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Acoustic monitoring of tool wear state with limited samples based on time-series generative adversarial network

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Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Volume 240, Issue 6-7, Page 919-936, May 2026.
Tool wear is unavoidable for mechanical manufacturing. The accurate tool wear prediction can reduce production costs, enhance production efficiency, and facilitate high-quality production. Acoustic monitoring using microphones is a reliable, efficient, ...