Abstract: A method of inspecting a component using computed tomography is described, the method comprising the steps of: (a) providing a computed tomography (CT) scanner; (b) providing a target component; (c) reviewing the geometry of the component; (d) estimating the best component orientation; (e) orienting the component; (f) scanning the component with the CT scanner; (g) loading CT scan data into 3D image software; (h) registering the best CT scan data; (i) determining acceptable and unacceptable regions of CT scan data; (j) determining additional component orientations; (k) repeating steps (e) through (i) until all regions of CT scan data for the component are acceptable; and (l) creating a merged volume of acceptable CT scan data.

Abstract: An image inspection computing device is provided. The device includes a memory device and at least one processor. The at least one processor is configured to receive at least one sample image of a first component, wherein the at least one sample image of the first component does not include defects, store, in the memory, the at least one sample image, and receive an input image of a second component. The at least one processor is also configured to generate an encoded array based on the input image of the second component, perform a stochastic data sampling process on the encoded array, generate a decoded array, and generate a reconstructed image of the second component, derived from the stochastic data sampling process and the decoded array. The at least one processor is further configured to produce a residual image, and identify defects in the second component.

Abstract: An image inspection computing device is provided. The device includes a memory device and at least one processor. The at least one processor is configured to receive at least one sample image of a first component, wherein the at least one sample image of the first component does not include defects, store, in the memory, the at least one sample image, and receive an input image of a second component. The at least one processor is also configured to generate an encoded array based on the input image of the second component, perform a stochastic data sampling process on the encoded array, generate a decoded array, and generate a reconstructed image of the second component, derived from the stochastic data sampling process and the decoded array. The at least one processor is further configured to produce a residual image, and identify defects in the second component.

Abstract: A method of inspecting a component using computed tomography is described, the method comprising the steps of: (a) providing a computed tomography (CT) scanner; (b) providing a target component; (c) reviewing the geometry of the component; (d) estimating the best component orientation; (e) orienting the component; (f) scanning the component with the CT scanner; (g) loading CT scan data into 3D image software; (h) registering the best CT scan data; (i) determining acceptable and unacceptable regions of CT scan data; (j) determining additional component orientations; (k) repeating steps (e) through (i) until all regions of CT scan data for the component are acceptable; and (l) creating a merged volume of acceptable CT scan data.

Abstract: Methods, apparatus and computer-readable media for detecting potential defects in a part are disclosed. A potential defect may be automatically detected in a part, and may be reported to an operator in various ways so that the operator may review the defect and take appropriate action.

Abstract: Methods, apparatus and computer-readable media for detecting potential defects in a part are disclosed. A potential defect may be automatically detected in a part, and may be reported to an operator in various ways so that the operator may review the defect and take appropriate action.

Abstract: Methods, apparatus and computer-readable media for detecting potential defects in a part are disclosed. A potential defect may be automatically detected in a part, and may be reported to an operator in various ways so that the operator may review the defect and take appropriate action.

Abstract: Methods, apparatus and computer-readable media for detecting potential defects in a part are disclosed. A potential defect may be automatically detected in a part, and may be reported to an operator in various ways so that the operator may review the defect and take appropriate action.

Abstract: A method and system for nondestructively detecting and quantifying material anomalies within materials, including composite articles. The method entails performing a three-dimensional imaging scan technique, such as a computed tomography scan, of the material and a reference standard such that a test image of the material and a reference image of the reference standard appear in a plurality of two-dimensional scan views generated by the scan technique. The reference images are located in the scan views and normalized to determine at least an average value of the pixel data for the reference images. Values of pixel data of the test image are determined in each scan view, and then compared to the pixel data of the reference images to detect the presence of an anomaly in the test images. The detected anomaly in at least one of the test images of the scan views is then compared to a requirement standard for the material.

Abstract: A method for determining 3D distances on a 2D pixelized image of a part or object includes acquiring a real 2D pixelized image of the object, creating a simulated image of the object using the 3D CAD model and the 2D pixelized image, determining a specified cost function comparing the simulated image with the real 2D pixilated image and repositioning the simulated image in accordance with iterated adjustments of a relative position between the CAD model and the 2D pixilated image to change the simulated image until the specified cost function is below a specified value. Then, the workstation is used to generate a 3D distance scale matrix using the repositioned simulated image, and to measure and display distances between selected pixels on a surface of the real image using 2D distances on the 2D pixelized image of the object and the 3D distance scale matrix.

Abstract: A method for inspecting a component is provided. The method includes generating an image of the component, generating a signal indication mask, and generating a noise mask using a signal within the signal indication mask. The noise mask facilitates reducing a quantity of prospective signals contained in the signal indication mask. The method further includes utilizing the signal indication mask and the generated noise mask to calculate the signal-to-noise ratio of at least one potential flaw indication that may be present in the image.

Abstract: A method and system for nondestructively detecting and quantifying material anomalies within materials, including composite articles. The method entails performing a three-dimensional imaging scan technique, such as a computed tomography scan, of the material and a reference standard such that a test image of the material and a reference image of the reference standard appear in a plurality of two-dimensional scan views generated by the scan technique. The reference images are located in the scan views and normalized to determine at least an average value of the pixel data for the reference images. Values of pixel data of the test image are determined in each scan view, and then compared to the pixel data of the reference images to detect the presence of an anomaly in the test images. The detected anomaly in at least one of the test images of the scan views is then compared to a requirement standard for the material.

Abstract: A method for determining 3D distances on a 2D pixelized image of a part or object includes acquiring a real 2D pixelized image of the object, creating a simulated image of the object using the 3D CAD model and the 2D pixelized image, determining a specified cost function comparing the simulated image with the real 2D pixilated image and repositioning the simulated image in accordance with iterated adjustments of a relative position between the CAD model and the XID pixilated image to change the simulated image until the specified cost function is below a specified value. Then, the workstation is used to generate a 3D distance scale matrix using the repositioned simulated image, and to measure and display distances between selected pixels on a surface of the real image using 2D distances on the 2D pixelized image of the object and the 3D distance scale matrix.

Abstract: Methods and systems for measuring indications in an image are provided. The method includes acquiring image data that includes a potential indication, processing the data such that features of the indication are enhanced, thresholding the data such that the indication is separated from the remaining data, determining a size of the indication, and displaying a determined size of the indication.

Abstract: Methods and apparatus for fabricating a component is provided. The method includes receiving an ultrasound image of the component, selecting a subimage that includes a first surface of the component and an inspection area of the component, combining a filtered subimage with the selected subimage, and outputting the combined image to at least one of a display and an analyzer.

Abstract: A method for inspecting a component is provided. The method includes generating an image of the component, generating a signal indication mask, and generating a noise mask using a signal within the signal indication mask. The noise mask facilitates reducing a quantity of prospective signals contained in the signal indication mask. The method further includes utilizing the signal indication mask and the generated noise mask to calculate the signal-to-noise ratio of at least one potential flaw indication that may be present in the image.

Abstract: An ultrasound inspection system is provided. The ultrasound inspection system includes a pulse echo transducer and a processor that is operationally coupled to the transducer. The system facilitates reducing noise in an echo received from a near surface inspection area of a component. To facilitate reducing noise the processor is programmed to extract an A-scan data set from a B-scan image of the component. The processor is also programmed to locate a half-max point of a front surface echo in the A-scan data set. The processor is also programmed to locate the front surface of the component using a first zero crossing in a derivative of the A-scan data set.

Abstract: The present disclosure provides for the application of a two-dimensional ultrasonic phased array (100), formed of a plurality of transducers (102) arranged in a rectilinear pattern, for material and volumetric component testing. The two-dimensional array enables electronic adjustment of the focal properties and size of the aperture in both the azimuthal and elevational directions such that uniform and/or specified sound field characteristics can be obtained at any or all locations in the component being tested.

Abstract: A system and a method for managing various Customer Productivity Applications utilize a web-enabled interactive database to organize, store and retrieve information for the benefit of the customer community to effectively manage the business. The system captures all customers related information and provides on-line, up-to-date information to the users upon request. The system is configured to manage various Customer Productivity Applications to increase the customers' productivity and minimizes cost of ownership by analyzing the customers' fleet, perform industry comparisons, and run iterations to develop fleet optimal performance requirements.

Abstract: A system and a method for managing various Customer Productivity Applications utilize a web-enabled interactive database to organize, store and retrieve information for the benefit of the customer community to effectively manage the business. The system captures all customers related information and provides on-line, up-to-date information to the users upon request. The system is configured to manage various Customer Productivity Applications to increase the customers' productivity and minimizes cost of ownership by analyzing the customers' fleet, perform industry comparisons, and run iterations to develop fleet optimal performance requirements.