Chatter detection based on synchrosqueezing transform and statistical indicators in milling process

Chatter detection based on synchrosqueezing transform and statistical indicators in milling process Chatter is a self-excited vibration between the workpiece and tool. In view of the non-stationarity of the chatter signal, the synchrosqueezing transform (SST) is used to process vibration signals during cutting, which can enhance the energy ratio of chatter. In order to eliminate the interference of tooth passing frequency and its harmonics, a time-frequency filtering method is applied to filter these frequency components out. Then, the vibration signal is reconstructed by inverse SST and statistical indexes in time and frequency domains are calculated. The cutting tests are carried out to select statistical indexes which are sensitive to chatter. The effectiveness of the proposed method is verified with cutting tests, and the results show that the chatter can be detected successfully before severe chatter marks are left on the workpiece. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The International Journal of Advanced Manufacturing Technology Springer Journals

Chatter detection based on synchrosqueezing transform and statistical indicators in milling process

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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/s00170-017-1283-0
Publisher site
See Article on Publisher Site

Abstract

Chatter is a self-excited vibration between the workpiece and tool. In view of the non-stationarity of the chatter signal, the synchrosqueezing transform (SST) is used to process vibration signals during cutting, which can enhance the energy ratio of chatter. In order to eliminate the interference of tooth passing frequency and its harmonics, a time-frequency filtering method is applied to filter these frequency components out. Then, the vibration signal is reconstructed by inverse SST and statistical indexes in time and frequency domains are calculated. The cutting tests are carried out to select statistical indexes which are sensitive to chatter. The effectiveness of the proposed method is verified with cutting tests, and the results show that the chatter can be detected successfully before severe chatter marks are left on the workpiece.

Journal

The International Journal of Advanced Manufacturing TechnologySpringer Journals

Published: Nov 7, 2017

References

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