AUTOMATED LIQUID ADHESIVE DISPENSING USING PORTABLE MEASURING DEVICE

    公开(公告)号:US20240075495A1

    公开(公告)日:2024-03-07

    申请号:US17754664

    申请日:2020-10-07

    Abstract: A system includes a robot, a measuring device, and a processor. The robot is configured to dispense, based on at least one process parameter, a liquid adhesive bead onto a substrate. The measuring device is configured to measure at least one characteristic of the bead shape. The processor is configured to determine, based on a reference bead shape and at least one reference process parameter, response surface profile of the liquid adhesive. The processor is configured to compare the measured bead shape to a reference bead shape and, responsive to determining the measured bead shape is different than the reference bead shape, determine, based on the response surface profile, at least one updated process parameter. The updated process parameter is configured to cause the robot to dispense a second bead having the reference bead shape.

    Inspecting Sheet Goods Using Deep Learning
    2.
    发明公开

    公开(公告)号:US20230169642A1

    公开(公告)日:2023-06-01

    申请号:US17925771

    申请日:2021-06-01

    CPC classification number: G06T7/001 G06V10/82 G06T2207/20084

    Abstract: An inspection system includes an inspection device having at least one image capture device. The image capture device captures image data of a sheet part passing through the inspection device. A processing unit of the inspection device provides the image data representative of the sheet part to a plurality of neural networks, where each of the neural networks is trained to identify a corresponding defect in the sheet part and output data indicative of the presence of the corresponding defect. The processing unit determines a quality category of the sheet part based on the data indicative of the presence of the corresponding defect output by each corresponding neural network. The processing unit can further output the quality category of the sheet part to a sorter that can sort the sheet part based on the quality category.

    AUTOMATED INSPECTION FOR SHEET PARTS OF ARBITRARY SHAPE FROM MANUFACTURED FILM

    公开(公告)号:US20210390676A1

    公开(公告)日:2021-12-16

    申请号:US17283611

    申请日:2019-10-14

    Abstract: An example system is described herein. The example system may include an inspection device comprising at least one image capture device, the at least one image capture device configured to capture a reference image of a sheet part. Additionally, the example system may include a processing unit configured to identify at least one primary point in the reference image and identify at least one secondary point in a mask image. The processing unit may transform the mask image based on the at least one primary point and the at least one secondary point. The processing unit may apply the transformed mask image to the reference image to identify an inspection region within the reference image, process the inspection region of the reference image to determine the quality of the sheet part, and output information indicative of the quality of the sheet part.

    Automated liquid adhesive dispensing using portable measuring device

    公开(公告)号:US12168243B2

    公开(公告)日:2024-12-17

    申请号:US17754664

    申请日:2020-10-07

    Abstract: A system includes a robot, a measuring device, and a processor. The robot is configured to dispense, based on at least one process parameter, a liquid adhesive bead onto a substrate. The measuring device is configured to measure at least one characteristic of the bead shape. The processor is configured to determine, based on a reference bead shape and at least one reference process parameter, response surface profile of the liquid adhesive. The processor is configured to compare the measured bead shape to a reference bead shape and, responsive to determining the measured bead shape is different than the reference bead shape, determine, based on the response surface profile, at least one updated process parameter. The updated process parameter is configured to cause the robot to dispense a second bead having the reference bead shape.

    Active Learning Management System for Automated Inspection Systems

    公开(公告)号:US20240071059A1

    公开(公告)日:2024-02-29

    申请号:US18269657

    申请日:2021-12-23

    CPC classification number: G06V10/778 G06V10/7715

    Abstract: An example method for selecting product images for training a machine-learning model includes obtaining product images to include in an image population; receiving an indication of an image selection strategy for determining if a product image is to be included in a set of images of interest; determining image transforms based on configuration data for the indicated image selection strategy, wherein the image transforms perform image manipulation operations to obtain transformed image data for each of the product images in the image population; selecting a subset of images from the image population for inclusion in the set of images of interest based on the indicated image selection strategy and the transformed image data; determining one or more descriptive labels and applying the one or more descriptive labels to the respective sets of images; and training an inspection model for a product inspection system based on the labeled images.

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