A Novel Multi-Task Learning Model with PSAE Network for Simultaneous Estimation of Surface Quality and Tool Wear in Milling of Nickel-Based Superalloy Haynes 230

For data-driven intelligent manufacturing, many important in-process parameters should be estimated simultaneously to control the machining precision of the parts. However, as two of the most important in-process parameters, there is a lack of multi-task learning (MTL) model for simultaneous estimat...

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Detalles Bibliográficos
Autores principales: Cheng, Minghui, Jiao, Li, Yan, Pei, Gu, Huiqing, Sun, Jie, Qiu, Tianyang, Wang, Xibin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269817/
https://www.ncbi.nlm.nih.gov/pubmed/35808436
http://dx.doi.org/10.3390/s22134943

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269817/
https://www.ncbi.nlm.nih.gov/pubmed/35808436
http://dx.doi.org/10.3390/s22134943

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