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Publication Detail
Crack detection in "as-cast" steel using laser triangulation and machine learning
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Publication Type:Conference
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Authors:Veitch-Michaelis J, Tao Y, Walton D, Muller JP, Crutchley B, Storey J, Paterson C, Chown A
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Publication date:29/12/2016
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Pagination:342, 349
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Published proceedings:Proceedings - 2016 13th Conference on Computer and Robot Vision, CRV 2016
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ISBN-13:9781509024919
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Status:Published
Abstract
© 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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