Machine learning for workpiece mass prediction using real and synthetic acoustic data

Abstract We apply a feedforward neural network using supervised learning to sound recordings obtained without specialised equipment as workpieces undergo a simple manufacturing process to predict their mass. We also report a simple technique to seed synthetic from real data for training and testing...

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Bibliographic Details
Main Authors: D. S. Whittaker, J. Gregório, T. F. Byrne
Format: Article
Language:English
Published: Nature Portfolio 2025-06-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-03018-3
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