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JKSPE : Journal of the Korean Society for Precision Engineering

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"영상센서"

Article
Vision Based On-Machine Measurement of Flank Wear in Drill Tool for Smart Machine Tool
Tae-Gon Kim, Kangwoo Shin, Seok-Woo Lee
J. Korean Soc. Precis. Eng. 2018;35(2):145-149.
Published online February 1, 2018
DOI: https://doi.org/10.7736/KSPE.2018.35.2.145
Tool wear is an essential parameter in determining tool life, machining quality and productivity. Current or power signals from motor drivers in machine have been used to estimate tool wear. However, accuracy of tool wear estimation was not enough to measure the amount of tool wear. In this study, flank wear of a drill tool was measured using vision sensor module which has zoom lens, CCD camera and image processing technique. The vision module was set up in the machine tool. Therefore, the image was acquired without ejecting the tool from the machine. Image processing techniques were used to define the cutting edge shape, tool diameter, and the wear edge on cutting rips with the proposed measuring algorithm. The automatically calculated wear value was compared with a manually measured value. As a result, the difference between the manual and the automatic methods was below 4.7%. The proposed method has an advantage to decrease the measuring time and improve measuring repeatability because the tool is measured holding chuck in a spindle.
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