硅钢资料

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... 

【作者】 吴玉美； 陆晔； ...

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... 

研究了取向硅钢制备过程中常见的两种冷轧工艺,主要研究了一阶段冷轧与两阶段冷轧+中间退火工艺对初次再结晶组织及织构的影响.结果表明:采用两阶段冷轧+中间退火工艺制备以Cu2S为主抑制剂的取向硅钢,其初次再结晶平均晶粒尺寸为18.1μm,高斯晶粒的体积分数为0.6%,迁移性强的重位点阵晶界(Σ5+Σ9)和高能晶界(20°~45°取向偏差角)所占比例分别为1.8%和50.4%.与一阶段冷轧工艺相比,其初次再结晶晶粒较细,且高斯晶核与特征晶界所占的比例较高,有利于高斯晶粒发生二次再结晶. Two common cold-rolling processes of grain oriented silicon steel and the effects of the single stage cold rolling and tw o-stage cold rolling w ith intermediate annealing processes on the primary recrystallization microstructure and texture w ere investigated. The results revealed that for the grain oriented silicon steel prepared under the tw o-stage cold rolling process w ith intermediate annealing w ith Cu 2 S as the main inhibitor,the average grain size of the primary recrystallization micr... 

研究的两种取向硅钢（%:No1-0.042C、3.16Si、0.009Al、0.07Mn、0.50Cu、0.015S、0.0084N和No2-0.040C、3.20Si、0.014Al、0.22Mn、0.49Cu、0.016S、0.008 2N）由50 kg真空感应炉冶炼,锻成（mm）350×120×35板坯,经1 250℃30 min加热,开轧温度1 100℃,5道次热轧成2.3 mm板,终轧温度950～1 000℃。实验结果表明,两热轧板沿板厚方向存在组织和织构的不均匀性,热轧板次表层为再结晶组织,有较强的Goss织构组分;中心层为形变组织,具有典型的形变织构。含0.22%Mn的No2钢次表层{110}〈001〉织构组分比含0.07%Mn的No1钢弱,中心层{001}〈110〉织构组分大大强于0.07%Mn No1钢,导致两者磁性能差异,0.22%Mn No2钢磁感应强度(B₈₀₀)和铁损(P_1.7/50)分别为1.87 T和1.24 W/kg,0.07%Mn No1钢分别为1.88 T和1.18 W/kg。 Studied both grain-oriented silicon steels（%:No1- 0.042C,3.16Si,0.009Al,0.07Mn,0.50Cu, 0.015S,0.0084N and No2-0.040C,3.20Si,0.014Al,0.22Mn,0.49Cu,0.016S,0.0082N） are melted by a 50 kg vacuum induction furnace,forged to（mm） 350×120×35 slab,heated at 1 250℃for 30 min,with beginning rolling temperature 1 100℃hot-rolled to 2.3 mm plate by 5 passes,finishing-rolled at 950～1000℃.Test results show that the structure and texture along thickness of both hot-rolled plates are inhomogeneous:the subsurface ... 

利用XRD和EBSD研究了长轴分别平行于轧向(RD)、横向(TD)和轧面法向(ND)的柱状晶样品在热轧、冷轧及退火过程中的组织、织构演变规律,并分别从几何诱导和取向诱导两个方面分析了晶界的交互作用.结果表明,热轧时由表面摩擦剪切作用引起的组织和织构梯度直接影响并遗传给后续冷轧及退火样品.热轧后,不同样品的初始晶粒形状各向异性差异消失,形成相同的各向异性晶界组织,但晶体学各向异性发生改变,导致随后冷轧、退火组织及织构的变化均不同于直接冷轧的柱状晶样品.研究中特别关注了对磁性能有利的{100}取向区域与晶界的关系. Columnar grains show their special characteristics of morphological and crystallographic anisotropies, and thus markedly influence the microstructure and texture evolution during rolling and annealing process in electrical steel. The rolling and annealing microstructure and texture of three columnar grained samples with the long axes arranged along different directions were investigated by means of XRD and EBSD techniques, and the effects of columnar grain boundaries were analyzed from the view ... 

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... 

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和1.67 kg/t钢时,钢中Ca含量分别为0、2×10-6和4×10-(6质量分数);随着钙合金添加量的增加,钢中夹杂物粒度逐渐由0～2μm向2～4μm、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,或与AlN、CaS夹杂复合;钢中粒径为5～10μm的夹杂物基本以Ca的氧化物和硫化物为主。与未经钙处理的炉次相比,钙合金添加量为0.67、1.00和1.67 kg/t钢时,粒径小于1.0μm的夹杂物减少幅度分别为68.06%、87.50%和94.94%。钙合金添加量为1.67 kg/t钢时,可以去除钢中绝大部分的微细夹杂物。 In order to improve the properties of final silicon steels,the calcium treatment was adopted by adding Ca alloys into the liquid steel during the RH refining process.Results show that when the addition of Ca alloys is 0.67 kg/t,1.00 kg/t and 1.67 kg/t,the corresponding Ca content in silicon steels is 0,2 × 10-6 and 4 × 10-6 respectively.With the increase of Ca alloy addition,the particle sizes of inclusions in steels become 2～4 μm and 4～6 μm,from 0～2 μm.Under different calcium treatments,there e... 

对低温加热工艺生产的以AlN为主抑制剂的高磁感取向硅钢高温退火过程进行中断实验,借助电子背散射衍射技术对高温退火过程中高斯晶粒的演变进行了研究.在升温过程中高斯晶粒平均尺寸先减小再增大.800℃时取向分布函数图出现高斯织构组分,但强度很弱,高斯晶粒偏离角在10°以上;900℃时高斯晶粒平均生长速率超过其他晶粒;950~1000℃时高斯晶粒异常长大,偏离角3°~6°;在1000℃之前高斯取向晶粒相比于其他晶粒没有尺寸优势. The high-temperature annealing process of high permeability grain-oriented silicon steel with AlN as an inhibitor was studied by interrupting test.The evolution of Goss texture in this process was analyzed by electron back-scattered diffraction.It is found that the Goss grain size first decreases and then increases with the rise of temperature.Goss texture appears in the orientation distribution function at 800 ℃,but the intensity is very weak and the deviation angle is more than 10°.The average... 

对新能源汽车以及驱动电机的现有市场和未来市场规模进行梳理分析，通过自建计算公式推导出我国2021年1-11月份驱动电机用电工钢的总量，进而预测未来10年中国新能源汽车驱动电机用电工钢情况，为无取向电工钢的生产和在电机中的应用提供有价值的参考。 The current market and future market size of new energy vehicles and traction motors were analyzed,and the total amount of electrical steels used in traction motors in China from January to November 2021 was derived by using self-built calculation formulas,and then the situation in the next ten years of electrical steel used in traction motors of new energy vehicles in China was predicted.It will provide a valuable reference for the production of non-grain oriented electrical steel and its appli... 

广泛应用于电子电力行业的取向硅钢材料的磁性能与其晶体取向密切关联，对取向硅钢晶体衍射花样的研究非常重要.采用理论计算的方式研究了取向硅钢的晶体衍射花样特征，并绘制了取向硅钢的高斯织构理论极图、理论单晶透射电子衍射斑点花样和理论电子背散射衍射(Electron backscatter diffraction, EBSD)菊池花样.取向硅钢理论单晶衍射花样不仅可以为以后标定样品实测晶体衍射花样提供一种简单快捷的方法，也可以为样品检测提供一种标准.这种研究方法不仅限于取向硅钢，也被期待应用于其他材料晶体衍射花样研究. The magnetic properties of oriented silicon steels which are widely used in electronic and power industries are closely related to their crystal orientations, so it is very important to study the crystal diffraction patterns of oriented silicon steels. The characteristics of crystal diffraction patterns of oriented silicon steels are studied by means of theoretical calculation. The theoretical pole figures, theoretical single crystal transmitted electron diffraction patterns and theoretical elec... 

硅钢工业退火炉温度控制具有强耦合、纯滞后、多扰动等特点,它的控制方法代表着一类非线性系统控制的解决方法。以硅钢工业退火炉温度为控制对象,在双交叉限幅控制的基础上引入了智能学习系统,形成了基于智能学习系统的双交叉限幅控制方法来解决此类非线性系统的控制问题,并通过模块化的编程来实现其功能。结果表明:与传统的PID控制相比,该控制方法的控制精度、抗扰性等控制指标有明显提高,是解决此类非线性控制的一种有效方法。 The temperature control of silicon steel industrial annealing furnace has the features of strong coupling,pure lag,multidisturbance. The control method represents the solution of a class of nonlinear control systems. The control object is the temperature control of silicon steel industrial an-nealing furnace, the intelligent learning system based on Double Across Limit Control is introducedand used to solve control problem of this kind of nonlinear system, and the module programming isused to re...