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Data-driven casting defect prediction model for sand casting based on random forest classification algorithm

Bang Guan Dong-hong Wang Da Shu Shou-qin Zhu Xiao-yuan Ji Bao-de Sun

China Foundry2024，Vol.21Issue(2)：P.137-146,10.

China Foundry2024，Vol.21Issue(2)：P.137-146,10.DOI:10.1007/s41230-024-3090-1

Data-driven casting defect prediction model for sand casting based on random forest classification algorithm

Bang Guan ¹Dong-hong Wang ²Da Shu ²Shou-qin Zhu ³Xiao-yuan Ji ⁴Bao-de Sun²

作者信息

1. Shanghai Key Lab of Advanced High-Temperature Materials and Precision Forming,School of Materials Science and Engineering,Shanghai Jiao Tong University,Shanghai 200240,China
2. Shanghai Key Lab of Advanced High-Temperature Materials and Precision Forming,School of Materials Science and Engineering,Shanghai Jiao Tong University,Shanghai 200240,China State Key Lab of Metal Matrix Composites,Shanghai Jiao Tong University,Shanghai 200240,China
3. Hefei Casting and Forging Factory of Anhui Heli Co.,Ltd,Hefei 230000,China
4. State Key Laboratory of Materials Processing and Die&Mould Technology,Huazhong University of Science and Technology,Wuhan 430074,China
折叠

摘要

关键词

sand casting process/data-driven method/classification model/quality prediction/feature importance

分类

信息技术与安全科学

引用本文复制引用

Bang Guan,Dong-hong Wang,Da Shu,Shou-qin Zhu,Xiao-yuan Ji,Bao-de Sun..Data-driven casting defect prediction model for sand casting based on random forest classification algorithm[J].China Foundry,2024,21(2):P.137-146,10.

基金项目

financially supported by the National Key Research and Development Program of China(2022YFB3706800,2020YFB1710100) （2022YFB3706800,2020YFB1710100）

the National Natural Science Foundation of China(51821001,52090042,52074183)。（51821001,52090042,52074183）

China Foundry

OACSTPCDEI

ISSN：1672-6421

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