钢厂
TSCR试制高强度无取向电工钢
采用固溶强化、细晶强化和位错强化方法,模拟TSCR流程试开发高强度无取向电工钢,试开发钢的主要合金成分为3%Si、0.83%Al和2.99%Mn。分析热轧、常化、退火后的钢板组织,并针对不同的成品板组织,详尽地分析了相应的力学性能和磁性能。试验电工钢平均晶粒直径为12.37μm时,R p0.2为530 MPa,R m为618 MPa;当退火制度为700℃×4 min,成品组织完全为未再结晶的回复组织时,R p0.2为853.5 MPa,R m为895.5 MPa。该成分的电工钢P15/50或P10/400最小时,对应的平均晶粒直径都大于59.67μm;P10/800或P10/1000最小时,对应的平均晶粒直径都处于12.37~59.67μm尺寸区间。 TSCR was simulated to develop high-strength non-oriented electrical steel with 3% of Si,0.83% of Al and 2.99% of Mn by solution strengthening,grain refinement strengthening and dislocation strengthening.The microstructures of hot rolled plates,normalized plates and annealed plates were analyzed.Furthermore,the mechanical properties and magnetic properties of products with different microstructures were detailedly studied.As the average grain diameter of the steel was 12.37 μm,the yield strength ...
钇元素对6.5%Si无取向硅钢组织、高温拉伸及断裂机制的影响
通过微观组织表征、高温拉伸和断口形貌分析,研究了钇(Y)元素对6.5%Si无取向硅钢组织、高温拉伸及断裂机制的影响。研究结果表明,添加Y元素可以在钢液中形成YS和YP的复合析出。YS和YP可以充当异质形核基底,提高形核率,细化凝固组织。热轧组织不均匀,由表层至芯部分别形成等轴晶、等轴晶/拉长晶和拉长晶的混合组织。退火后,热轧变形组织转变为等轴晶,含Y实验钢的退火组织得到明显细化。500℃时效处理后,含Y实验钢具备较低的有序度,300℃的拉伸断口呈现韧性断裂特征,断后伸长率达到20.2%。相反,无Y实验钢发生脆性断裂,断后伸长率仅为2.1%。研究结果证实,Y元素可以通过组织细化和降低有序度提高6.5%Si无取向硅钢的中温塑性。 The effects of yttrium(Y)on microstructure,elevated-temperature tensile properties and fracture mechanism of 6.5% Si non-oriented electrical steel were investigated by means of microstructure characterization,high-temperature tensile test and fracture analysis.The results showed that the doping of Y introduced composite Y-rich precipitates(YS/YP)in the melt.YS and YP precipitates were qualified for heterogeneous nucleation agents,which thus raised the nucleation rate and refined the solidificati...
锡或锑在无取向电工钢中的研究进展
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. ...
高硅FeSi合金层对普通取向硅钢磁性能的影响
目的提高硅钢的磁性能。方法采用多弧离子镀技术,在普通取向硅钢薄板两面沉积高硅FeSi合金层制得高硅梯度硅钢,并进行热处理,观察其显微组织,测量磁性能。结果退火态高硅梯度硅钢表面的高硅FeSi合金层与基底结合紧密,均匀致密。高硅梯度硅钢中硅含量呈梯度分布,最表层硅质量分数为11.0%,随着深度增加,硅含量逐渐降低,在距表面20μm处硅质量分数仍能达到6.5%。沉积态高硅梯度硅钢的电阻率ρ、低频铁损P10/50、高频铁损P10/1k及磁感应强度B8分别为68.6μΩ·cm,0.82W/kg,83.3 W/kg和1.73 T,退火后分别为63.1μΩ·cm,0.44 W/kg,54.38 W/kg和1.89 T。结论由于表层高硅FeSi合金层的存在,梯度高硅钢的低频磁学性能良好,但高频损耗需进一步改善。 Objective To improve the magnetic properties of silicon steel. Methods FeSi alloy coatings with high-silicon content were deposited on the surface of common grain-oriented silicon steel by cathodic arc plasma evaporation,and then a kind of high silicon gradient steel was prepared. The morphologies,content and magnetic properties of the samples were tested. Results FeSi alloy coatings were featured with compact microstructures and excellent adhesive quality with the substrates. The silicon conten...
微量Sn对0.4%Si无取向硅钢组织和磁性能的影响
结合实际生产0.4%Si无取向硅钢，统计了不含Sn和0.025%Sn无取向硅钢的磁性能变化，利用金相显微镜、X射线衍射仪观察分析不同成分下试样的显微组织和微观织构。试验结果表明：Sn元素可以显著降低无取向硅钢的晶粒尺寸，0.025%Sn试样的平均晶粒尺寸比不含Sn减小28.4%;加入Sn元素后抑制了无取向硅钢中不利于磁性能的{111}面织构组分强度，提高了对磁性能有利的{100}面织构组分强度，0.025%Sn与不含Sn相比磁感均值从1.756 T提升至1.768 T,铁损均值从5.476 W/kg降低至5.204 W/kg,明显改善了无取向硅钢磁性能。 In this paper combined with the actual production of 0.4% Si non oriented silicon steel, the magnetic properties of non oriented silicon steel without Sn and 0.025% Sn were counted. The microstructure and microtexture of samples with different compositions were observed and analyzed by metallographic microscope and X-ray diffraction. The results show that: Sn can significantly reduce the grain size of non oriented silicon steel, and the average grain size of 0.025% Sn sample is 28.4% smaller tha...
硅元素对Fe-(4.5～7.0)%Si高硅钢组织和性能的影响
通过Axio Imager金相显微镜考察4.5%~7.0%硅(质量分数)对高硅钢材料组织形貌的影响,并利用Fe-6.5%Si高硅钢薄板制备方法对其进行轧制,通过DDL50电子万能试验机对阶段产品进行力学性能测试。结果证明,硅含量为5.58%的高硅钢在实验硅含量区间内存在最大延伸率及最小铸态组织晶粒尺寸。 An investigation about the influence of 4.5%-7.0% Si on microstructure and mechanical properties of high-silicon steel was presented.SEM was adopted to take an observation towards microstructure during fabrication,and DDL50electronic universal testing machine was applied into the detection of tensile curves.The results show that silicon steel with 5.58% Si provides the maximum elongation and minimum grain size as cast.
取向硅钢常化水冷温度模型及控制方法研究
取向硅钢常化工序主要采用现场实测带钢温度的方式测定冷却速率，并通过稳定冷却水温、调整冷却水量及喷梁运行数量等方式保证合理的冷却速率，给常化工艺设计和生产带来诸多不便。通过对常化工艺水冷过程带钢的传热分析求解，在建立带钢水冷温度模型的基础上，研究了不同冷却工艺参数对带钢温度及冷却速率的影响规律以及冷却工艺的交互作用结果。结果表明：模型计算结果能够较好地反映取向硅钢在常化水冷过程中的温度及冷却速率的变化，其计算误差为0.80%～4.11%;在特定取向硅钢厚度规格和常化工艺下，随着常化冷却水量及有效冷却长度的增加，带钢水冷温度及冷却速率与呈非线性变化；常化水冷工艺主要通过调控带钢与冷却水之间热交换量和交换时间实现对带钢温度的控制，实际生产中需综合考虑机组速度、冷却水量及有效冷却长度之间的交互作用，选定喷梁投入数量和冷却水量以获得稳定的冷却速率。 The cooling rate of normalization process mainly determined by measuring the grain oriented silicon steel strip temperature on site, and ensures the cooling rate by stabilizing the cooling water temperature, adjusting the cooling water volume and the operation quantity of spray beam, which brings inconvenience to the normalization process design and production. Based on the heat transfer of strip in the water cooling section of normalization process, the water cooling temperature model for the n...
一类非线性系统控制方法在硅钢生产上的应用
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...
