硅钢资料

【作者】 韩超； 代智肄； ...

含铜抑制剂作为取向硅钢的主抑制剂或辅助抑制剂不仅可以抑制初次晶粒的长大,促进二次再结晶,还可以降低铸坯的加热温度。取向硅钢中主要抑制剂为10～50 nm Cu₂S,在钢的铸坯、热轧、冷轧、脱碳等工艺过程均可析出;（Cu,Mn）_1.8S、Cu_1.8S、ε-Cu等主要作为辅助抑制剂,尺寸一般为30～50 nm（或大于50 nm）,主要在热轧阶段析出。总结了国内外有关取向硅钢中含铜抑制剂析出行为的研究进展,当前主要研究不同生产流程和工序中含铜抑制剂的析出行为和作用机理。 As main inhibitor or auxiliary inhibitor for grain-oriented silicon steel,the particles of inhibitor bearing copper not only inhibit the primary crystal growing and promote the secondary recrystallization,but also decrease the heat temperature of casting slab.The main inhibitor for grain-oriented silicon steel is 10～50 nm Cu₂S,which precipitate in process and procedure including steel casting slab,hot rolling,cold rolling and decarburizing process,while the 30～50 nm or more than 50 nm... 

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... 

【作者】 陶永根； ...

利用OM,TEM,EDS与XRD技术,对Fe-3.15%Si低温取向硅钢热轧板不同常化处理后的显微组织、析出相及最终产品的磁性能进行了分析研究,并对热轧板和常化板经过冷轧后的冷轧板织构进行了对比分析.结果表明,采用1120℃保温3 min二段式冷却的常化处理工艺,常化板表层显微组织均匀,沿板厚方向的显微组织的不均匀性显著,对后续过程中形成高取向的Goss织构最有利,取向硅钢的磁性能最高;采用二段式冷却的常化冷却工艺最优,在此冷却工艺下析出的细小的析出物数量最多,且弥散分布在基体中,抑制剂的抑制效果最好,对成品获得高磁性最有利;热轧板、常化板经过冷轧后的冷轧板织构均主要由{111}〈110〉和{111}〈112〉织构组成,但常化板较热轧板冷轧后的冷轧板γ取向线织构密度明显增高,由此可以证实常化处理有助于取向硅钢最终获得高取向的Goss织构. The decreasing of slab heating temperature for grain-oriented silicon steel will reduce the amount of precipitates in hot rolled plate,and be disadvantage to the formation of ultimate Goss texture.The aim of normalizing is to control and adjust the amount,size and distribution of precipitates.Microstructures,precipitates and magnetic characteristics of finished products with different normalizing technologies for Fe-3.15%Si low temperature hot rolled grain-oriented silicon steel are researched,a... 

【作者】 胡志强； 张文康； ...

6.5%Si硅钢具有优异的磁学性能和广泛的应用前景。本文综述了6.5%Si硅钢的物理、机械及磁学特性,讨论了传统轧制、温轧、薄带连铸、快速凝固、CVD、粉末轧制等不同制备工艺的关键技术及特点,概括了6.5%Si硅钢在高效节能电机、汽车马达及磁屏蔽等领域中的主要应用,介绍了硅钢的制备技术取得的研究进展,并指出了其广阔的发展前景。 6.5% Si silicon steel has good magnetic properties and wide applications.In this paper physical and mechanical magnetic properties were summarized,and key technology and characteristic of several preparation methods,such as traditional rolling,warm rolling,thin strip continuous casting,rapid solidification,CVD and powder rolling,were discussed.Main applications of 6.5% Si steel in the fields of high-efficiency electrical motors,automobile motors,transformer cores and magnetic shielding were gene... 

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... 

硅钢高温退火环形炉炉壳制作与安装精度要求较高,施工时通过对壳体原材料矫正、炉壳板拼焊、下料切割、型钢骨架组装及焊接、骨架及炉壳板矫正、骨架与炉壳板组装及焊接、炉壳矫正、零配件装置、定位钻孔、报验检查、出厂、内侧板安装、外侧板安装、顶板安装等环节的工艺技术控制,能保质高效地完成硅钢高温退火环形炉炉壳制作与安装,为以后同类工程的施工提供可借鉴经验。 The required precision of manufacture and installation technique of the silicon steel high temperature annealing annular-furnace shell is high.During construction , manufacture and installation of the silicon steel high temperature annealing annular-furnace shell could be finished high efficiently through correcting the raw materials of shell , furnace shell plate welding , material cutting , steel frame assembly and welding , skeleton and shell plate correction , skeleton and furnace shell asse... 

对高磁感取向硅钢冷轧板分别进行800、950、1050和1120℃不脱碳的预退火处理,在800℃预退火,成品的磁性能较好。织构分析的结果表明,随着预退火温度升高,初次再结晶后有利织构组分{111}<112>与不利织构组分(118)[110]的比值f(111)/f(118)逐渐降低,初次再结晶织构的变化是成品磁性的影响因素之一。 Preliminary annealing process at different temperatures for cold-rolled strips of a high permeability grain-oriented silicon steel was investigated to study the effect of the annealing temperature on microstructure and magnetic performance of the steel.Results show that the magnetic performances of the products annealed at 800 ℃ are best.Analysis of primary recrystallization texture indicates that with rising temperature,f(111)/f(118) which is the ratio of the favorable component {111}<112>... 

利用EBSD技术研究了电工钢中不同的柱状晶尺寸及退火工艺下{100}织构的演变规律。结果表明,初始晶粒尺寸的影响最显著。细小柱状晶热轧后经过常化处理,组织已均匀,但中心层有强{100}织构。粗大柱状晶中{100}织构的遗传性强,常化及中间退火后,中心层仍有粗大的以{100}取向为主的晶粒;脱碳退火后才能完成组织均匀化和织构梯度的弱化。常化时的升温速度也对织构演变存在影响,低的升温速度有利于{100}织构的保留,但升温速度的影响没有初始晶粒尺寸及退火次数的影响显著。细小柱状晶样品经过热轧及三次退火工艺适合制备取向电工钢。 Evolution of {100} texture of different columnar grains and annealing process was investigated in electrical steels with the help of EBSD technique.The results show that the effect of initial grain size is the strongest.The initial fine-grained specimen shows uniform microstructure after the normalizing process,while {100} grains appear preferentially in the central layer of sheets.The heredity of {100} texture in the initial coarse-grained specimen is more significant.{100} mainly-oriented coar... 

用还原分离-原子荧光光谱法分析了硅钢中的痕量汞.分析方法的不确定度主要来自测量重复性,样品溶液浓度,工作曲线变动性,标准溶液,移取、配制标准溶液,仪器变动性等.文章分别对上述构成合成不确定度大小的分量进行了计算讨论. Trace mercury in silicon steel and galvanized sheet was analyzed by adopting reduced separation-atomic fluorescence spectrometry.The uncertainty of the analysis method mainly comes from measurement repeatability,sample concentration,working curve volatility,standard solution,pipetting and preparation of standard solution,and instrument variability,etc.The essay conducted all calculations and discussions on the above components that determine uncertainty.