硅钢资料

试验的铸态取向硅钢（/%:0.044⁰.056C,3.12³.32Si,0.08⁰.11Mn,0.002⁰.008S,0.002 9⁰.029 1Als,0.006 2⁰.010 9N）由30 kg高频真空感应炉熔炼。通过场发射扫描电子显微镜/能谱仪（FE-SEM/EDS）研究结果表明,0.002 9%Als钢中氧化物主要为SiO₂,存在片状、棒状及近似球状的独立MnS,未发现含铝的氧化物或氮化物;0.0090%Als钢中出现以Al₂O₃为主的复合氧化夹杂物,存在MnS与AlN的复合析出物。钢中Als增加,复合析出物多呈簇状发展。氧化物容易成为MnS-AlN复合析出的核心,钢中Als含量越低,夹杂物中的MnS含量越高;作为核心的氧化物夹杂的尺寸越小,形成的复合夹杂物的形状越规则,尺寸也越小。热力学计算结果表明,钢中Als含量主要影响了钢中氧化物夹杂的组成和AlN的析出温度及析出量。 Test as-cast grain-oriented silicon steel（/%:0.044 ⁰.056C,3.12 3.32Si,0.08 0.11Mn,0.002⁰.008S,0.002 9⁰.029 1 Als,0.006 2⁰.010 9N） is melted by a 30 kg high frequency vacuum induction furnace.The research results by using field emission-scanning electron microscope/energy dispersive spectrometer（FE-SEM/EDS） show that in 0.002 9%Als steel the main oxide is SiO₂,and there is independent laminable,rod-like and approximate ... 

轧制力是影响冷轧带钢厚度精度的关键因素。为实现高精度的冷轧带钢厚度控制,通过优化变形抗力模型参数和摩擦系数模型参数提高冷轧轧制力模型计算精度,并使用指数平滑法的自学习算法保证轧制力精度的稳定性。在首钢股份公司迁安钢铁公司20辊森基米尔轧机生产线进行S12硅钢钢种轧制力优化试验,将优化的模型参数应用于L2并投入现场生产,结果表明该优化方法不仅提高了轧制力设定精度,而且减小了冷轧硅钢的厚度超差长度,提高了成材率。 The rolling force is the key factor which influences the accuracy of cold-rolling strip thickness. To implement high precision control of cold-rolling strip thickness,we optimize the deformation resistance model parameters and friction coefficient model parameters to improve the calculation precision of cold-rolling force model,and use exponential smoothing self-learn algorithm to ensure the stability of rolling force accuracy. In Shougang Qiangang 20-high Sendzimir mill single stand production ... 

采用RH精炼添加钙合金方式对硅钢进行钙处理。结果表明,钙合金添加量为0.67、1.00、1.67kg/t钢时,钢中钙含量分别为0、2×10-6、4×10-6;随着钙合金添加量增大,钢中夹杂物粒度逐渐由0～2μm向2～4、4～6μm偏移;不同钙处理条件下,钢中均存在粒径小于1μm和粒径为1～5μm的MnS、CuxS夹杂物,后者或单独存在,或同AlN、CaS夹杂复合;粒径为5～10μm区间,钢中的夹杂物基本以钙的氧、硫化物为主。与钙处理前相比,钙合金添加量为0.67、1.00、1.67kg/t钢时,粒径小于1.0μm的微细夹杂物减少幅度分别为68.06%、87.50%、94.94%。钙合金添加量为1.67kg/t钢时,可以去除钢中绝大部分的微细夹杂物。 Ca alloy was added into the liquid steel during RH refining,and the results show that Ca concentration in final Si steel sheets is insignificant,about 0,2×10-6 and 4×10-6 when the added amount of Ca is 0.67,1.00 and 1.67 kg/t steel,respectively.With the increase in the added Ca alloy amount,the inclusions in the steel gradually change from those of 0～2 μm to those of 2～4 and 4～6 μm.Under different Ca treatments,there exist MnS and CuxS inclusions whose size is below 1 μm as well as MnS and CuxS ... 

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 ... 

【摘要】 <正>目前,日本进口硅钢猛增,6月份4181吨,...

采用扫描电镜、场发射扫描电镜、能谱仪等对50SW1300冷轧无取向硅钢中的夹杂物分不同尺寸区间进行数量统计,利用主成分回归分析法,即数据的标准化处理—主成分分析—回归分析—标准化的变量还原成原始变量—确定显著影响因素,综合分析夹杂物总量及各尺寸区间的夹杂物数量对无取向硅钢磁性能的影响。结果表明:主成分回归分析能够从夹杂物尺寸区间及数量的多个影响因素中提取主要的因素,定量研究其对磁性能的影响。分析表明,显著影响无取向硅钢铁损的夹杂物为100~500nm的AlN、AlN+MnS、MnS、Al2O3、AlN+Al2O3,而劣化磁感最明显的夹杂物尺寸区间为100~200nm。 Different size intervals of inclusions in cold rolled non-oriented silicon steel 50SW1300 were counted by scanning electron microscope(SEM),field emission scanning electron microscope(FESEM)and energy disperse spectroscopy(EDS).With principal component regression method:standardization for experimental data,principal component analysis,regression analysis,transform standardized variables into original variables,determination of significant factor,effects of the total number of inclusions and the... 

【摘要】 <正>日前,宝钢自主研发的新型高磁感取向...

研究了冷轧95%变形量无取向硅钢不同退火温度(710～1 050℃)下再结晶织构特征.再结晶刚完成时(710℃退火),呈现强γ({111<112>～<134>)与弱{114}<481>织构特征;随退火温度升高至900℃,γ明显减弱,{114}<481>组分持续增强,形成典型的{h,1,1}<1/h,1,2>织构;进一步升温至1 050℃,再结晶织构不再发生明显变化.基于EBSD分析,{114}<481>组分的持续强化可归因于其明显的尺寸优势以及较高频率的高能晶界(取向差角为20°～45°). A non-oriented silicon steel was heavily rolled to 95% reduction and subsequently annealed at 710~1 050 ℃ to investigate recrystallization texture evolution.When annealed at 710 ℃ with complete recrystallization,the texture is characterized by a strong partial γ fiber spreading from {111}<112> to {111}<134> and a weak {114}<481> component.As annealing at 900 ℃,γ fiber is decreased significantly while {114}<481> is increased consistently,producing a typical {h,1,1}<1/h,... 

采用磁控溅射方法,分别在纯Fe以及低硅钢基片上沉积富Si膜,并对其进行真空扩散热处理.通过能谱分析及X射线衍射研究了Si在纯Fe与低硅钢基体中的扩散特征,运用DICTRA软件建立了扩散模型.研究发现Si在纯Fe基体中扩散时发生γ-Fe(Si)→α-Fe(Si)相转变,扩散速率受控于相界面的迁移.当沿截面Si含量梯度不足以驱动相界面正向迁移时,延长扩散时间会发生相界面回迁现象,最终趋于单一相内均匀化扩散过程.Si在低硅钢基体中的扩散符合Fick扩散第二定律. Si-rich films were deposited on pure iron and low-Si steel substrates by direct current magnetron sputtering,and then were subjected to vacuum annealing.The distribution characteristics of Si across Fe and low-Si steel substrates were studied by energy spectrum analysis(EDS) and X-ray diffraction(XRD).DICTRA software was used to simulate the diffusion models.It is found that the diffusion behavior of Si in the Fe substrate is from γ-Fe(Si) phase to α-Fe(Si) phase and the rate of diffusion is con... 

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... 

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... 

【摘要】 <正>含6.5%Si的电工钢是软磁特性最佳的电...