硅钢资料

为了确定普通冷轧取向硅钢最优的中间完全脱碳退火工艺,在其一次冷轧后进行5种不同工艺的脱碳退火处理,借助扫描电镜及电子背散射衍射技术研究了不同工艺脱碳退火后的组织、织构和脱碳效果。结果表明:经5种工艺脱碳退火处理后,初次再结晶的平均晶粒尺寸均约为19μm,且不随退火温度和时间的变化而变化;经840℃×10min工艺退火后的晶粒最均匀,高斯织构位向更准确,高斯织构面积分数最多,为3.1%,可将碳脱至0.003 5%。 In order to determine the optimal intermediate complete decarburizing annealing processes for common grain-oriented(CGO)silicon steel,five kinds of intermediate decarburizing annealing processes were conducted,the microstructure,texture and decarbonization after different decarburizing annealing processes were studied by scanning electron microscopy and electro back-scattered diffraction(EBSD)technology.The results show that the average grains sizes of primary recrystallization were about 19μm a... 

近年来，在节能减排背景之下，国内外众多研究者对无取向电工钢磁性能的提升做了大量研究。为了探索无取向电工钢磁性能提升的方法，对锡或锑对无取向电工钢磁性能的作用机制(晶粒尺寸和晶体织构的控制)进行分析。基于该作用机制，介绍锡或锑的添加对无取向电工钢磁性能的影响。经研究发现，适量的锡或锑在晶界偏聚，不会阻碍晶界的移动并且致使晶粒尺寸降低；与此同时，锡或锑在晶界偏聚不仅抑制{111}织构在原始晶界处形核及生长，还降低(100)晶粒表面能，促进(100)晶粒生长。因此，适量添加锡或锑，可使无取向电工钢铁损下降、磁感提升。最后结合生产工艺，建议无取向电工钢的研究方向应为稀土含量对高牌号无取向硅钢夹杂物尺寸和数量分布的影响，锡或锑的添加量和常化工艺参数(常化时间、常化温度)对常化晶粒尺寸的影响。 In recent years, due to the background of energy saving and emission reduction, numerous researchers all around the world have done a lot of investigations on the improvement of magnetic properties for non-oriented electrical steel. In order to explore the method of improving the magnetic properties of non-oriented electrical steel, the mechanism of tin or antimony on the magnetic properties(the control of grain size and crystallographic texture) of non-oriented electrical steel is illuminated. ... 

通过对辉光放电发射光谱法分析电工钢样品光谱行为的研究,分析其工作参数如:电压、电流、预溅射时间和积分时间对光谱强度和稳定性的影响,并以铁为内标元素,优化了工作参数。确定了直流辉光放电光谱法测定电工钢中碳、硅、锰、磷、硫、铬、镍、铜共8种元素的定量分析方法,并对该方法分析的精密度和准确度进行验证,结果表明,各元素的测定结果与认定值和其他方法测定值一致,测量元素结果RSD值小于2%。 Based on research on analyzing the spectrum behavior of the sample taken from the electrical steel by glow discharge optical emission spectrometry,the effect of its operational parameters such as current,voltage,pre-sputtering time and integrating time on the spectral intensity and spectral stability is analyzed.Taking the Fe as an element applied by internal standard method,these operational parameters are optimized,and therefore the quantitative analysis method for testing eight kinds of eleme... 

【作者】 汤婧； ...

基于TEAM(Testing Electromagnetic Analysis Methods)Problem 21基准模型和不同类型的磁化曲线Bm-Hm及Bm-Hb数据,分别在50 Hz至200 Hz的频率范围内计算了基准模型的硅钢叠片内的损耗及磁通,并考虑集肤效应和材料的电-磁各向异性的影响。数值计算结果与实验测量结果具有很好的一致性。提出的有限元建模方法和基于模拟结果的分析、结论有助于提高大型电力变压器的电磁设计的有效性。 Based on TEAM(Testing Electromagnetic Analysis Methods) Problem 21 standard model and the different B-H(such as Bm-Hm and Bm-Hb) curves,the iron loss and magnetic flux inside the grain-oriented(GO) silicon steel lamination are modeled under different frequency(from 50 Hz to 200 Hz) in this paper,And the influences of skin effect and electric-magnetic anisotropy on the numerical simulation results have been examined.The calculated and measured results with respect to the model are in good agreeme... 

通过实验室25 kg真空感应炉冶炼和锻轧研究了0.26%～0.95%Al含量对0.5 mm 2.2%Si无取向硅钢冷轧板组织、织构和磁性能的影响。试验结果表明,0.26%～0.81%Al含量时,随钢中Al含量的增加,成品退火钢板的晶粒尺寸增加同时铁损减少;当Al含量大于0.81%时,随Al含量增加,钢板的晶粒尺寸减小,同时铁损增加。Al含量对硅钢板磁感的影响没有明显的规律。2.2%Si无取向硅钢的合适Al含量为0.48%～0.81%。 The effect of 0.26%～0.95%Al content on structure,texture and magnetic performance of 0.5 mm cold rolled sheet of 2.2%Si non-oriented silicon steel has been studied by a 25 kg vacuum induction furnace smelting,and forging -rolling in laboratory.Results show that as 0.26%～0.81%Al,with increasing Al content in steel the grain size of annealed finished sheet increases while iron loss of sheet decreases,and as Al content in steel is more than 0.81%,the grain size of sheet decreases while iron loss in... 

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... 

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... 

对高磁感取向硅钢冷轧板分别进行800、950、1050和1120℃不脱碳的预退火处理,在800℃预退火,成品的磁性能较好。织构分析的结果表明,随着预退火温度升高,初次再结晶后有利织构组分{111}<112>与不利织构组分(118)[110]的比值f(111)/f(118)逐渐降低,初次再结晶织构的变化是成品磁性的影响因素之一。 Preliminary annealing process at different temperatures for cold-rolled strips of a high permeability grain-oriented silicon steel was investigated to study the effect of the annealing temperature on microstructure and magnetic performance of the steel.Results show that the magnetic performances of the products annealed at 800 ℃ are best.Analysis of primary recrystallization texture indicates that with rising temperature,f(111)/f(118) which is the ratio of the favorable component {111}<112>... 

通过对湿H2气氛下,相同退火温度、不同退火时间的CGO硅钢初次再结晶样品进行金相组织观察,并进行了EBSD微观织构分析,研究了CGO硅钢初次再结晶过程中的组织及再结晶织构演变行为。结果表明,在湿H2气氛下,820℃保温,CGO硅钢初次再结晶过程约在120 s时完成。随着退火时间的延长,γ面上{111}<112>织构含量逐渐减少,{111}<110>织构先减少后增多,随着再结晶的完成,部分{111}<112>取向晶粒向高斯{110}<001>取向转化的同时,也向{111}<110>取向转化,高斯{110}<001>织构含量逐渐增多。高斯取向晶粒较多是由{111}<112>取向晶粒转化而来,同时也证明了CGO硅钢高斯取向晶粒的二次再结晶异常长大生长机制为择优形核。 Microstructure development and texture evolution of conventional grain oriented silicon steel,which were annealed at same annealing temperature and different annealing time under wet H2 atmosphere,were investigated through metallographic observation and electron backscattered diffraction analyzing.The results show that the primary recrystallization finishes in 120 s at 820 ℃ under wet H2 atmosphere.With the extending of annealing time,{111}<112> texture decreases,{111}<110> texture d... 

以取向电工钢成分为基础,制备了含C或Mn和S的4种实验钢。观察了接近平衡析出状态实验钢经60%冷轧后在600～1000℃范围再结晶退火过程中微观组织演变,统计分析了再结晶体积分数随退火时间的变化规律,进而计算了各实验钢静态再结晶的激活能。观察了高含C实验钢退火初期再结晶晶粒优先出现的部位。结果表明900～1000℃范围内各实验钢铁素体的化学成分相似,因而其再结晶激活能基本一致。在600～800℃范围内铁素体内会有阻碍再结晶进程的三次渗碳体析出,从而使再结晶激活能明显提高。高C含量实验钢中还会有从奥氏体转变而来的粗大珠光体或渗碳体,轧制过程中其附近形成的变形区会促进600～800℃加热时该区域附近率先发生再结晶形核、降低再结晶激活能。固溶的Mn、S元素可微弱提高再结晶激活能,但高Mn、S含量会改变粗渗碳体从奥氏体析出时的形态。 Four experimental steels based on grain oriented electrical steel containing C,or Mn and S were prepared.Microstructure evolution of the steels close to a state of equilibrium precipitation were observed during annealing processes at 600-1000 ℃after 60% cold rolling,the changes of recrystallization volume fraction were analyzed statistically as the annealing was prolonged,and the activation energy for static recrystallization of the steels were calculated.The locations,where the recrystallizatio... 

为进行磷酸盐系无铬无取向硅钢涂层烧结固化工艺研究,首先对磷酸盐系无铬无取向硅钢涂层进行热重-差示扫描量热(TG-DSC)分析;然后在不同烧结固化温度条件下,测定涂层板温随时间变化曲线;最终获得涂层烧结固化温度与时间(T-t)工艺曲线。通过中性盐雾试验、动电位极化、交流阻抗、涂层附着力以及扫描电子显微镜(SEM)和能谱(EDS)分析验证。结果表明,根据涂层烧结固化温度与时间(T-t)工艺曲线制备的涂层结构致密、性能优异,证明该工艺曲线具有合理性与正确性。 In order to study the curing process of chromium-free non-oriented silicon steel coatings,phosphatic chromium-free non-oriented silicon steel insulating coating was prepared and TG-DSC analysis of the coating was conducted,then the change of the actual temperature of the coated non-oriented silicon steel sheet with time at different curing temperatures was studied. Based on the experiments,the processing curves of curing temperature vs. curing time( T-t) for the chromium-free non-oriented silico...