Largest-extreme-value distribution analysis of multiple inclusion types in determining steel cleanliness
Largest-extreme-value distribution analysis of multiple inclusion types in determining steel cleanliness
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DOI：
10.1007/s11663-001-0036-4
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发表时间：
2001-06-01
影响因子：
3
通讯作者：
Murakami, Y
中科院分区：
文献类型：
--
作者：
Beretta, S;Murakami, Y
需要新的夹杂物评级方法来评估现代钢的清洁度并预测部件中最大缺陷的特征尺寸。这些关键任务可能非常困难，因为存在不同的夹杂物类型。因此，必须开发新的统计工具来解决这些问题。本文提出了一种分析极端缺陷的新方法，并成功地应用于不同类型的多夹杂钢。特别是，分析，这使得不同的夹杂物的相对密度的评估，是基于对不同的控制区域进行夹杂物取样。
There is the need for new inclusion rating methods able to assess the cleanliness of modern steel and to predict the characteristic size of maximum defects in a component. These critical tasks can be extremely difficult, because of the presence of different inclusion types. Therefore, new statistical tools have to be developed for addressing these problems. A new method for the analysis of extreme defects is proposed in this article and is successfully applied to different steels containing multiple inclusions. In particular, the analysis, which allows the assessment of the relative density of the different inclusions, is based on inclusion samplings carried out on different control areas.