Paper
8 March 2002 Machine vision prototype for defect detection on metallic tubes
Fabrice Meriaudeau, Gerald Lavallee, Eric Fauvet
Author Affiliations +
Proceedings Volume 4664, Machine Vision Applications in Industrial Inspection X; (2002) https://doi.org/10.1117/12.460197
Event: Electronic Imaging, 2002, San Jose, California, United States
Abstract
Metallurgy Industry which mainly changes the steel or its derivative products into products with either better surface properties (thanks to the surface transformations....), or into different shape products (lamination...), involves some processing tools which can generate flaws (cracks, grooves...) within the process. Prior to this study the laminated tubes, recipient for the uranium inside the nuclear reactor, where visually inspected after the lamination process. According to the quality estimation of the tube, subjectively done by the operator (between 1 and 4), the process was possibly stopped (grade 4). In order to have a more objective control of the tube, a machine vision set-up was developed. The primary goal of this prototype is to provide a view of the whole surface of the tube to the operator. Various lighting systems where tested so as to reveal the maximum number of defect (tool marks, scratches, ..). The tube surface being not even (rough), we found that an homogenous lighting of the scene enabled a clear inspection of the tube surface and reveal most of the defects. Unfortunately a structured lighting system was also required for the tool-marks to be visible. Then, different image processing tools have been applied to the images. At this point, all the defects are detected. Further experiments are currently being done to classify the defects.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Fabrice Meriaudeau, Gerald Lavallee, and Eric Fauvet "Machine vision prototype for defect detection on metallic tubes", Proc. SPIE 4664, Machine Vision Applications in Industrial Inspection X, (8 March 2002); https://doi.org/10.1117/12.460197
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Cited by 3 scholarly publications.
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KEYWORDS
Light sources and illumination

Defect detection

Machine vision

Inspection

Prototyping

Optical inspection

Visualization

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