Sam St. John
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View article: 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 Open
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…
View article: 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 Open
Chatter, a self-excited vibration phenomenon, is a critical challenge in high-speed machining operations, affecting tool life, surface quality, and overall process efficiency. While ML models trained on simulated data have shown promise in…
View article: Chatter Detection in Simulated Machining Data: A Simple Refined Approach to Vibration Data
Chatter Detection in Simulated Machining Data: A Simple Refined Approach to Vibration Data Open
Vibration monitoring is a critical aspect of assessing the health and performance of machinery and industrial processes. This study explores the application of machine learning techniques, specifically the Random Forest (RF) classification…