relation: https://khub.utp.edu.my/scholars/10449/
title: Wear Detection of Drill Bit by Image-based Technique
creator: Sukeri, M.
creator: Paiz Ismadi, M.Z.
creator: Othman, A.R.
creator: Kamaruddin, S.
description: Image processing for computer vision function plays an essential aspect in the manufacturing industries for the tool condition monitoring. This study proposes a dependable direct measurement method to measure the tool wear using image-based analysis. Segmentation and thresholding technique were used as the means to filter and convert the colour image to binary datasets. Then, the edge detection method was applied to characterize the edge of the drill bit. By using cross-correlation method, the edges of original and worn drill bits were correlated to each other. Cross-correlation graphs were able to detect the difference of the worn edge despite small difference between the graphs. Future development will focus on quantifying the worn profile as well as enhancing the sensitivity of the technique. © Published under licence by IOP Publishing Ltd.
publisher: Institute of Physics Publishing
date: 2018
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Sukeri, M. and Paiz Ismadi, M.Z. and Othman, A.R. and Kamaruddin, S.  (2018) Wear Detection of Drill Bit by Image-based Technique.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044511220&doi=10.1088%2f1757-899X%2f328%2f1%2f012011&partnerID=40&md5=7901e84187f19bf7edf58ca8ee70856f
relation: 10.1088/1757-899X/328/1/012011
identifier: 10.1088/1757-899X/328/1/012011