硅钢资料

介绍了烟气余热利用系统的工艺流程及控制思想,结合该系统在钢厂硅钢连续退火机组中的应用实践,估算出烟气余热利用系统每年可节约蒸汽5 040 t,经济效益良好,同时分析了该系统存在的问题及对策。 Introduced a method about the process and control of the application of waste heat system, which had been used into a silicon steel continuous annealing line and profiting a good economic benefit by saving a large number of steam every year, which has been estimated about 5 040 tons, and analyzed the problems and solutions existed in this system. 

电工钢反复弯曲次数是电工钢性能检验的重要指标之一,直接影响到用户在使用电工钢过程的机加工性能。主要分析了试样宽度、试样张力、晶粒取向、反复弯曲设备等因素对电工钢反复弯曲试验的影响,并对各个因素的影响程度进行量化以及原因探讨,从而归纳形成各影响因素的基本规律,以便为电工钢实际生产、用户使用提供科学指导。结果表明:试样宽度增加,反复弯曲次数也会不断增加,晶粒位向对取向电工钢的反复弯曲次数影响较大,当支座顶部到拨杆底部的距离减小或拉紧力增加时,反复弯曲次数会不断减小,但当拉紧力达到60N以上时,对反复弯曲次数影响不大,试样经退火后,反复弯曲次数略有上升。 The reverse bend number is an important performance of electrical steels′capabilities,affecting the machining performance directly when the customers used.It investigated some factors,such as sample′s width,sample′s tension load,grain orientation and equipment,how to effect the reverse bend test for electrical steel,measured the influence degree,and discussed the reason,in order to form basic rules which could be guided the manufacturing and using for electrical steel.Results showed that the rev... 

目前高磁感冷轧硅钢生产过程中，采用经验方法确定的乳化液流量设定值往往会造成硅钢产品的磁感性能达不到预期目标，针对此情况，基于轧机轧制机理研究了的乳化液流量数学模型，确定了乳化液流量设定值。实践表明，使用该数学模型输出的乳化液流量设定值，可提高轧制过程中乳化液流量控制精度，从而提高高磁感冷轧硅钢的轧制性能。 In view of the current production process of high magnetically inductive cold-rolled silicon steel, the mathematical model of emulsified fluid flow based on mill rolling mechanism is studied in view of the situation in which the magnetic sensing performance of silicon steel products is often not up to the expected target by using empirical method to determine the emulsified liquid flow setting. Practice shows that the emulsified fluid flow setting value output from this mathematical model improv... 

双辊连铸技术是冶金及材料领域内的一项前沿技术,对于生产高品质硅钢具有独特优势.本实验研究了一种双辊铸轧w[Si]=4.5%的无取向硅钢,考察其铸态和常化处理后样品的组织、织构及析出相尺寸特征.结果表明:铸带组织以与铸带法向成5~20(°)倾角的柱状晶为主,晶内存在少量0.3~0.4μm的AlN析出相,铸带织构以λ(<001>//ND)织构为主,表层织构漫散.950℃/10 min常化处理后,析出相尺寸增大,表层λ织构增强. As an advanced technique of metallurgy and material science,twin- roll strip casting has unique advantages for producing high quality silicon steel. The present study was aimed at a 4. 5% Si non- oriented electrical steel for analyzing the structure,texture and the size of precipitates at the initial and normalized state. The results revealed that the initial structure mainly consisted of columnar grains with 5 ~ 20( °) angle to the normal of cast strip,and some AlN precipitates of 0. 3 ~ 0. 4 μ... 

【作者】 谌剑； ...

组织和织构是影响无取向硅钢性能的重要因素。为改善产品性能，研究了冷轧压下率（71.7%～87.0%）对高牌号无取向硅钢组织、织构、磁性能和力学性能的影响。结果表明，随冷轧压下率的增加，退火晶粒平均尺寸先减小后增大；高斯和立方织构强度减弱，γ纤维织构增强，α纤维织构转变为较强的α^*（{h, 1, 1}〈1/h, 1, 2〉）织构，并随冷轧压下率的增加而增强，同时其峰值逐渐向{111}面移动；工频铁损P_1.5/50、高频铁损P_1.0/400和磁极化强度J₅₀₀₀同时降低，屈服强度变化不大，表面硬度逐渐增加。当冷轧压下率由84.7%增至87.0%、厚度减至0.30 mm时，高频铁损降幅是工频铁损的11倍，表面硬度增幅变大。以上研究成果对硅钢减薄后织构及组织的优化提供了很好的指导。 Microstructure and texture are critical factors on non-oriented silicon steel properties. In order to improve product properties, this paper studied the effect of cold rolling reduction rate（71.7%-87.0%） on microstructure, texture, magnetic properties and mechanical properties of high-grade non-oriented silicon steel. The results show that with the increase of cold rolling reduction rate, the average size of annealing grain decreases first and then increases. The intensity of Goss and λ fiber te... 

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... 

【作者】 朱传芳； 潘恒韬； ...

【作者】 陶永根； ...

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... 

考虑剪应变对微孔洞损伤演化的影响,对GTN损伤模型的损伤演化机制进行修正,建立了适用于不同应力三轴度水平的损伤模型。结合隐式应力更新算法和显式有限元计算,采用VUMAT子程序实现了修正GTN模型在有限元软件ABAQUS中的数值计算。通过模拟纯剪切和剪切-拉伸两组试样的损伤演化和断裂行为,验证了修正GTN模型在不同应力三轴度承载条件下的有效性。运用修正GTN损伤模型模拟含边部缺口的带钢在轧制过程中裂纹的萌生和扩展行为,模拟结果与实验相一致,表明该模型可有效地用于带钢缺陷在轧制过程中扩展行为的分析和预测。模拟和实验结果表明,带钢边部缺口在轧制过程中,缺口前沿和后沿均会萌生裂纹,且后沿裂纹扩展更为明显。 Considering the effect of shear strain of micro-void on damage evolution, a modified GTN model applicable to various stress triaxiality conditions is proposed by modifying the damage evolution mechanism of the GTN damage model. The modified model is implemented in commercial finite element software ABAQUS by combining the implicit stress update method with an explicit finite element solving algorithm and through the user-defined material subroutine VUMAT. The damage evolution and the failure pro... 

研究了退火温度和退火时间对电沉积硅钢试样中的断面层组织、硅在试样中的分布情况、织构分布和磁性能的影响。结果表明:退火温度为1000℃、退火时间为210 min时得到的试样晶粒分布均匀、硅在试样中分布均匀、硅平均浓度为6.3715%(接近6.5%)。试样的织构分析及磁性能检测的结果表明,在较高温度下延长退火时间可增加{100}和{110}面织构,降低铁损,所得试样的磁性能较为良好。 The effect of annealing temperature and time on the microstructure, distribution of silicon,texture and magnetism of the high silicon steel prepared by electrodeposition was investigated. The results showed that after annealing at 1000℃ for 210 min, the mean grain size of steel was about 190 μm with a uniform grain size distribution, and the silicon is also uniformly distributed on the entire cross section with an average Si concentration 6.3715%(close to 6.5%); With the increasing annealing tim...