Transitioning from Simulation to Reality: Applying Chatter Detection Models to Real-World Machining Data

Transitioning from Simulation to Reality: Applying Chatter Detection Models to Real-World Machining Data

Chatter, a self-excited vibration phenomenon, is a critical challenge in high-speed machining operations, affecting tool life, product surface quality, and overall process efficiency. While machine learning models trained on simulated data have shown promise in detecting chatter, their real-world ap...

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Detalles Bibliográficos
Autores principales: Matthew Alberts, Sam St. John, Simon Odie, Anahita Khojandi, Bradley Jared, Tony Schmitz, Jaydeep Karandikar, Jamie B. Coble
Formato: Artículo
Lenguaje:English
Publicado: MDPI AG 2024-12-01
Colección:Machines
Materias:
real world
predictive analytics
vibration analysis
chatter
stability
Acceso en línea:https://www.mdpi.com/2075-1702/12/12/923

Internet

https://www.mdpi.com/2075-1702/12/12/923

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