oriented silicon steel at home and abroad,the inclusions in finished steel samples with typical grades were investigated by electrolytic extraction from non-aqueous solution and SEM(EDS).Results show that,from the viewpoint of improving the magnetic properties,affected by chemical composition and production technique,the size,type and amount of inclusions in finished steel samples are various,which will af...
钙处理对无取向硅钢中非金属夹杂物的影响
采用电解法和扫描电镜研究了300 t转炉-RH精炼钙处理对无取向硅钢板(%:≤0.005C、1.2~2.2Si、0.2~0.6Mn、≤0.20P、≤0.005S、0.2~0.6Al、0~0.01Ca)中夹杂物的影响。结果表明,钢中Al含量为0.25%和0.35%时,钢中溶解氧均小于1×10-4%,钙处理后都会产生CaS夹杂物,尤其是含0.35%Al的钢水;钙处理可以有效减少钢中的夹杂物数量,尤其是0.5μm以下的微细夹杂物数量;钙处理后夹杂物的种类以AlN、CaS为主,同时还含有少量的氧化物夹杂物以及AlN-CaS复合夹杂物,尺寸主要为1.5~5.0μm。 The effect of 300 t converter-RH refining calcium treatment on inclusions in non-oriented silicon steel sheet (%:≤0.005C,1.2~2.2Si,0.2~0.6Mn,≤0.20P,≤0.005S,0.2~0.6A1,0~0.01Ca) has been studied by electrolysis and scanning electron microscope.Results show that with 0.25%and 0.35%Al content in steel,all the dissolved oxygen in liquid is less than 1×10-4%,and the CaS inclusions are produced after calcium treatment,especial for the liquid containing 0.35%Al;the amount of inclusions in ste...
无取向硅钢冶炼过程中的夹杂物遗传变化
研究表明,硅钢中的夹杂物对成品带钢的磁性能有显著影响。为研究冶炼过程硅钢中的夹杂物遗传变化,进而提出更有效的控制措施加以去除,本文结合典型的无取向硅钢生产炉次,采用非水溶液电解提取+扫描电镜观察方法分析冶炼过程中上述炉次典型试样的夹杂物。结果表明:转炉冶炼结束、RH精炼开始时,钢的氧化物夹杂总量最大,约为0.23%;RH精炼过程中,氧化物夹杂总量不断降低,并在脱碳结束时达到最低,约为0.02%;连铸过程中,氧化物夹杂总量仍有不断降低趋势,但夹杂物的平均尺寸变化不大。本试验条件下,中间包试样的夹杂物数量约为1.59×104个/mm3。 As we all know, the non-metallic inclusion effects magnetic properties of silicon steel sheets obviously. The article aims to study the heredity of non-metallic inclusion in non-oriented silicon steels during the steel making process, and then provides a more effective controlling measure to remove the inclusions. Based on the typical non-oriented silicon steel charges, the non-aqueous solution extraction and SEM observation were adopted to analyze the non-metallic inclusions. Results show that,...
云边一体化系统架构下硅钢制造管理业务数字化融合应用
提出以“云边一体化架构”构建硅钢智慧决策系统,来解决原硅钢制造L1~L5系统架构模式下的数字信息孤岛、业务功能割裂等问题。在此基础上,开发了云边协同的自学习型控制模型及业务决策模型,构建起硅钢“智慧大脑”,形成了以研发、制造、服务等核心业务数字化融合的智能化决策支持新模式,探索出一条钢铁制造业数字化、智能化转型之路。 SIDS(Silicon-steel Intelligent Decision-making System)based on \"cloud-edge integration architecture\" was proposed to solve the problems of data silos and business function fragmentation in the original L1~L5 system architecture.On this basis,the self-learning control model and decision-making model of cloud-edge collaboration were developed,the \"smart brain\" of silicon steel department was constructed,and a new intelligent decision-making support model of digital integration of core businesses s...
硅钢铸坯再加热过程中夹杂物的析出行为
研究了硅钢铸坯再加热过程中夹杂物的析出行为。采用非水溶液电解提取+扫描电镜观察方法,观察了试样的显微组织,统计了夹杂物的尺寸、种类、数量、分布。结果表明,均热温度为1 523 K时,水淬试样的夹杂物尺寸绝大部分小于0.5μm,0.5~5.0μm的夹杂物数量很少,没有发现5.0μm以上的夹杂物。此外,均热时间为10、30、60、90、120、240 min时,对应试样中0.05~0.2μm的夹杂物数量分别为4.04×104、4.73×104、3.70×104、3.33×104、3.10×104、1.56×104个/mm3。绝大部分夹杂物以MnS、AlN、CuxS类为主,并以三类夹杂物中的两类复合或三类复合居多。三类复合夹杂物总量占每组试样夹杂物总量的90%或以上。随均热时间延长,典型的夹杂物组成会发生如下变化:MnS+AlN+CuxS MnS+AlN AlN。与此同时,MnS、AlN、CuxS三者复合比例从45.2%(均热10 min)降为9.7%(均热240 min)。 The methods of electrolysis extraction from nonaqueous solution and scanning electron microscope were adopted to study the precipitation behavior of non-metallic inclusions in Si steel slabs during reheating processes.The morphologies,chemical compositions,quantity and size distribution of non-metallic inclusions in these steel samples were analyzed.Results show that,when the soaking temperature is 1 523 K,almost all of the non-metallic inclusions are smaller than 0.5 μm,few are in the range of ...
不同牌号无取向硅钢夹杂物定性定量分析
无取向硅钢中夹杂物的存在会抑止晶粒生长,使基体的均匀连续性中断,其在钢中的形态、含量及分布情况都不同程度影响着硅钢的性能,尤其是对磁性能起关键的作用。因此,全尺度分布考察夹杂物对无取向硅钢夹杂物的研究极为重要。本实验确定了适用于不同牌号无取向硅钢夹杂物全尺度分布的分析方法:样品制备—小样电解—过滤喷金—根据不同牌号的要求选择合适的放大倍率扫描观测—夹杂物颗粒的分类统计。通过统计的结果,结合电解的失重量可以得到不同尺度的体积分布数据。实验分析了不同牌号和工艺无取向硅钢夹杂物的种类、形貌、大小和尺度分布,并初步考查了夹杂物与磁性能的关系,对无取向硅钢的工艺研究具有一定参考价值。 Inclusions in non-oriented silica steel could inhibit the growth of grain and cause discontinuity of micro-structure.The configuration,content and size distribution of inclusion have different effects on the performance of silica steel,especially significant on the magnetic property.Therefore,it is very useful to completely characterize inclusions with full size distribution in silica steel.In our research,full size analysis method for inclusion in silica steel had been established as follows: s...

