Automatic drill wear measurement using colour image processing and artificial neural network

Urs Bopp, Takao Sajima, Hiromichi Onikura

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

The corner wear of drills is measured automatically in order to predict end of drill life, using hole quality as criterion. Drilling experiments show a strong correlation between the progress of maximum hole diameter and hole surface roughness Rα over drill life. The proposed measurement system uses colour image processing and an artificial neural network. It can detect the corner wear of a drill accurately and predict the surface roughness Rα of the hole to be drilled with mean and maximum errors of 0.32pm and -1.00μm, respectively. The presence of a built-up edge does not influence the measurement results.

Original languageEnglish
Pages (from-to)287-292
Number of pages6
JournalInternational Journal of the Japan Society for Precision Engineering
Volume31
Issue number4
Publication statusPublished - Dec 1997

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Color image processing
Wear of materials
Neural networks
Surface roughness
Drilling
Experiments

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Automatic drill wear measurement using colour image processing and artificial neural network. / Bopp, Urs; Sajima, Takao; Onikura, Hiromichi.

In: International Journal of the Japan Society for Precision Engineering, Vol. 31, No. 4, 12.1997, p. 287-292.

Research output: Contribution to journalArticle

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