Machine based three-dimensional (3D) object defect detection

    公开(公告)号:US11189021B2

    公开(公告)日:2021-11-30

    申请号:US16685848

    申请日:2019-11-15

    Abstract: Implementations describe systems and methods for machine based defect detection of three-dimensional (3D) printed objects. A method of one embodiment of the disclosure includes providing a first illumination of a 3D printed object using a first light source arrangement. A plurality of images of the 3D printed object are then generated using one or more imaging devices. Each image may depict a distinct region of the 3D printed object. The plurality of images may then be processed by a processing device using a machine learning model trained to identify one or more types of manufacturing defects of a 3D printing process. The machine learning model may provide a probability that an image contains a manufacturing defect. The processing device may then determine, without user input, whether the 3D printed object contains one or more manufacturing defects based on the results provided by the machine learning model.

    MACHINE BASED THREE-DIMENSIONAL (3D) OBJECT DEFECT DETECTION

    公开(公告)号:US20220036531A1

    公开(公告)日:2022-02-03

    申请号:US17370966

    申请日:2021-07-08

    Abstract: Systems and methods for machine based defect detection of 3D printed molds for orthodontic aligners are described. A method includes providing illumination of a 3D printed mold for an orthodontic aligner; generating a plurality of images of the 3D printed mold for the orthodontic aligner using one or more imaging devices, wherein each image of the plurality of images depicts a distinct region of the 3D printed mold for the orthodontic aligner; processing the plurality of images by a processing device to identify one or more types of manufacturing defects of the 3D printed mold for the orthodontic aligner, wherein for each type of manufacturing defect a probability that an image comprises a defect of that type of manufacturing defect is determined; and classifying, by the processing device, the 3D printed mold for the orthodontic aligner as defective based on identifying the one or more types of manufacturing defects.

    MACHINE BASED THREE-DIMENSIONAL (3D) OBJECT DEFECT DETECTION

    公开(公告)号:US20200160497A1

    公开(公告)日:2020-05-21

    申请号:US16685848

    申请日:2019-11-15

    Abstract: Implementations describe systems and methods for machine based defect detection of three-dimensional (3D) printed objects. A method of one embodiment of the disclosure includes providing a first illumination of a 3D printed object using a first light source arrangement. A plurality of images of the 3D printed object are then generated using one or more imaging devices. Each image may depict a distinct region of the 3D printed object. The plurality of images may then be processed by a processing device using a machine learning model trained to identify one or more types of manufacturing defects of a 3D printing process. The machine learning model may provide a probability that an image contains a manufacturing defect. The processing device may then determine, without user input, whether the 3D printed object contains one or more manufacturing defects based on the results provided by the machine learning model.

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