An Industrial Vision System to analyze the Wear of Cutting Tools

نویسندگان

  • Christina Gillmann
  • Tobias Post
  • Benjamin Kirsch
  • Thomas Wischgoll
  • Jörg Hartig
  • Bernd Hamann
  • Hans Hagen
  • Jan C. Aurich
چکیده

The wear behavior of cutting tools directly affects the quality of the machined part. The measurement and evaluation of wear is a time consuming process and is subjective. Therefore, an image-based wear measurement that can be computed automatically based on given image series of cutting tools and an objective way to review the resulting wear is presented in this paper. The presented method follows the industrial vision system pipeline where images of cutting tools are used as input which are then transformed through suitable image processing methods to prepare them for the computation of a novel image based wear measurement. For multiple cutting tool settings a comparative visualization of the wear measurement outputs is presented. The effectiveness of the presented approach is shown by applying the method to measure the wear of four different cutting tool shapes.

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تاریخ انتشار 2017