Abstract: Systems and methods for target inspection are provided. The system includes a camera, at least one sensor, and a controller. The camera acquires images of a target over time and the sensor(s) acquire motion data characterizing camera and target movement. The controller generates, using a first computer vision (CV) algorithm, an initial prediction and confidence level regarding an object of interest for a first image acquired at a first time. The controller also determines, using the motion data, a motion parameter characterizing relative motion between the camera and the target at the first time. The controller additionally receives a weighting based upon a second image acquired at a second time prior to the first time. The controller generates, using a second CV algorithm, a final prediction and confidence level for the first image based upon the first image, the initial prediction and confidence level, the motion parameter, and the weighting.

Abstract: 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.

Abstract: A system for analysis of a porous formation is disclosed. Such a system can provide electrical signals for one or more of the porous formation or a representation of the porous formation; can determine, using the electrical signals, permittivity and conductivity measures for the porous formation or the representation of the porous formation; and can model the permittivity and conductivity measures to generate a first estimation model associated with pore features for the porous formation, so that a downhole rock formation can be evaluated for pore connectivity, permeability, and Archie's texture parameters using estimation models.

Abstract: 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.

Abstract: Systems and methods for target inspection are provided. The system includes a camera, at least one sensor, and a controller. The camera acquires images of a target over time and the sensor(s) acquire motion data characterizing camera and target movement. The controller generates, using a first computer vision (CV) algorithm, an initial prediction and confidence level regarding an object of interest for a first image acquired at a first time. The controller also determines, using the motion data, a motion parameter characterizing relative motion between the camera and the target at the first time. The controller additionally receives a weighting based upon a second image acquired at a second time prior to the first time. The controller generates, using a second CV algorithm, a final prediction and confidence level for the first image based upon the first image, the initial prediction and confidence level, the motion parameter, and the weighting.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method of nondestructive testing includes receiving data characterizing an image of an inspection region of an industrial machine acquired by an inspection device configured to inspect the inspection region. The inspection device includes a camera and a light source. The camera has a first position and a first orientation and the light source has a second position and a second orientation when the image is acquired. The method also includes identifying a defect in the inspection region of the industrial machine based on the received data characterizing the image of the inspection region. The method further includes determining that a new image of the inspection region needs to be acquired. The method also includes varying one or more of position of the camera, orientation of the camera, position of the light source and orientation of the light source.

Abstract: A synchronous reluctance machine that has a stator and a rotor shaft operationally disposed within the confines of the stator. Laminations are axially stacked to form boat shaped segments. A plurality of selected boat shaped segments form a selected number of rotor poles about the rotor shaft and a plurality of support bars disposed intermittently between the boat shaped segments. Each segment of lamination is boat shaped with angular acuity facing towards the stator.