Real- Time evaluation of tool wear detection system under wet machining based on electrical contact resistance

Amine Gouarir, Syuhei Kurokawa, Takao Sajima, Mitsuaki Murata

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

Abstract

This study presents a real- Time evaluation of tool flank wear detection system under wet machining based on electrical contact resistance. The developed tool wear detection system based on DC two terminal method uses the contact resistance between the tool and workpiece as a signal gauge to observe the progression of the tool wear during the cutting process. The contact resistance decreases as the increase of the flank wear contact area. Meanwhile, the influence of the thermo-electromotive force (E.M.F) is also measured and considered during the detection process. In the previous experiment, the target was the detection of the tool wear in face milling process, and also for uncoated solid square end mill by using a contact mercury transmission system. In this experiment, all attentions were focused on the new transmission system which is based on slip ring. The results of the experiment using the new slip ring transmission system on the present tool wear detection system based on DC two terminal method, demonstrates that the wear detection of the square end mill with indexable inserts has been done successfully under wet machining which was not possible in the previous system due to the isolation problem.,.

Original languageEnglish
Title of host publicationProceedings of the 16th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2016
Publishereuspen
ISBN (Electronic)9780956679086
Publication statusPublished - 2016
Event16th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2016 - Nottingham, United Kingdom
Duration: May 30 2016Jun 3 2016

Other

Other16th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2016
CountryUnited Kingdom
CityNottingham
Period5/30/166/3/16

All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Environmental Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Instrumentation

Fingerprint Dive into the research topics of 'Real- Time evaluation of tool wear detection system under wet machining based on electrical contact resistance'. Together they form a unique fingerprint.

Cite this