Assessment of Porosity Defects in Ingot Using Machine Learning Methods during Electro Slag Remelting Process

Assessment of Porosity Defects in Ingot Using Machine Learning Methods during Electro Slag Remelting Process

The porosity defects in the ingot, which are caused by moisture absorption in slag during the electroslag remelting process, deserve the researcher’s attention in the summer wet season. The prediction of slag weight gain caused by moisture absorption is critical for developing slag baking and schedu...

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Hlavní autoři: Ganggang Zhang, Yingbin Hu, Dong Hou, Dongxuan Yang, Qingchuan Zhang, Yapeng Hu, Xinliang Liu
Médium: Článek
Jazyk:English
Vydáno: MDPI AG 2022-06-01
Edice:Metals
Témata:
electroslag remelting
slag moisture absorption
machine learning
SVR
ingot porosity defects
On-line přístup:https://www.mdpi.com/2075-4701/12/6/958

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https://www.mdpi.com/2075-4701/12/6/958

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