Weak chatter detection in milling based on sparse dictionary

Chenxi Wang, Xingwu Zhang, Xuefeng Chen, Ruqiang Yan, Peng Wang

Research output: Contribution to journalConference articlepeer-review

6 Scopus citations

Abstract

As one of the most unfavorable factors in milling, chatter will lead to poor surface quality, low production efficiency and tool life reduction. Chatter detection, especially weak chatter detection, is an effective way to ensure stable cutting. In this work, the milling dynamic responses based weak chatter detection method is put forward using sparse dictionary. Based on the milling dynamic equations, chatter frequencies are calculated and verified, which are the bases for chatter detection. With the calculated chatter frequencies, the sparse dictionary matrix can be constructed and the orthogonal matching pursuit (OMP) algorithm is adopted for chatter frequencies reconstruction. The proposed method can extract weak chatter frequencies accurately. Experimental results shows that the proposed method can be successful in weak chatter identification.

Original languageEnglish
Pages (from-to)839-843
Number of pages5
Journal48th SME North American Manufacturing Research Conference, NAMRC 48
Volume48
DOIs
StatePublished - 2020
Event48th SME North American Manufacturing Research Conference, NAMRC 48 - Cincinnati, United States
Duration: Jun 22 2020Jun 26 2020

Bibliographical note

Publisher Copyright:
© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Keywords

  • Milling
  • OMP algorithm
  • Sparse dictionary
  • Weak chatter identification

ASJC Scopus subject areas

  • Artificial Intelligence
  • Industrial and Manufacturing Engineering

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