硅钢资料

冷轧无取向硅钢是高技术含量、高附加值产品,工艺复杂,生产周期长,过程控制难度大,被誉为钢铁产品中的\"工艺品\"。热轧生产工艺又是无取向硅钢生产的重中之重,直接决定了硅钢的铁损和电磁性等多项指标。 Cold rolled non-oriented silicon steel is high technology content 、high added value product. Its process is complex, its production cycle is of length, and its process control is difficult, which is known as the iron and steel products \" Arts and crafts\". Hot rolling production process is the top priority of non-oriented silicon steel, which directly determines iron loss of the silicon steel and electromagnetic property,as well as other many index. 

【作者】 陶永根； ...

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... 

采用化学气相沉积(CVD)渗硅处理工艺连续制备6.5%Si高硅钢,具有优质的软磁性能,通过理论研究化学反应并且用简单的试验设备做进一步的探讨。根据试验的结果对连续制备6.5%Si高硅钢的CVD工艺构造提出全面、有效的建议,实现制备6.5%Si高硅钢系统。 CVD method for continuously manufacturing 6.5%Si Steel Sheet has excellent soft magnetic.Carried out a theoretical study of related chemical reaction and performing basic research with a simple test apparatus.Based on the results,finally proposed an overall process configuration to realize such a production-CVD method for continuously manufacturing 6.5%Si Steel Sheet. 

【摘要】 <正>为了确保电工钢的产品质量,在生产线...

变压器D21硅钢铁芯片采用冲压工艺生产。首先对其工艺进行了分析,确定了冲压方案。对产品进行了排样设计,计算了冲压力,确定了压力中心。然后,设计了单工序落料模具,完成了模具装配图。 D21 silicon steel chips for transformer are produced by stamping.First,its stamping process was analyzed and the scheme of the stamping process was determined.The product layout was designed,the punching pressure was calculated,the pressure center was determined.Then,the blanking die with single procedure was designed,the die assembly drawing was completed. 

综述了电工钢从生产到成品过程中涉及到的检测项目、检测方法及仪器,并通过对电工钢标准的发展改进,详细阐述了我国现有的电工钢技术标准体系,同时对代表企业的电工钢重点指标进行了摘录对比,为综合应用电工钢检测方法并促进电工钢的发展提供了一定的参考。 This article summarizes the testing items,methods,and instruments involved in the process from manufacturing to finished products of electric steel. The current electric steel technical standards system in our country is also elaborated in detail,along with the development and improvement of electric steel standards. Meanwhile,by comparison of electric steel KPI in representitive companies,this article provides references for comprehensive application of electric steels testing methods and promo... 

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... 

无取向硅钢的磁性能主要取决于铁素体的晶粒尺寸、晶体织构和钢中的夹杂物。通过合适的化学成分设计以及采用适宜的夹杂物控制技术,可以获得最佳的夹杂物控制效果,使其纯净度大幅度提高或者无害,最终获得磁性能优良的高级别无取向硅钢。同时,为满足节能、环保、高效需求,无取向硅钢正朝着节能降耗、环境友好以及多功能、高效率、易加工等方向发展。 The magnetic properties of non-oriented silicon steel mainly depend on the grain size of ferrite,the crystallographic texture,and the inclusions in the steel.The optimum inclusion control effects can be obtained through a suitable chemical composition design and an appropriate inclusion control technique,and then the liquid steel will get be clean or the inclusion will get be harmless,finally the excellent magnetic property of the non-oriented silicon steel can be obtained.Meanwhile,in order to ... 

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... 

【机构】 商务部进出口公平贸易局； ...

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...