Detection of cutting tool wear using statistical analysis and regression model

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

Abstract

This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals. A statistical-based method called Integrated Kurtosis-based Algorithm for Z-Filter technique, called I-kaz was used for developing a regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out using a CNC turning machine Colchester Master Tornado T4 in dry cutting condition. A Kistler 9255B dynamometer was used to measure the cutting force signals, which were transmitted, analyzed, and displayed in the DasyLab software. Various force signals from machining operation were analyzed, and each has its own I-kaz 3D coefficient. This coefficient was examined and its relationship with flank wear lands (VB) was determined. A regression model was developed due to this relationship, and results of the regression model shows that the I-kaz 3D coefficient value decreases as tool wear increases. The result then is used for real time tool wear monitoring.

Original languageEnglish
Title of host publicationAIP Conference Proceedings
Pages249-259
Number of pages11
Volume1285
DOIs
Publication statusPublished - 2010
EventInternational MultiConference of Engineers and Computer Scientists, IMECS 2010 - Hong Kong
Duration: 17 Mar 201019 Mar 2010

Other

OtherInternational MultiConference of Engineers and Computer Scientists, IMECS 2010
CityHong Kong
Period17/3/1019/3/10

Fingerprint

statistical analysis
regression analysis
machining
coefficients
tornadoes
dynamometers
kurtosis
computer programs
filters

Keywords

  • I-kaz method
  • statistical analysis
  • tool wear detection

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Detection of cutting tool wear using statistical analysis and regression model. / A Ghani, Jaharah; Rizal, Muhammad; Nuawi, Mohd. Zaki; Che Haron, Che Hassan; Ramli, Rizauddin.

AIP Conference Proceedings. Vol. 1285 2010. p. 249-259.

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

A Ghani, J, Rizal, M, Nuawi, MZ, Che Haron, CH & Ramli, R 2010, Detection of cutting tool wear using statistical analysis and regression model. in AIP Conference Proceedings. vol. 1285, pp. 249-259, International MultiConference of Engineers and Computer Scientists, IMECS 2010, Hong Kong, 17/3/10. https://doi.org/10.1063/1.3510551
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