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

A. V. Filippov, V. E. Rubtsov, S. Y. Tarasov, O. A. Podgornykh, N. N. Shamarin

Research output: Contribution to journalArticle

9 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalInternational Journal of Advanced Manufacturing Technology
DOIs
Publication statusAccepted/In press - 13 Oct 2017

Fingerprint

Acoustic emissions
Vibrations (mechanical)
Power spectrum
Monitoring
Cutting tools
Processing

Keywords

  • Acoustic emission
  • Chatter
  • Peakless tool turning
  • Precision
  • Vibration

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

Cite this

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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.",
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T1 - Detecting transition to chatter mode in peakless tool turning by monitoring vibration and acoustic emission signals

AU - Filippov, A. V.

AU - Rubtsov, V. E.

AU - Tarasov, S. Y.

AU - Podgornykh, O. A.

AU - Shamarin, N. N.

PY - 2017/10/13

Y1 - 2017/10/13

N2 - 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.

AB - 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.

KW - Acoustic emission

KW - Chatter

KW - Peakless tool turning

KW - Precision

KW - Vibration

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