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Autoencoders for learning latent information of cutting tool health

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Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, Ahead of Print.
This article presents an unsupervised method for monitoring the health of cutting tools in precision machining processes. The method is developed and validated using the IEEE PHM 2010 data, which comprises three sets of cutting tool run-to-failure tests. ...