硅钢资料

对低温加热工艺生产的普通取向(common grain-oriented,CGO)硅钢的高温退火过程进行了中断实验,材料为含3.0%Si、0.5%Cu、0.009 8%S(均为质量分数)的以Cu2S为主抑制剂的普通取向CGO钢。原始板坯厚度为230 mm,于1 200℃均热后经4道次粗轧、7道次精轧至2.3mm;热轧板采用两次冷轧法轧至0.3mm,中间完全脱碳退火,最后于1 200℃高温退火。最后样品的磁性能:铁损P17/50为1.182W/kg,磁感应强度B8为1.897T。借助配有EDAX OIM电子背散射衍射(EBSD)系统的ZEISS SUPRA 55VP扫描电子显微镜,对高温退火过程中高斯晶粒的演变进行了研究,结果表明:升温过程中晶粒尺寸增长缓慢,650℃时取向分布函数(ODF)图出现高斯织构组分,但强度很弱,高斯晶粒偏离角小于9°;950℃时高斯晶粒平均生长速度超过其他晶粒;950~1 000℃时高斯晶粒异常长大,偏离角降至约3°;在950℃之前高斯取向晶粒相比于其他晶粒没有尺寸优势。 The high-temperature annealing process of common grain-oriented(CGO)silicon steel was investigated by interrupting test.The samples were rolled from CGO silicon steel slab under low reheating temperature.The CGO silicon steel,taking Cu2S as the main inhibitor,contains3.0%Si,0.5%Cu,and 0.0098%S.The original casting slab is 230mm in thickness.After 1 200℃reheating,four-pass rough rolling and seven-pass finish rolling were conducted to make the thickness of the slab get to 2.3mm.Then the hot rolled... 

根据相关的取向电工钢典型专利技术,概述了日本高磁感低铁损取向电工钢低温板坯加热、抑制剂合理调节、关键成分Mn、C、Sn和Sb调节与利用、新型退火剂和绝缘溶液的制备及细化磁畴等生产工艺最新动态和进展情况,并提出了国内企业申请取向电工钢专利时应当借鉴之处。 According to related typical patent technology for grain-oriented electrical steel sheets,the recent trends and progress situation for production process of grain-oriented electrical steel sheets with high magnetic flux density and low core loss in Japan are summarized including low temperature slab heating,suitably regulating inhibitors,adjusting and utilizing key element Mn,C,Sn and Sb,manufacturing for new annealing agent and insulating solutions,and fining magnetic domain,and some suggestion... 

为了优化激光刻痕降低取向硅钢铁损的工艺,寻找刻痕速度、脉冲能量、扫描间距等重要刻痕参数的最佳匹配关系,提出了一种基于人工神经网络与遗传算法的优化模型,并利用这种模型对30Q130取向硅钢材料的刻痕工艺进行了优化实验,结果表明,这种模型稳定可靠,可以作为取向硅钢刻痕工艺优化的一种有效的措施。 A laser is often considered to scribe the grain-oriented silicon steel surfaces after cold-rolling and annealing to reduce the core loss.It is necessary to select the best scribing parameters to maximize the reduction in this process.This paper proposes an optimization method of genetic algorithm during laser scribing of 30Q130 steel,by developing an artificial neural network prediction model using a database form a designed orthogonal experiment.The objective is to determine the best combinatio... 

采用双辊薄带连铸技术试制了3.98%Si-0.71%Al无取向硅钢铸带,研究了二次冷轧法对硅钢组织和磁性能的影响。结果表明:硅钢铸带显微组织为等轴晶组织,铸带再结晶较完全,常化对铸带显微组织影响较小。二次冷轧工艺和一次冷轧工艺下,最终退火后成品显微组织为等轴晶组织,二次冷轧法最终退火后的晶粒尺寸小于一次冷轧法。二次冷轧法能够提高成品磁性能. Effect of double cold rolling on magnetic properties and microstructure of 3.98%Si-0.71%Al non-oriented silicon Steel Sheets cast by twin-roll thin strip casting process were investigated.The results show that the structure of the thin strip is equiaxed crystal,the recrystallization is complete and normalizing has lesser effect on microstructure.Using both cold rolled and double cold rolled process,the microstructure is equiaxed grain after final annealing.The average grain size of annealed shee... 

叠片系数是冷轧无取向电工钢的重要质量指标。为了提高叠片系数,必须保证无取向电工钢板形良好以及横向厚差小。针对攀钢冷轧厂4机架HC轧机轧制无取向电工钢的边部减薄问题,以无取向电工钢横向厚差最小作为目标函数,建立了一套针对无取向电工钢边部减薄控制的辊型曲线优化数学模型,开发了无取向电工钢专用辊型曲线,使无取向电工钢横向厚差从25μm降低到10μm以下,取得了良好的控制效果。 The lamination factor is an important quality index of non-oriented silicon steel strip.Considering the lamination factor,the non-oriented silicon steel must have a good shape and a smaller transverse thickness difference.In order to solve the edge thinning of non-oriented silicon steel strip in Panzhihua Steel,a mathematic model for designing the roll shape is built.In the model,the transverse thickness difference of non-oriented silicon steel strip is taken as the objective function.Based on t... 

采用扫描电镜、场发射扫描电镜、能谱仪等对50SW1300冷轧无取向硅钢中的夹杂物分不同尺寸区间进行数量统计,利用主成分回归分析法,即数据的标准化处理—主成分分析—回归分析—标准化的变量还原成原始变量—确定显著影响因素,综合分析夹杂物总量及各尺寸区间的夹杂物数量对无取向硅钢磁性能的影响。结果表明:主成分回归分析能够从夹杂物尺寸区间及数量的多个影响因素中提取主要的因素,定量研究其对磁性能的影响。分析表明,显著影响无取向硅钢铁损的夹杂物为100~500nm的AlN、AlN+MnS、MnS、Al2O3、AlN+Al2O3,而劣化磁感最明显的夹杂物尺寸区间为100~200nm。 Different size intervals of inclusions in cold rolled non-oriented silicon steel 50SW1300 were counted by scanning electron microscope(SEM),field emission scanning electron microscope(FESEM)and energy disperse spectroscopy(EDS).With principal component regression method:standardization for experimental data,principal component analysis,regression analysis,transform standardized variables into original variables,determination of significant factor,effects of the total number of inclusions and the... 

研究了无取向硅钢钙处理前后夹杂物的行为,重点考察了钙处理前后夹杂物的成分、类型、形貌和尺寸研究的变化情况,为实际生产中无取向硅钢的钙处理提供理论指导。试验发现:钙处理前夹杂物主要以Al2O3、Al2O3-MgO为主,且在夹杂物表面有AlN析出,钙处理后夹杂物以Al2O3-MgO-CaS-CaO系复合夹杂物为主,还含有少量的SiO2或AlN;钙处理前后,夹杂物形貌由多边形或不规则形逐渐向球形或近似球形转变,并且夹杂物尺寸不断增大;钙处理前后,含钙夹杂物的比例发生突变,由10%增大到74.5%,且随着钙处理时间的延长,含钙夹杂物比例下降,表明钙处理使夹杂物变性后易聚集长大并上浮去除。 Behavior of inclusions before and after calcium treatment in non-oriented silicon steel was researched by investigating changes of compositions,types,shapes and sizes of inclusions before and after calcium treatment,for the purpose of providing theoretical guidance for calcium treatment of non-oriented silicon steel in actual situation. Results indicated that Al2O3 and Al2O3-MgO were main types of inclusions before calcium treatment,sometimes AlN maybe precipitate in the outer of inclusions. Al2... 

提出一种基于粒子群优化算法实现的硅钢涂层厚度近红外光谱检测新方法。首先,采用近红外光谱仪采集获得了硅钢表面绝缘涂层的近红外光谱,然后,采用离散粒子群算法筛选出近红外光谱数据的最佳波长变量并组成新的光谱数据,最后,建立涂层厚度的核偏最小二乘定量分析模型。实验显示,所建定量分析模型对检验样本分析的绝对误差范围为-0.12～0.19μm,最大相对误差为14.31%,完全符合现场检验需要。研究表明,离散粒子群算法可以有效地筛选出携带更多有用信息的波长变量,提高定量分析模型的分析准确度和速度,是一种有效的近红外光谱波长筛选方法,同时,近红外光谱法也是一种有效的硅钢绝缘涂层厚度检测方法。 A novel thickness measurement NIR spectrometry for surface insulation coating of silicon steel based on discrete binary particle swarm optimization(DBPSO) algorithm is presented.First,we used NIR spectrometer to collect the NIR spectra of insulation coating of silicon steel,and then,DBPSO algorithm was used to select the optimal wavelength variates and composed a new spectra set.Last,the authors created the thickness quantitative analysis model using kernel partial least square algorithm.The exp... 

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... 

通过热力学计算,分析了实验钢中主要析出物析出的可能性。结果表明:在液相和固液两相区中,AlN和MnS均不能析出;在奥氏体区,AlN和MnS具备热力学析出条件,平衡析出温度分别为1547、1582 K。成品退火板中的析出物主要为AlN和MnS。扫描电镜下观察到的AlN形貌多为长条状,MnS形貌多为棒状或近似球形。这两种析出物占了析出物总量的85%以上,尺寸集中分布在400~800nm;复合析出物主要是(Al2O3+MnS)和(AlN+MnS),形貌不规则,尺寸集中在0.7~1.5μm;透射电镜下观察到了少量100nm以下独立的AlN析出。 According to thermodynamic calculation, the precipitation probability of precipitates was analyzed, AlN and MnS can not precipitate in liquid phase area and solid-liquid two-phase area. In austenite area, both the AlN and MnS have precipitation condition in thermodynamics and precipitates at 1547 K and 1582 K, respectively. The precipitates in annealing plate are mainly AlN and MnS. The shape of AlN is mostly strip, and MnS is stick or near sphericity. They accounted for over 85% of the total qu... 

采用取向分布函数分析了无取向电工钢不同再结晶退火温度下的织构变化及织构对磁感应强度和铁损的影响,并计算了无取向电工钢的磁晶各向异性能。结果表明,随着实验钢的再结晶退火温度升高,Goss织构和立方织构组分显著增强,而{111}面织构强度却减弱。较高的退火温度有利于减小织构因子,提高磁感应强度。磁晶各向异性能计算结果显示,随着再结晶退火温度升高,无取向电工钢板的磁晶各向异性能降低。 The recrystallization texture and the relationship of texture to magnetic induction intensity and core loss of a non-oriented electrical steel were investigated by orientation distribution function analysis. The magnetic anisotropy energy of the steel was calculated also. The results show that,the intensity of Goss texture and cubic texture increases,but the intensity of { 111} texture decreases with increasing recrystallization annealing temperatures of the steel. The higher annealing temperatu... 

轧制力是影响冷轧带钢厚度精度的关键因素。为实现高精度的冷轧带钢厚度控制,通过优化变形抗力模型参数和摩擦系数模型参数提高冷轧轧制力模型计算精度,并使用指数平滑法的自学习算法保证轧制力精度的稳定性。在首钢股份公司迁安钢铁公司20辊森基米尔轧机生产线进行S12硅钢钢种轧制力优化试验,将优化的模型参数应用于L2并投入现场生产,结果表明该优化方法不仅提高了轧制力设定精度,而且减小了冷轧硅钢的厚度超差长度,提高了成材率。 The rolling force is the key factor which influences the accuracy of cold-rolling strip thickness. To implement high precision control of cold-rolling strip thickness,we optimize the deformation resistance model parameters and friction coefficient model parameters to improve the calculation precision of cold-rolling force model,and use exponential smoothing self-learn algorithm to ensure the stability of rolling force accuracy. In Shougang Qiangang 20-high Sendzimir mill single stand production ...