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Statistical analysis of EBSD data to predict potential abnormal grain growth in 3.0 wt% Si grain-oriented electrical steel
Materials Characterization ( IF 4.7 ) Pub Date : 2020-09-01 , DOI: 10.1016/j.matchar.2020.110450 Seil Lee , Kyung Jun Ko , Se-Jong Kim , Jong Tae Park
Materials Characterization ( IF 4.7 ) Pub Date : 2020-09-01 , DOI: 10.1016/j.matchar.2020.110450 Seil Lee , Kyung Jun Ko , Se-Jong Kim , Jong Tae Park
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Abstract The role of grain topology as a predictor on abnormal grain growth (AGG) of primary recrystallized silicon steel sheet has been investigated by EBSD technique. Goss oriented grains in the primary recrystallized silicon steel sheet were observed to have larger grain sizes than average matrix grains. The average grain size of grains with the smallest deviation angle (
中文翻译：
EBSD 数据的统计分析以预测 3.0 wt% Si 取向电工钢中潜在的异常晶粒生长
摘要 通过EBSD 技术研究了晶粒拓扑结构作为一次再结晶硅钢板异常晶粒生长(AGG) 预测因子的作用。观察到一次再结晶硅钢板中的高斯取向晶粒具有比平均基体晶粒更大的晶粒尺寸。偏角最小的晶粒的平均晶粒尺寸（
更新日期：2020-09-01
中文翻译：
EBSD 数据的统计分析以预测 3.0 wt% Si 取向电工钢中潜在的异常晶粒生长
摘要 通过EBSD 技术研究了晶粒拓扑结构作为一次再结晶硅钢板异常晶粒生长(AGG) 预测因子的作用。观察到一次再结晶硅钢板中的高斯取向晶粒具有比平均基体晶粒更大的晶粒尺寸。偏角最小的晶粒的平均晶粒尺寸（
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