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

Urs Bopp, Takao Sajima, Hiromichi Onikura

Research output: Contribution to journalArticle

Abstract

In the present research 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 Ra over drill life. The proposed measurement system, using colour image processing and an artificial neural network, can detect corner wear of a drill accurately and predict the surface roughness Ra of the hole to be drilled with mean and maximum errors of 0.32μm and -1.00μm, respectively. The presence of a built-up edge does not influence the results.

Original languageEnglish
Pages (from-to)1040-1044
Number of pages5
JournalSeimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering
Volume64
Issue number7
DOIs
Publication statusPublished - Jan 1 1998

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

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering

Cite this

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

In: Seimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering, Vol. 64, No. 7, 01.01.1998, p. 1040-1044.

Research output: Contribution to journalArticle

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