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- W2563875571 abstract "Dynamic instability in the form of chatter is a highly undesirable phenomenon that occurs during machining, resulting in poor surface finish and reduced tool life. Though analytical models exist for identifying conditions that avoid chatter, they do not account for process uncertainties or they require extensive cutting tests. Therefore, an on-line chatter detection algorithm is required to detect chatter before irreversible damage to the cutting tool or workpiece occurs. This paper evaluates the performance of three chatter detection algorithms in detecting chatter in the turning process with the eventual goal of developing embedded sensor-based process monitoring automation. Cutting force data are gathered from a number of turning scenarios with varying workpiece geometries. Of the chatter detection algorithms evaluated, spectral analysis is found to be the most robust and capable of detecting dynamic instability before tool or workpiece damage occurs." @default.
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- W2563875571 date "2016-08-01" @default.
- W2563875571 modified "2023-10-18" @default.
- W2563875571 title "Comparison of on-line chatter detection algorithms in turning" @default.
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- W2563875571 doi "https://doi.org/10.1109/isfa.2016.7790141" @default.
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