硅钢资料

在Gleeble-3500热/力模拟试验机上对HW600钢进行高温压缩试验,研究在不同试验条件下的变形抗力。试验结果表明:变形温度对变形抗力的影响最为显著,在相同的变形速率下,随着变形温度的升高,变形抗力降低;在同一变形温度下,变形速率增大,变形抗力增加;在同一变形温度、变形速率下,随着变形程度的增加,变形抗力急剧增大,真应变达到0.1后,变形抗力增加趋势变缓。 The high-temperature compression test is done for HW600 steel with Gleeble-3500 thermal simulation testing machine to research its resistance to deformation under different test conditions.It is showed from result that deformation temperature has greatest effect on the resistance,and along with the temperature getting higher the resistance lowered under same deformation rate;the resistance increases along with deformation rate getting greater under same temperature;and under same deformation tem... 

采用Nb对Fe-6.5%Si(质量分数)高硅钢进行微合金化处理,结果表明:Nb在高硅钢薄板制备过程中细晶效果明显.铸态、锻态和热轧态组织的晶粒分别细化了17.50%,24.51%和30.13%.铸态样品压缩强度由1365 MPa提高至1520 MPa,延伸率提高77.78%;温轧板试样室温拉伸强度由573 MPa提高至621 MPa,延伸率提高44.44%.利用XRD对厚度为0.30—1.68 mm的温轧板的板面织构演变过程进行跟踪测量,结果发现:初始织构以(011)〈100〉Goss织构为主,单道次变形量为26.2%的情况下,Goss织构完全转化为(100)〈011〉旋转立方织构,随后,在单道次变形为22.6%的情况下,旋转立方织构完全转化为{111}面织构,即纤维织构,并稳定保持至0.30 mm. Fe-6.5%Si（mass fraction） alloy possess perfect magnetic properties,though intermetallics of Fe₁₄Si₂ phase brought 6.5%Si leads to room temperature brittleness and hinder this significant materials industrialization.Nb was adopted into micro-alloying of Fe-6.5%Si high silicon steel. OM,thermal simulated test machine and XRD were employed to study the influence of Nb on high silicon steel in processing stages.Textures of warm-rolled high silicon steel strips were determined b... 

磁性能指标是硅钢产品最关键的质量指标之一，但是目前磁性能判定100%依赖于样品的离线实验室检测结果，生产线配置的在线检测仪的测量结果由于精度问题，不宜直接用于成品牌号判级。本文在现有硅钢产品质量管控体系基础上，利用大数据技术对生产数据进行分析与建模，构建不同磁性能指标在线检测模型，并在现有信息系统上完成模型库的集成部署，实现硅钢产品全长、多指标磁性能结果的拟合数据输出，支撑取样优化、精准分切、辅助综合判定等功能应用，进一步优化硅钢产品质量管控体系。 The magnetic performance index of silicon steel products is one of the most critical quality indexes.However,at present,100%determination of magnetic performance depends on the offline laboratory test results of samples,and the measurement results of the online detector configured in the production line cannot be applied in practice due to the accuracy problem.Based on the existing quality control system of silicon steel products,big data technology was used to analyze and model the production d... 

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...