Material selection and optimization process for component manufacturing

    公开(公告)号:US11485520B2

    公开(公告)日:2022-11-01

    申请号:US16104435

    申请日:2018-08-17

    摘要: A method for designing a material for an aircraft component includes training a neural network to correlate microstructural features of an alloy with material properties of the alloy by at least providing a set of images of the alloy to the neural network. Each of the images in the set of images has varied constituent compositions. The method further includes providing the neural network with a set of determined material properties corresponding to each image, associating the microstructural features of each image with the set of empirically determined data corresponding to the image, and determining non-linear relationships between the microstructural features and corresponding empirically determined material properties via a machine learning algorithm, receiving a set of desired material properties of the alloy for aircraft component, and determining a set of microstructural features capable of achieving the desired material properties of the alloy based on the determined non-linear relationships.

    Automated material characterization system including conditional generative adversarial networks

    公开(公告)号:US10733721B2

    公开(公告)日:2020-08-04

    申请号:US16549332

    申请日:2019-08-23

    摘要: A material characterization system includes an imaging unit, a material characterization controller, and an imaging unit controller. The electronic imaging unit generates a test image of a specimen composed of a material. The electronic material characterization controller determines values of a plurality of parameters and maps the parameters to corresponding ground truth labeled outputs. The mapped parameters are applied to at least one test image to predict a presence of at least one target attribute of the specimen in response to applying the learned parameters. The test image is convert to a selected output image format so as to generate a synthetic image including the predicted at least one attribute. The electronic imaging unit controller performs a material characterization analysis that characterizes the material of the specimen based on the predicted at least one attribute included in the synthetic image.

    AUTOMATED MATERIAL CHARACTERIZATION SYSTEM INCLUDING CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS

    公开(公告)号:US20190378267A1

    公开(公告)日:2019-12-12

    申请号:US16549332

    申请日:2019-08-23

    摘要: A material characterization system includes an imaging unit, a material characterization controller, and an imaging unit controller. The electronic imaging unit generates a test image of a specimen composed of a material. The electronic material characterization controller determines values of a plurality of parameters and maps the parameters to corresponding ground truth labeled outputs. The mapped parameters are applied to at least one test image to predict a presence of at least one target attribute of the specimen in response to applying the learned parameters. The test image is convert to a selected output image format so as to generate a synthetic image including the predicted at least one attribute. The electronic imaging unit controller performs a material characterization analysis that characterizes the material of the specimen based on the predicted at least one attribute included in the synthetic image.

    Automated material characterization system including conditional generative adversarial networks

    公开(公告)号:US10430937B2

    公开(公告)日:2019-10-01

    申请号:US15714339

    申请日:2017-09-25

    摘要: A material characterization system includes an imaging unit, a material characterization controller, and an imaging unit controller. The electronic imaging unit generates a test image of a specimen composed of a material. The electronic material characterization controller determines values of a plurality of parameters and maps the parameters to corresponding ground truth labeled outputs. The mapped parameters are applied to at least one test image to predict a presence of at least one target attribute of the specimen in response to applying the learned parameters. The test image is convert to a selected output image format so as to generate a synthetic image including the predicted at least one attribute. The electronic imaging unit controller performs a material characterization analysis that characterizes the material of the specimen based on the predicted at least one attribute included in the synthetic image.

    SENSOR SYSTEM FOR TRANSCODING DATA
    18.
    发明申请

    公开(公告)号:US20190050753A1

    公开(公告)日:2019-02-14

    申请号:US15840132

    申请日:2017-12-13

    IPC分类号: G06N99/00

    摘要: A sensor system may comprise a sensor; a processor in electronic communication with the sensor; and/or a tangible, non-transitory memory configured to communicate with the processor, the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations. The operations may comprise recording, by the sensor, a preliminary type data sample; and/or applying, by the processor, a mapping function having a plurality of tuned parameters to the preliminary type data sample, producing a desired type data output.