硅钢资料

研究了热处理工艺(退火温度、保温时间、冷却方式)对含Mn的Fe-6.5wt%Si高硅钢热轧带的显微组织及硬度的影响。结果表明,退火温度对Fe-6.5wt%Si合金的组织和显微硬度均有较大影响,随退火温度升高,平均晶粒尺寸和显微硬度均明显增大。小于1 h退火时,晶粒长大缓慢,而长时间(>1 h)退火时,一些次表层晶粒将发生异常长大。水冷组织比空冷组织略细小,但水冷显著降低了显微硬度。Mn含量提高能抑制850℃退火时晶粒的长大,并且促进退火后高硅钢的软化。 The influences of heat treatment process(annealing temperature,heating time,cooling methods) on the microstructure and microhardness of Fe-6.5wt%Si high silicon steel containing manganese for hot rolled strip were studied.The results show that the annealing temperature has a great effect on the microstructure and microhardness of Fe-6.5wt%Si alloy,and as the annealing temperature increases,the average grain sizes and microhardness will significantly increase.When annealing time for less than 1 h... 

 

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... 

一种基于大数据分析技术的电工钢用户选材询单推荐方法，于终端计算机内、以可与终端计算机各数据库进行信息交互的形式、设置一计算模块；经此计算模块完成依次的基于各数据库的有效信息的采集、用户询单选材推荐方案模型的设置、基于有效信息及推荐方案模型完成推荐牌号的生成，根据设定的评估模型对生成的推荐牌号及信息评估运算的运行，据此建立对用户的选材询单推荐。本发明的一种基于大数据分析技术的电工钢用户选材询单推荐方法，基于L4计算机系统开发出的计算模块及相应的可与计算模块进行信息交互的用户界面完成，形成可根据不同用户需求对应的不同评价体系，完成与不同用户需求适配的方案推荐。

结合工业化生产的50A1300牌号无取向硅钢,分析了化学成分、RH精炼脱氧方式、板坯装炉温度以及热轧平整工艺等对磁性能的影响,探讨成品钢磁性能的改善。结果表明,采取改善后,50A1300牌号无取向硅钢的磁性能得到明显改善。2012年,该钢种平均铁损、磁感应强度分别达到5.26 W/kg、1.762 T,能够较好地满足用户市场需求及同行对标需要。 Based on the industrial manufacture of 50A1300 grade non-oriented silicon steel sheets,effects of chemical composition,deoxidization method in RH vacuum refining,charging temperature of steel slabs,hot rolling and flattening progress on magnetic properties are analyzed.The optimization methods of magnetic properties of steels are discussed. Results show that the magnetic properties are obviously improved by the adopted measures above. In 2012,the average core loss and the magnetic induction of 5... 

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... 

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... 

【机构】 宝山钢铁股份有限公司规划与科技部； ...

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... 

结合工业化生产的高效硅钢,进行了RH精炼稀土处理试验研究。针对不同的稀土处理条件,观察了夹杂物的形貌和尺寸分布,探讨了稀土处理后钢中的夹杂物形成、变化规律。结果表明:试验条件下,最佳的稀土合金添加数量为0.6～0.9 kg/t。经过合适的稀土处理后,可以有效抑制尺寸相对较小的、不规则的AlN、MnS复合夹杂生成,促进钢中微细夹杂物的聚合、上浮,钢质纯净度得到明显提高。此时,钢中全氧含量最低,脱硫效果最佳,钢中的夹杂物主要是尺寸相对较大的、近似球形或者椭球形的稀土类夹杂。 Based on the industrial production of non-oriented silicon steel,the experiment on RE treatment during the RH refining process was studied.The morphology and the size distribution were observed for the steel specimens treated with different RE treatment conditions.Further more,the formation and change of inclusions of final steel sheets after RE treatment were discussed.The results show that the suitable RE added amount was 0.6～0.9 kg/t.After the suitable RE treatment,the formation of AlN and Mn... 

借助高温激光共聚焦显微镜,在线观察了不同Mn含量的无取向硅钢中夹杂物的尺寸、类型、数量变化。结果表明,Mn含量(质量分数)为0.77%、0.32%时,试样中的夹杂物数量分别约为1000万个/mm3、1600万个/mm3。Mn含量较高的钢种,会优先析出球形、椭球形MnS夹杂物,其析出数量较少,尺寸相对较大,可以有效抑制AlN、CuxS夹杂物析出;Mn含量较低的钢种,会在试样再加热后冷却过程中,先析出相当数量MnS夹杂物,并作为AlN夹杂物析出核心,形成MnS+AlN复合夹杂物。这种复合夹杂物数量较多,尺寸也较大。 Based on the high temperature confocal microscope, the chage of size, type, and quantity of inclusions in non-oriented silicon steels with different Mn content were observed by in-situ SEM. Results show that the inclusion quantities are 10 million per mm3 and 16 million per mm3,while the mass fractions of Mn are 0.77% and 0.32%, respectively. In the silicon steel with higher Mn content, the spherical and ellipsoidal MnS inclusion will precipitate first, which can retard the precipitation of AlN ... 

本发明公开了一种取向硅钢产品的在线性能判级与精确分切装置和方法，使得同一个分卷上的性能分布均匀，避免分卷出现性能废品或多个性能等级的情况，提高分卷性能稳定性。提供的一种取向硅钢产品的在线性能判级与精准分切方法包括生产数据采集、铁损曲线自学习、数据存储、性能在线判级、缺陷数据采集、缺陷判级、智能分切等模块，依据修正后的磁性能全长数据，得到产品的性能判级结果，结合表面缺陷判级结果，综合确定分切位置，制定最佳分切方案。本发明可以实现取向硅钢生产过程中的性能在线判级和精准分切，得到性能均匀、表面质量好的分卷，减少分卷性能不稳定带来的损失。