An on-line tool wear monitoring method based on cutting power

Teng Wan, Xingzheng Chen, Congbo Li, Ying Tang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In a CNC batch process, excessive tool wear will lead to a bad surface quality of the final product. On-line tool wear monitoring is recognized as an effective method to reduce the impact of the tool wear on surface quality. In this paper, a cutting power model is firstly established with the consideration of tool wear and cutting parameters. A novel on-line tool wear monitoring approach for CNC batch processing is then proposed and a monitoring system is developed. Result of the case study shows that the proposed approach is effective in tool wear on-line monitoring.

Original languageEnglish (US)
Title of host publication2018 IEEE 14th International Conference on Automation Science and Engineering, CASE 2018
PublisherIEEE Computer Society
Pages205-210
Number of pages6
ISBN (Electronic)9781538635933
DOIs
StatePublished - Dec 4 2018
Event14th IEEE International Conference on Automation Science and Engineering, CASE 2018 - Munich, Germany
Duration: Aug 20 2018Aug 24 2018

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2018-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Other

Other14th IEEE International Conference on Automation Science and Engineering, CASE 2018
Country/TerritoryGermany
CityMunich
Period8/20/188/24/18

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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