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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... 
2022-01-28 148 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... 
2014-03-28 140 5.8

研究二次冷轧压下率对于硅的质量分数为3.0%的无取向硅钢组织结构和磁性能的影响。结果表明:当第二次冷轧压下率从0变化至16.7%时,铁损逐渐增加,磁感逐渐降低。当第二次冷轧压下率大于16.7%时,随压下率的增加,铁损逐渐减小,磁感逐渐增加。当第二次冷轧压下率大于38%时,二次冷轧法所能获得的磁性能明显优于一次冷轧法。 Effect of double cold reduction on magnetic,microstructure and texture of 3.0% Si non-oriented silicon steel sheets was investigated.The results show that the iron loss increases and magnetic induction reduces as the percentage redcution in secondary cold rolling changes from 0 to 16.7%.The core loss can be reduced remarkably,and magnetic induction can get a little benefit if the percentage redcution in double cold reduction is higher 16.7%.In case of higher than 38% of the percentage redcution ... 
2012-11-28 144 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... 
2011-09-28 111 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... 
2014-02-28 154 5.8

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P1.5/50、高频铁损P1.0/400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... 
2022-05-28 168 5.8

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