System and method for controlling a robotic arm

    公开(公告)号:US11084169B2

    公开(公告)日:2021-08-10

    申请号:US15986952

    申请日:2018-05-23

    Abstract: A robotic arm assembly includes a robotic arm, a base, and a utility member, the robotic arm extending between a root end attached to the base and a distal end including the utility member. A method for controlling the robotic arm assembly includes: determining a position of the base, the root end, or both relative to the environment; determining a task position and orientation for the utility member within the environment; determining a three-dimensional constraint of the environment; and determining a path for the robotic arm through the environment based on each of the position of the base, the root end, or both relative to the environment, the task position and orientation for the utility member within the environment, and the three-dimensional constraint of the environment.

    FLUORESCENT PENETRANT INSPECTION SYSTEM AND METHOD

    公开(公告)号:US20200166467A1

    公开(公告)日:2020-05-28

    申请号:US16201322

    申请日:2018-11-27

    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.

    Situ gas turbine prevention of crack growth progression

    公开(公告)号:US10544676B2

    公开(公告)日:2020-01-28

    申请号:US15014115

    申请日:2016-02-03

    Abstract: A method for remotely stopping a crack in a component of a gas turbine engine is provided. The method can include inserting an integrated repair interface attached to a cable delivery system within a gas turbine engine; positioning the tip adjacent to a defect defined on a surface on the component; and locally heating the base of the defect. A method is also provided for clamping a crack defined between a first surface and a second surface of a component of a gas turbine engine. The method can include attaching a strap over the crack such that a first end of the strap is attached to the first surface of the component and the second end of the strap is attached to the second surface of the component.

    In Situ Gas Turbine Prevention of Crack Growth Progression

    公开(公告)号:US20200011181A1

    公开(公告)日:2020-01-09

    申请号:US16556608

    申请日:2019-08-30

    Abstract: Methods provided for remotely stopping a crack in a component of a gas turbine engine are provided, along with methods of remotely cleaning a surface area of a component of a gas turbine engine. The method can include inserting an integrated repair interface attached to a cable delivery system within a gas turbine engine; positioning the tip adjacent to a defect within a surface of the component; temporarily attaching the tip adjacent to the defect within the surface on the component; and drilling a hole into the base of the defect. An integrated repair interface is also provided.

    NEURAL NETWORK FEATURE RECOGNITION SYSTEM
    10.
    发明申请

    公开(公告)号:US20180342069A1

    公开(公告)日:2018-11-29

    申请号:US15605243

    申请日:2017-05-25

    Abstract: A system includes one or more processors configured to analyze obtained image data representing a rotor blade to detect a candidate feature on the rotor blade and determine changes in the size or position of the candidate feature over time. The one or more processors are configured to identify the candidate feature on the rotor blade as a defect feature responsive to the changes in the candidate feature being the same or similar to a predicted progression of the defect feature over time. The predicted progression of the defect feature is determined according to an action-guidance function generated by an artificial neural network via a machine learning algorithm. Responsive to identifying the candidate feature on the rotor blade as the defect feature, the one or more processors are configured to automatically schedule maintenance for the rotor blade, alert an operator, or stop movement of the rotor blade.

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