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介绍了普通取向硅钢(CGO)和高磁感取向硅钢(Hi-B)铸坯高温加热两次冷轧、一次冷轧和铸坯低温加热两次冷轧、一次冷轧法4种成熟生产工艺的主要技术参数,取向硅钢理论研究(Goss晶核和抑制剂)和生产技术现状。取向钢的发展趋势为:提高(110)[001]晶粒取向度,降低取向硅钢铁损,发展铸坯低温加热(≤1 300℃)和薄板坯连铸连轧流程生产取向硅钢工艺。 Main technology parameters of four developed process:cast bloom higher temperature heating-double cold rolling or single cold rolling,lower temperature heating-double cold rolling or single rolling process for production of common grain oriented silicon steel(CGO) and high magnetic induction grain oriented silicon steel(Hi-B),theory research on grain oriented steel(Goss nucleus and inhibitor) and present situation of process are summarized in this paper.The development trend of grain oriented si... 
2013-05-28 82 5.8

阐述了国内外高磁感取向硅钢的生产研究水平与发展趋势,包括通过提高高斯晶粒取向度、细化磁畴、涂覆张力涂层、减薄钢片厚度进一步降低铁损以及低温加热技术和短流程技术新工艺。分析高磁感取向硅钢在我国大型电力变压器上的应用情况,结果表明,发展更薄规格高磁感、低铁损、低磁致伸缩取向硅钢可为大型变压器的安全性、节能性及环保性提供有效保障。 The research progress and development trend of high magnetic induction grain-oriented silicon steel at home and abroad are summarized,including the technology of improving the Goss alignment,refining domain wall,adding stress coating,decreasing thickness of sheet,and the new technique of reducing heating temperature of casting slab and shortening operational.Moreover,the application of high magnetic induction grain-oriented silicon in power transformer is presented.Developing grain-oriented sili... 
2014-11-28 98 5.8

本文介绍了无取向硅钢C6涂液的性能,研究了配水量、固化程度和涂层厚度等因素对无取向硅钢C6涂层性能的影响。结果表明,随着配水量的增加,完全固化所需的时间增加,涂液固体含量降低,涂层厚度减小;随着固化程度的提高,涂层硬度先增大然后趋于恒定,而柔韧性逐渐变差,在过固化后急剧恶化;涂层厚度对涂层的表面外观、附着性和绝缘层间电阻均有显著影响。 Based on the introduction about the performance of C6 varnish for non-oriented silicon steel sheets,effects of water amount,curing degree and coating thickness are discussed. Results show that with the increase of water amount,the time required to cure completely extends,and both the solid content of C6 varnish and the coating thickness decrease. As the curing degree increases,the hardness of the coating increases first and then tends to be constant,however the flexibility degenerates,especially... 
2014-02-28 75 5.8

冷轧无取向硅钢(/%:0.003C,2.35Si,0.22Mn,0.011P,0.002S,0.36A1,0.003 0N)经890℃或940℃3 min常化的2.3 mm热轧板冷轧成0.35 mm薄板。研究了常化温度和800920℃3 min退火对该钢高频(400Hz)磁性能和抗拉强度的影响。结果表明,830920℃退火时高频铁损P10/400值最低,随退火温度增加,晶粒尺寸增大,钢的抗拉强度降低;该钢的最佳热处理工艺为常化温度940℃,退火温度830℃,其抗拉强度Rm、高频铁损P10/400和磁感应强度J50分别为565 MPa,21.5 W/kg和1.69 T。 The cold-rolled non-oriented silicon steel(/%:0.003C,2.35Si,0.22Mn,0.011P,0.002S,0.36A1,0.003 0N) is cold-rolled to 0.35 mm sheet from 2.3 mm hot-rolled plate normalized at 890 ℃ or 940℃ for 3 min.The effect of normalizing temperature and annealing process at 800 920 °C for 3 min on high frequency(400 Hz) magnetic properties and tensile strength of the steel has been tested and studied.Results show that with annealing at 830 920 ℃the high frequency iron loss value P10... 
2014-03-28 69 5.8

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... 
2022-01-28 80 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 50 5.8

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