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Publication Detail
Crack detection in "as-cast" steel using laser triangulation and machine learning
  • Publication Type:
  • Authors:
    Veitch-Michaelis J, Tao Y, Walton D, Muller JP, Crutchley B, Storey J, Paterson C, Chown A
  • Publication date:
  • Pagination:
    342, 349
  • Published proceedings:
    Proceedings - 2016 13th Conference on Computer and Robot Vision, CRV 2016
  • ISBN-13:
  • Status:
© 2016 IEEE. We describe a high-accuracy inspection system designed to automatically detect cracks in "as-cast" steel slabs. Real-time slab inspection requires instrumentation capable of withstanding high temperatures above the steel surface as well as coping with the dirty and dusty environment present in a steel mill. Crack detection is also challenging due to the presence of oxidation scale on the slab surface. A bespoke laser triangulation system has been developed, providing images at 250 fps with a calibrated surface resolution of 97 μm from a 1m standoff distance. Cracks are detected using a combination of morphological detection and SVM classifier. Results are reported from laboratory testing and from extended trials at a production steel mill.
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