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  2. Ball Screw Drive Surface Defect Dataset for Classification
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    Datenpaket: Ball Screw Drive Surface Defect Dataset for Classification

    Alternativer Identifier:
    (KITopen-DOI) 10.5445/IR/1000133819
    Verwandter Identifier:
    -
    Ersteller/in:
    Schlagenhauf, Tobias [Schlagenhauf, Tobias]
    Beitragende:
    -
    Titel:
    Ball Screw Drive Surface Defect Dataset for Classification
    Weitere Titel:
    -
    Beschreibung:
    (Abstract) The dataset contains of 21835 150x150 Pixel RGB images of the surface of Ball Screw Drives. 11075 of these images are images without surface defects whereas the rest shows images with surface defects in form of so called pittings. So the dataset is evenly split over the classes. Pittings result from surface disruption and can ultimately lead to the breakdown of the component. To keep the availability of machines high it is important to find surface defects in time. The here presented dataset gives researchers and practitioners the possibility to train and test models for the classification of surface defects on machine tool elements.
    (Technical Remarks) Images including *_ in the name are rotated by 90°. This originates from the process of image acquisition and does not harm the quality of the dataset but can be seen as a data augmentation technique. This can be reversed. Images with "N" in the file name are images without defect whereas images with "P" in the file name are images showing Pittings.
    Schlagworte:
    Condition Monitoring
    Surface Inspection
    Dataset
    Machine Learning
    Classification
    Mechanical Engineering
    Zugehörige Informationen:
    -
    Sprache:
    -
    Herausgeber/in:
    Karlsruhe Institute of Technology
    Erstellungsjahr:
    Fachgebiet:
    Engineering
    Objekttyp:
    Dataset
    Datenquelle:
    -
    Verwendete Software:
    -
    Datenverarbeitung:
    -
    Erscheinungsjahr:
    Rechteinhaber/in:
    Schlagenhauf, Tobias
    Förderung:
    -
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    Status:
    Publiziert
    Eingestellt von:
    kitopen
    Erstellt am:
    Archivierungsdatum:
    2023-06-23
    Archivgröße:
    685,9 MB
    Archiversteller:
    kitopen
    Archiv-Prüfsumme:
    68631d160b7780c8dee415faa3d111f3 (MD5)
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