硅钢资料

采用双辊薄带连铸工艺制备了厚度为2.4mm的3.98%Si-0.71%Al无取向硅钢带,经常化、冷轧、不同温度退火后,对其显微组织、析出物、织构和磁性能进行了检测分析。结果表明:随着退火温度的提高,退火板晶粒尺寸增大,组织均匀性提高;退火板析出物主要是AlN和MnS与AlN复合析出物,尺寸较粗大,达0.5~2.5μm;退火板织构沿厚度方向变化明显,表层和1/2层存在较强的{100}织构,1/2层还存在较强的{111}织构,1/4层主要是{112}织构;随退火温度的升高相应的铁损和磁感应强度均降低。 Using twin roll thin strip continuous casting technique,the 3.98%Si-0.71%Al no-oriented silicon steel strip in thickness of 2.4mm was produced.The microstructure,precipitates,texture,and magnetic properties of the sheet after normalizing,cold rolling and annealing at different temperatures were studied.The results show that with annealing temperature increase,the grain size and uniformity of annealed sheet increased.The main precipitates in coarse size of 0.5-2.5μm in annealed sheet were AlN and... 

借助电子背散射(EBSD)技术对AlN为主抑制剂的Hi-B取向硅钢常化工艺的中间冷却制度进行了研究。结果表明:常化后试样均发生了完全再结晶,在60℃/s冷速下组织最均匀;在合适的冷却制度下常化板表层保留了强的Goss织构,它深入到1/4厚度处,并且形成对Goss织构有利的强{554}<225>织构。 The intermediate cooling system of Hi-B oriented silicon steel with AlN main inhibitor in normalizing process was studied by means of electron back diffraction(EBSD) technique. The results show that:the specimens after normalizing are fully recrystallization, and the microstructure is most uniform under the intermediate cooling rate of 60℃/s; under suitable cooling system, normalized plate surface retains strong Goss texture, it penetrates into the 1/4 thickness of the plate and forming strong {... 

试验研究了退火温度(850~950℃)和时间(5~18 min)对2.3 mm热轧硅钢板(/%:0.036C,3.15Si,0.21Mn,0.005P,0.007S,0.032A1)6道次轧制的0.35 mm冷轧板组织和织构的影响。结果表明,退火温度越高,晶粒平均尺寸越大,900℃5 min退火时平均晶粒尺寸41.39μm,试样织构主要集中在γ取向线上的{111}<112>织构组分和{111}<110>织构组分;900℃18 min退火时平均晶粒尺寸为48.08μm,试样的{111}面织构和{112}面织构密度都明显减弱,{001}面织构增强,磁性能较优。 The effect of annealing temperature(850 ~950 ℃) and holding time(5 ~ 18 min) on structure and texture of 0.35 mm sheet by 6 passes cold-rolling from 2.3 mm hot-rolled plate of silicon steel(/%:0.036 C,3.15 Si,0.21 Mn,0.005 P,0.007 S,0.032A1) has been tested and studied.Results show that the higher the annealing temperature the coarser the average grain size;As annealing at 900 ℃ for 5 min the average grain size of steel sheet is 41.39 μm,and the texture in sample is mainly concentrated in y orie... 

针对硅钢连续退火机组的主要能源介质消耗现状,对现有生产工艺和设备研究采取机组循环用水、增加清洗段漂洗级数等措施可节约大概27 m3/h的过滤水量,并可减少78%的弱碱处理量;将炉子烟气换热系统增加一级余热回收,每年回收的余热相当于583 t标煤消耗,可节约蒸汽5 368 t。 The present situation of energy consumption for silicon steel annealing line is analyzed in this paper.In existing process and equipment conditions,increasing the number of cleaning series will lead to a saving of about 27 m3/h of filter water and reduce 78 % of weak base processing volume.For the flue gas heat-exchange system,adding a waste heat recovery device will recover waste heat equivalent to 583 tons of standard coal per year,corresponding to a saving of steam 5 368 t per year. 

采用节能、环保、经济型的生产技术与工艺来制造高磁感取向硅钢目前已成为世界各大取向硅钢生产厂的研发热点。总结了国内外各大钢铁企业与研究机构采用低温板坯加热技术生产高磁感取向硅钢的开发及应用情况,概括了传统流程实现低温板坯加热技术的方法。介绍了薄板坯连铸连轧与双辊薄带连铸等短流程工艺生产高磁感取向硅钢的研发现状。在此基础上,探讨了高磁感取向硅钢生产技术与工艺的发展趋势及方向。 Utilizing energy-efficient,environmentally friendly,economic production processes and technologies to manufacture high magnetic induction grain-oriented silicon steel has become the focus of current research work.Based on using low-temperature slab reheating techniques to produce high magnetic induction grain-oriented silicon steel at both iron and steel enterprises and research institutions all over the world,the current application and exploitation was thoroughly generalized;the implementation... 

选用Q235和Q345钢,在纯锌浴和含钛量分别为0.05%、0.10%、0.15%、0.20%(质量分数)的合金浴中浸镀0.5、1、3、5、8 min。利用扫描电子显微镜和能谱仪研究了钛对热浸镀锌组织和生长动力学的影响,并提出钛对含硅钢铁锌反应抑制作用的机理。结果表明:钛的加入缩短了Γ的孕育期,促进了合金层中δ的生长和ζ的消失,δ的生长依然受扩散控制,呈抛物线生长规律;Zn-0.05%Ti锌浴可以很好的抑制高硅钢的硅反应性;含硅钢热浸镀锌钛合金浴时,在锌浴中会形成锌铁钛三元T相,该相能吸收ζ晶界处富集的硅,从而抑制了铁锌反应。 Both Q235 and Q345 steels were immersed for 0.5 to 8 min in Zn bath with different amount of Ti,ranging from 0 to 0.20 mass%,for galvanization.The effect of Ti in Zn bath on microstructure and growth kinetics of hot-dip galvanizing coatings on the two steels were investigated by means of SEM and EDS analysis.Base on the experiment,the mechanism of Ti additions in controlling Fe-Zn reaction was proposed.The results show that addition of Ti in the zinc bath decreases the incubation time of Γ phase... 

分析了冲裁硅钢芯片时出现的质量问题,针对影响硅钢芯片冲裁质量的4大因素——人、原材料状态、工艺和工装进行了工艺试验和分析,根据原材料状态的差异,采用不同工艺方案,特别是如何合理选择冲裁模具间隙,解决了硅钢芯片冲裁时产生的主要质量问题,使冲裁的硅钢芯片达到最佳质量状态,并满足硅钢芯片的使用性能。 The problems occurred during silicon steel chip punching and the factors that affect the quality of silicon steel chip punching were analyzed,the factors include 4aspects,that is,people,raw material status,process and frock,at the same time,process tests and analysis aimed at the factors that affect punching quality were did,according to the difference of raw material status,corresponding process schedules wee taken,especially in how to reasonably select punching dies clearance,which solved the ... 

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... 

研究表明,硅钢中的夹杂物对成品带钢的磁性能有显著影响。为研究冶炼过程硅钢中的夹杂物遗传变化,进而提出更有效的控制措施加以去除,本文结合典型的无取向硅钢生产炉次,采用非水溶液电解提取+扫描电镜观察方法分析冶炼过程中上述炉次典型试样的夹杂物。结果表明:转炉冶炼结束、RH精炼开始时,钢的氧化物夹杂总量最大,约为0.23%;RH精炼过程中,氧化物夹杂总量不断降低,并在脱碳结束时达到最低,约为0.02%;连铸过程中,氧化物夹杂总量仍有不断降低趋势,但夹杂物的平均尺寸变化不大。本试验条件下,中间包试样的夹杂物数量约为1.59×104个/mm3。 As we all know, the non-metallic inclusion effects magnetic properties of silicon steel sheets obviously. The article aims to study the heredity of non-metallic inclusion in non-oriented silicon steels during the steel making process, and then provides a more effective controlling measure to remove the inclusions. Based on the typical non-oriented silicon steel charges, the non-aqueous solution extraction and SEM observation were adopted to analyze the non-metallic inclusions. Results show that,... 

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... 

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. 

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...