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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Bibliographic Details
Main Authors: Ganggang Zhang, Yingbin Hu, Dong Hou, Dongxuan Yang, Qingchuan Zhang, Yapeng Hu, Xinliang Liu
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Metals
Subjects:
electroslag remelting
slag moisture absorption
machine learning
SVR
ingot porosity defects
Online Access:https://www.mdpi.com/2075-4701/12/6/958

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