Baker Hughes Oilfield Operations LLC

Baker Hughes Holdings LLC

Carlneil Domkam

Sheldon McCrackin

Jeremy Vandam

Samvid Jhaveri

Kevin Andrew Coombs

Brice Kim

Tom Lambdin

Jeremy Daniel VanDam

Christopher Blake

An inspection system is provided and includes a camera and controller. The controller can include one or more processors in communication with the camera and receive a plurality of images of a target captured by the camera. The controller can also determine, using a first computer vision algorithm, a first prediction and corresponding confidence level for substantially all of the images. The controller can select a subset of the images having the first prediction confidence level greater than or equal to a first prediction threshold value. The controller can additionally determine, using a second computer vision algorithm, a second prediction and corresponding second prediction confidence level for each of the selected images. The at least one second prediction can require more time to determine than the at least one first prediction. The controller can output the second prediction and the second prediction confidence level for each of the selected images.

Computer vision inferencing for non-destructive testing

An inspection system is provided and includes a camera and controller. The camera can acquire at least one image of a target including opposed first and second surfaces. The controller can be in communication with the camera and receive the at least one image. The controller can also detect, using at least one computer vision algorithm, a geometry of the target including the first target surface and the second target surface of the target within at least one image. The at least one image can be acquired at a respective time under respective operating conditions. The controller can additionally segment erosion within the at least one image using the at least one computer vision algorithm. The controller can also generate an erosion depth profile for the at least one image. The erosion depth profile can characterize a depth of erosion of the target between the first and second surfaces.

Erosion detection and prediction

A method for automatically determining whether an operator carried out a first operation on an asset positioned at a location includes the steps of installing a camera module at the location to observe the asset, sending image data from the camera module to an analytics center, processing the image data to automatically determine the identity of the operator or changes at the location resulting from the first operation, developing an event signature based on the image data, wherein the event signature is indicative of whether the first operation on the asset took place, and verifying the status of the first operation based on the event signature. Based on the step of verifying the status of the first operation, the methods can also be configured to automatically process an invoice for the first operation or automatically command a second operation.

Operation identification of sequential events

A method of adaptive inspection includes receiving data characterizing one or more images of an inspection region of an industrial machine acquired by an inspection system operating based on a first set of operating parameters. The inspection region includes a site feature. The method also includes determining, by an analytical model, one or more characteristics of the inspection region from the received data characterizing the one or more images of the inspection region. The method further includes generating a control signal based on the one or more characteristics of the inspection region and/or a user input. The inspection system is configured to perform a new inspection of the inspection region based on the control signal.

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Houston, TX, United States of America

Carlneil Domkam