论文

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... 

结合工业化生产的无取向硅钢,探讨了氧硫交互作用对钢中夹杂物生成的影响。借助非水溶液电解+扫描电镜法,研究了不同O、S含量下钢中夹杂物的变化规律。结果表明,本实验条件下,提高O含量、降低S含量,会劣化热轧组织再结晶效果。在劣化效果上,O的作用大于S;低Si、无Al硅钢中,应尽可能降低O含量、适当提高S含量,以粗化钢中微细夹杂物,减少尺寸小于1.0μm的夹杂物的数量;O、S含量与钢中夹杂物数量不具有关联性。生产过程中,不仅要严格控制O、S含量,还要严格控制生产工艺,以免生成较多的有害夹杂物。 Based on the industrial production of non-oriented silicon steel,the effects of interaction between oxygen and sulfur on the formation of inclusions were discussed.The change of non-metallic inclusions in steel sheets was investigated by means of electrolysis with non-aqueous solution under different oxygen and sulfur content.Results show that the recrystallization microstructure of hot rolled sheets will be deteriorated with the increase of oxygen content and the decrease of sulfur content.The ... 

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... 

某冷连轧机生产无取向硅钢板材时,其边缘降的长度合格率频繁超标。为满足用户的叠片厚度精度要求,这类产品必须以增大切边量的方式来保证交货质量,而这种方式又直接降低了金属收得率,提高了生产成本。基于此,以该产线现有设备特性为基础,详细分析其软、硬件功能模式,分别对辊形与反馈控制进行全面分析与优化改进。通过现场试验论证,充分明确依托辊形优化与反馈控制程序的改进能显著提高边缘降的控制水平,该技术的使用为生产现场的边缘降控制提供了合理的技术支撑。 A cold rolling mill production of non-oriented silicon steel sheet,the thickness difference of the edge( edge-drop) is usually exceed the preset standard value,In order to meet the accuracy requirements of the user flatness,these production must be trimed wider length to meet the delivery quality of the user need, which directly reduce the metal yield and increase the manufacturing cost. Therefor,the software and hardware of the production line has been analyzed, and the work roll shape and feed... 

对碳-锰-硅钢进行不同配分温度的Q&P(Quenching and Partitioning)处理,测试了热处理后不同钢的力学性能和残余奥氏体含量,并用扫描电子显微镜和透射电镜观察其显微组织,分析了配分温度对显微组织和力学性能的影响。结果表明:试验钢显微组织基本由低碳板条状马氏体、块状铁素体和条状残余奥氏体组成;随配分温度的升高,试验钢的抗拉强度呈下降趋势,伸长率与奥氏体含量的变化趋势相同,但变化规律不确定;提高锰含量能稳定残余奥氏体,从而提高试验钢的伸长率,并使伸长率对配分温度不敏感。 The C-Mn-Si steel was quenched and partitioned at different partitioning temperatures,the mechanical properties and residual austenite contents were investigated,the microstructure was observed by SEM and TEM,and the effect of partitioning temperature on microstructure and mechanical properties was analyzed.The results show that the microstructure of the tested steel consisted of lath martensite with low carbon,nubby ferrite and banded residual austenite.The tensile strength of the tested steel ... 

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... 

聚焦无取向硅钢产品标准,从电磁性能、表面性能、机械性能以及尺寸公差与边部质量等维度对国际标准IEC、EN、JIS、ASTM以及国标GB进行了分析研究。分析得出,各类标准在电磁性能方面要求基本一致;ASTM标准的机械性能要求有别于其他几个标准。 In this paper,non-oriented silicon steel standards of EN,JIS,GB and ASTM were compared and analyzed. It is showed that,all types of standards in electromagnetic performance requirements are basically the same. Surface properties in ASTM standard are expressed in the most detailed. The mechanical properties requirements of the standards,except for ASTM,are basically the same. 

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... 

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 ... 

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... 

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... 

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...