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    ENGINE INSPECTION AND MAINTENANCE TOOL
    102.
    发明申请
    ENGINE INSPECTION AND MAINTENANCE TOOL 有权

    公开(公告)号：US20210239010A1

    公开(公告)日：2021-08-05

    申请号：US16779837

    申请日：2020-02-03

    Applicant: General Electric Company ,  Oliver Crispin Robotics Limited

    Inventor： Andrew Crispin Graham ,  David Scott Diwinsky ,  Ton Thu Lang Giang ,  Wayne Ray Grady

    IPC: F01D21/00 ,  F01D5/00

    Abstract: A tool for performing inspection and/or maintenance operations on an engine defines a longitudinal direction and a tangential direction. The tool includes a base extending along the longitudinal direction and including a body, a first extension member extending from the body in the tangential direction at a first location, and a second extension member extending from the body in the tangential direction at a second location. The second location is spaced from the first location along the longitudinal direction. The tool also includes a pivot member rotatably coupled to the base and moveable between an insertion position in which the pivot member is oriented generally along the longitudinal direction and a deployed position in which the pivot member is oriented away from the longitudinal direction.

    Inspection tool and method
    104.
    发明授权
    Inspection tool and method 有权

    公开(公告)号：US10822997B2

    公开(公告)日：2020-11-03

    申请号：US16008454

    申请日：2018-06-14

    Applicant: General Electric Company

    Inventor： Andrew Crispin Graham ,  Lyle Timothy Rasch ,  Michael Dean Fullington ,  Wayne Ray Grady ,  David Scott Diwinsky

    IPC: F01D21/00

    Abstract: An engine assembly includes an engine including a component and defining an opening and an interior, the component including a first side and an opposite second side, the second side positioned within the interior of the engine. The engine assembly also includes an inspection tool having a first member including at least one of a receiver or a transmitter and directed at the first side of the component. The inspection tool also includes a second member including the other of the receiver or the transmitter and positioned at least partially within the interior of the engine and directed at the second side of the component to communicate a signal with the first member through the component, the second member being a robotic arm extending through the opening of the engine.

    System and method for work piece inspection
    105.
    发明授权
    System and method for work piece inspection 有权

    公开(公告)号：US10755401B2

    公开(公告)日：2020-08-25

    申请号：US16208668

    申请日：2018-12-04

    Applicant: General Electric Company

    Inventor： Xiao Bian ,  Arpit Jain ,  David Scott Diwinsky ,  Bernard Patrick Bewlay ,  Steeves Bouchard ,  Jean-Philippe Choiniere ,  Marc-Andre Marois ,  Stephane Harel ,  John Karigiannis

    IPC: G06T7/00 ,  H04N5/235

    Abstract: An inspection system includes one or more imaging devices and one or more processors. The imaging devices generate a first set of images of a work piece at a first position relative to the work piece and a second set of images of the work piece at a second position relative to the work piece. At least some of the images in the first and second sets are acquired using different light settings. The processors analyze the first set of images to generate a first prediction image associated with the first position, and analyze the second set of images to generate a second prediction image associated with the second position. The first and second prediction images include respective candidate regions. The processors merge the first and second prediction images to detect at least one predicted defect in the work piece depicted in at least one of the candidate regions.

    Fluorescent penetrant inspection system and method
    106.
    发明授权
    Fluorescent penetrant inspection system and method 有权

    公开(公告)号：US10746667B2

    公开(公告)日：2020-08-18

    申请号：US16201322

    申请日：2018-11-27

    Applicant: General Electric Company

    Inventor： Xiao Bian ,  John Karigiannis ,  Stephane Harel ,  Steeves Bouchard ,  Maxime Beaudoin Pouliot ,  Wayne Grady ,  David Scott Diwinsky ,  Bernard Patrick Bewlay

    IPC: G01N21/91 ,  G01N21/64

    Abstract: An inspection system includes an imaging device, visible light source, ultraviolet light source, and at least one processor. The imaging device generates a first image set of a work piece while the ultraviolet light source illuminates the work piece with ultraviolet light to cause fluorescent dye thereon to emit light, and generates a second image set of the work piece while the visible light source illuminates the work piece with visible light. The first and second image sets are generated at the same positions of the imaging device relative to the work piece. The processor maps the second image set to a computer design model of the work piece based on features depicted in the second image set and the positions of the imaging device. The processor determines a defect location on the work piece based on an analysis of the first image set and the computer design model.

    Image analysis neural network systems
    109.
    发明授权
    Image analysis neural network systems 有权

    公开(公告)号：US10546242B2

    公开(公告)日：2020-01-28

    申请号：US15495313

    申请日：2017-04-24

    Applicant: General Electric Company

    Inventor： Arpit Jain ,  Swaminathan Sankaranarayanan ,  David Scott Diwinsky ,  Ser Nam Lim ,  Kari Thompson

    IPC: G06N7/00 ,  G06K9/62 ,  G06N3/08

    Abstract: A method includes determining object class probabilities of pixels in a first input image by examining the first input image in a forward propagation direction through layers of artificial neurons of an artificial neural network. The object class probabilities indicate likelihoods that the pixels represent different types of objects in the first input image. The method also includes selecting, for each of two or more of the pixels, an object class represented by the pixel by comparing the object class probabilities of the pixels with each other, determining an error associated with the object class that is selected for each pixel of the two or more pixels, determining one or more image perturbations by back-propagating the errors associated with the object classes selected for the pixels of the first input image through the layers of the neural network without modifying the neural network, and modifying a second input image by applying the one or more image perturbations to one or more of the first input image or the second input image prior to providing the second input image to the neural network for examination by the neurons in the neural network for automated object recognition in the second input image.

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