Detecting transition to chatter mode in peakless tool turning by monitoring vibration and acoustic emission signals

Detecting transition to chatter mode in peakless tool turning by monitoring vibration and... Stability of a peakless tool turning on slender shafts was studied under conditions of low- and high-magnitude vibrations by registering and short-time Fourier transformation (STFT) processing of acoustic emission (AE) and vibration acceleration (VA) signals. Both VA and AE signals have been registered in three positions of the cutting tool on the workpiece and for different shaft diameters. Both amplitude- and frequency-dependent AE and VA characteristics were obtained and analyzed for overall process signal length as well as for single frames. It was shown that power spectrum characteristic could be used for monitoring the fast-occurring changes in the cutting process stability. A criterion of the cutting process stability based on the power spectrum has been offered. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The International Journal of Advanced Manufacturing Technology Springer Journals

Detecting transition to chatter mode in peakless tool turning by monitoring vibration and acoustic emission signals

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Publisher
Springer London
Copyright
Copyright © 2017 by Springer-Verlag London Ltd.
Subject
Engineering; Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design
ISSN
0268-3768
eISSN
1433-3015
D.O.I.
10.1007/s00170-017-1188-y
Publisher site
See Article on Publisher Site

Abstract

Stability of a peakless tool turning on slender shafts was studied under conditions of low- and high-magnitude vibrations by registering and short-time Fourier transformation (STFT) processing of acoustic emission (AE) and vibration acceleration (VA) signals. Both VA and AE signals have been registered in three positions of the cutting tool on the workpiece and for different shaft diameters. Both amplitude- and frequency-dependent AE and VA characteristics were obtained and analyzed for overall process signal length as well as for single frames. It was shown that power spectrum characteristic could be used for monitoring the fast-occurring changes in the cutting process stability. A criterion of the cutting process stability based on the power spectrum has been offered.

Journal

The International Journal of Advanced Manufacturing TechnologySpringer Journals

Published: Oct 13, 2017

References

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