硅钢资料

借助OM、激光共聚焦显微镜、质谱仪和电解萃取等设备和方法，研究了添加微量稀土La（质量分数0.001 1%）的取向硅钢在轧制前采用不同加热保温时间对抑制剂固溶行为的影响。结果表明：当稀土取向硅钢在1 250℃分别保温10、20、30 min后，试验钢晶粒尺寸随保温时间延长有先快后慢的长大趋势；三种抑制剂元素Mn、Cu和Al均发生固溶，保温时间对Mn和Cu两种元素的固溶影响明显，固溶量分别由69.8%和43.7%增加至84.2%和85.2%；随着保温时间的延长，稀土取向硅钢中抑制剂的小尺寸未溶物逐渐减少直至消失，较大尺寸未溶物（300～600 nm）逐渐转变为小尺寸未溶物逐步溶入基体中，数量减少且未溶物的类型由复杂逐渐转变为单一。 In this paper the solid solution behavior of the inhibitor under various holding time in 0.001 1 %La oriented silicon steel during reheating had been investigated by using OM, LM, methods of electrolytic extraction and mass spectrometer. The results showed that grain size of the test steel increased significantly with the holding time prolonging when the rare earth oriented silicon steel was heated to1 250 ℃ and held for 10, 20 min and 30 min respectively, and the growth trend slowed down after ... 

针对宝钢硅钢常化退火过程中产生的退火炉辊印缺陷问题,通过实际生产的大数据与产品质量问题相结合,将数据挖掘、数据分析方法应用到实际,一定程度上解决了现场实际生产中的痛点,为现场生产提供决策支撑,避免了以前通过人工识别判定存在疏漏和无法定量判断的问题,形成了一套具有鲁棒性和可操作性的钢铁生产过程数据分析方法。通过智慧决策系统平台获取实际生产和表检仪数据,基于Pearson相关系数算法进行变量挑选和特征工程,并应用随机森林算法对数据建立分类预测模型,实现了质量问题的溯源和监控,通过数据量化预测了炉辊印缺陷是否可通过轧制消除的质量问题,识别准确率达到96.43%。 In views of the normalizing annealing furnace roll marks problem occurred in the process of normalizing annealing of silicon steel in Baosteel,by combining big data from actual production with product quality problems,data mining and data analysis methods were applied to actual production to solve the pain points and provide decision support,a robust and practical data analysis method for the steel production process has been developed,which avoided the previous problems of omission and non-quan...