Ultrasonic Time-Of-Flight Diffraction (TOFD) is a recent innovation that has proved highly effective for the inspection of steel plates and tubular pipelines and has started to take its way to replace the other ultrasonic testing techniques. TOFD technique has a lot of advantages which make it the preferable technique in material testing. This technique gives accurate sizing, positioning and characterising of weld and other defects with a high probability of detection. TOFD still suffers from the difficulties associated with the interpretation of the images. Feature analysis and shape detection have been applied to TOFD images. Combining the obtained features with an artificial intelligent system allows the full automation of the interpretation process. The results of an initial investigation are presented and discussed.


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    Titel :

    Automatic classification of defects in time-of-flight-diffraction data


    Weitere Titelangaben:

    Automatische Fehlerklassifikation mittels Laufzeitbeugungsdaten


    Beteiligte:
    Zahran, O. (Autor:in) / Al-Nuaimy, W. (Autor:in)


    Erscheinungsdatum :

    2004


    Format / Umfang :

    11 Seiten, 15 Bilder, 9 Quellen


    Anmerkungen:

    (Nicht paginiert)


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Datenträger


    Sprache :

    Englisch




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