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对取向硅钢在不同气氛下的高温退火工艺进行实验室模拟,利用X射线衍射仪(XRD)分析了硅钢退火至900℃和1170℃时的样品表面氧化层和底层的物相组成,采用场发射扫描电镜(SEM)观察了样品表面氧化层和底层在截面方向上的微观形貌特征,并计算了高温退火一次升温阶段氧化反应的吉布斯自由能以及900℃时退火气氛的氧分压。结果表明:当退火气氛的露点温度保持一定时,较高的氢气含量有利于生成完整连续的底层;当退火气氛的水氢分压比保持一定时,在露点温度与氢气含量两者较低的条件下,底层附着性不佳易脱落,较高条件下,底层中夹杂着较多的铁单质;当氧化层中无FeO时,底层完整连续但易脱落,当FeO层较薄时,底层下方存在部分未反应的SiO2,当FeO层较厚时,底层不完整连续且有分层。 The high temperature annealing process of grain-oriented silicon steel in different atmospheres was simulated in the laboratory. X-ray diffractometer(XRD) was used to analyze the phase compositions of the surface oxide layer and forsterite film of the silicon steel annealed to 900 ℃ and 1170 ℃. Field-emission scanning electron microscopy(SEM) was used to observe the micro morphology characteristics of the surface oxide layer and forsterite film of the samples in the cross section direction. The ... 
2022-12-28 219 5.8

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. 
2011-12-28 161 5.8

取向硅钢因其高磁导率、低矫顽力和大电阻系数等特性,被广泛应用于大中型变压器和大型电动机铁芯的制造。因取向硅钢性能和成分控制严格,生产工艺复杂,故其产品代表了钢铁企业特殊钢生产的最高水平。本文介绍了新钢公司卷板厂1580热连轧线生产取向硅钢过程中出现的窄尺问题,研究了取向硅钢产品的特点,分析了热轧过程中的组织转变,并结合生产实际提出了改进措施。通过对加热炉钢坯加热模式、粗轧轧制策略、精轧轧制工艺、二级模型等方面的优化和改进,取向硅钢窄尺情况明显好转,提高了产品的成材率和市场口碑。 The oriented silicon steel is widely used in the iron core manufacture of large and mediumsized transformers and large motors because of its high permeability, low coercivity and large resistance coefficient. Due to the performance and composition control of oriented silicon steel is strict, the production process is complex,therefore, its products represent the highest level of special steel production in iron and steel enterprises. This paper introduces the problem of narrow gauge in the produ... 
2022-06-28 188 5.8

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... 
2014-05-28 155 5.8

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... 
2011-09-28 132 5.8

采用拉伸试验和显微组织观测的方法确定了GTN损伤模型中的9个损伤参数,运用GTN损伤模型对冷轧硅钢薄板边部缺陷的扩展及边裂的产生进行了有限元模拟,并与预置缺口的钢板轧制试验进行对比。结果表明:轧制过程中边部缺陷是造成钢板边部裂纹萌生和扩展的一个重要原因,GTN损伤模型可用来预测含边部缺陷硅钢薄板在冷轧过程中边裂的产生;预测结果与试验结果基本一致。 The crack initiation and propagation of silicon steel strip with edge defect during cold rolling process was studied by using GTN damage model in this paper.Nine damage parameters in GTN model were identified by tensile testing and microstructure observing,and then the FE simulation of edge defect evolution of silicon steel strip during rolling process was conducted on the base of GTN damage model,and then the results were compared with rolling experimental results.The results show that the edge... 
2013-01-28 157 5.8

介绍在取向硅钢生产中抑制剂的作用以及多元抑制剂的机理和应用情况,分析多元抑制剂方案中各种元素对高磁感取向硅钢性能的影响,并根据生产实践提出了进一步研究的方向. The role of an inhibitor in the production of grain oriented silicon steel,and the mechanism of multiplex inhibitor in the production are described in the present article.In addition,the influence of various elements in the multiplex inhibitor on the performance of grain oriented silicon steel with high magnetic induction is elucidated.Further work needed in this research is also indicated. 
2013-01-28 157 5.8

【摘要】 <正>含6.5%Si的电工钢是软磁特性最佳的电...
2014-04-28 123 5.8

采用RH精炼添加钙合金方式对硅钢进行钙处理,结果表明,钙合金添加量为0.67、1.00和1.67 kg/t钢时,钢中Ca含量分别为0、2×10-6和4×10-(6质量分数);随着钙合金添加量的增加,钢中夹杂物粒度逐渐由0~2μm向2~4μm、4~6μm偏移;不同钙处理条件下,钢中均存在粒径小于1μm和粒径为1~5μm的MnS、CuxS夹杂物,后者或单独存在,或与AlN、CaS夹杂复合;钢中粒径为5~10μm的夹杂物基本以Ca的氧化物和硫化物为主。与未经钙处理的炉次相比,钙合金添加量为0.67、1.00和1.67 kg/t钢时,粒径小于1.0μm的夹杂物减少幅度分别为68.06%、87.50%和94.94%。钙合金添加量为1.67 kg/t钢时,可以去除钢中绝大部分的微细夹杂物。 In order to improve the properties of final silicon steels,the calcium treatment was adopted by adding Ca alloys into the liquid steel during the RH refining process.Results show that when the addition of Ca alloys is 0.67 kg/t,1.00 kg/t and 1.67 kg/t,the corresponding Ca content in silicon steels is 0,2 × 10-6 and 4 × 10-6 respectively.With the increase of Ca alloy addition,the particle sizes of inclusions in steels become 2~4 μm and 4~6 μm,from 0~2 μm.Under different calcium treatments,there e... 
2013-02-28 189 5.8

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... 
2022-01-28 170 5.8

在实验室试制了TSCR流程的低碳低硅无取向硅钢,研究了在850~1050℃不同温度常化对冷轧量0.5mm厚钢板再经950℃×7min退火后的组织、织构和磁性能的影响。结果表明:随常化温度的升高,使热轧板晶粒尺寸增大,晶界更清晰,组织均匀性更好;由于第二相AlN和MnS析出物尺寸比较大,使冷轧退火后钢板晶粒也随常化温度升高呈单调增大趋势;γ有利织构和{111}、{112}不利织构与常化温度升高同时增强,但前者增强更多;冷轧板退火后铁损随常化温度升高呈单调下降,磁感呈单调上升趋势。 The low-carbon and low-silicon non-oriented silicon steel was prepared by thin slab casting and rolling(TSCR) in lab.The effect of normalizing at different temperatures in 850-1 050℃on microstructure, texture and magnetic properties of 0.5 mm cold-rolled sheets after annealing at 950℃for 7 min was researched. The results show that with increasing the normalizing temperature,the grain size of hot-rolled sheets increased,the grain boundaries were more clear and the rnicrostructure uniformity was b... 
2011-03-28 165 5.8

试验2.3Si无取向硅钢(/%:0.003C,2.30Si,0.16Mn,≤0.020P,≤0.005S,0.54Al)冷轧板由常化和未常化的2.5 mm热轧板冷轧至0.6 mm(压下率76%),经750~950℃2.5 min中间退火后再冷轧至0.5 mm(压下率16.7%),成品板经890℃+960℃2.5 min退火。研究了中间退火温度对该钢晶粒尺寸、织构和磁性能的影响。结果表明,随中间退火温度的升高,二次冷轧前晶粒和成品晶粒增大,成品中不利织构组分{111}和{112}减弱,磁性能得到改善。热轧板经过常化时的磁性能明显好于未经常化时的磁性能,但中间退火温度较高时常化对磁性能的有利作用减弱。 The test cold sheet of 2.3Si non-oriented silicon steel(/%:0.003C,2.30Si,0.16Mn,≤0.020P,≤0.005S,0.54Al) is first cold-rolled from normalized and un-normalizing 2.5 mm hot-rolled plate to 0.6 mm sheet(reduction 76%),then intermediate annealed at 750~950℃ for 2.5 min and double cold-rolled to 0.5 mm sheet(reduction16.7%),the finished sheet annealed at 890℃+960℃ for 2.5 min.Effect of the intermediate annealing temperature on grain size,texture and magnetic performance of the steel has been studied.... 
2014-02-28 178 5.8

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