To provide a magnetic domain image processing apparatus and a magnetic domain image processing method by which strain of an electromagnetic steel sheet can be evaluated in more detail. The invention is a magnetic domain image processing apparatus that processes a magnetic domain image, and the magnetic domain image processing apparatus includes: an image acquisition unit configured to acquire a reference magnetic domain image and a positive magnetic domain image or acquire the reference magnetic domain image and a negative magnetic domain image, the reference magnetic domain image being a magnetic domain image that is obtained when a stimulus of a reference intensity that is an intensity serving as a reference is applied to a sample, the positive magnetic domain image being a magnetic domain image that is obtained when the stimulus of an intensity higher than the reference intensity is applied to the sample, and the negative magnetic domain image being a magnetic domain image that is obtained when the stimulus of an intensity lower than the reference intensity is applied to the sample; and an image generation unit configured to generate, based on the reference magnetic domain image and the positive magnetic domain image, or based on the reference magnetic domain image and the negative magnetic domain image, a stress distribution image indicating a distribution of a stress region that is a region where stress is generated.

Disclosed herein are systems and methods for efficiently and economically manufacturing molded polymer products such as those that require a two-shot, two-material injection molding process, with complex geometries and incorporate metal components such as inserts. The systems and methods include compact manufacturing cells and processes of operating such manufacturing cells. The manufacturing cells include a single injection molding machine with two molds arranged to simultaneously operate both molds. The manufacturing cell is arranged to be fully automated so that it is operative without the need for intervention or management from dedicated personnel. Such automation includes the automated sorting and placement of metal inserts into the injection molding machine, the automated removal of the product after the first molding stage and second molding stage, the automated inspection of every finished product, the automated sorting of conforming and rejected products, and the automated packaging of finished product for shipment to end user.

A system and method are disclosed for enhancing pit detection and sizing in a test object. Response signatures are created and stored in a signature library to characterize various sensor responses (liftoff, orientation) and pit properties (e.g., depth, width), possibly with or without additional considerations (e.g., edges, cracks). A sensor is placed on and scanned across a surface of interest on the test object. During scanning the sensor is measured repeatedly at regular intervals. An encoder may be used to record the sensor position for each measurement. The measurement results are then correlated with one or more signatures in the signature library. A threshold is used to determine if the correlation is indicative of the detection of a pit. If so additional processing may be performed to estimate pit properties.

A three-dimensional shape measurement system includes an image pickup unit, a storage device that stores image pickup conditions required in imaging for measurement as condition information for each of a plurality of combinations of the material and surface property of an object, and a measurement controller that controls driving of the image pickup unit. The measurement controller identifies the material and surface property of the object, specifies image pickup conditions corresponding to the identified material and surface property of the object based on the condition information, causes the image pickup unit to perform the imaging for measurement under the specified image pickup conditions, and measures the shape of the object based on the obtained image for measurement.

Disclosed are a method of inspecting and evaluating a coating state of a steel structure, and a system therefor. A plurality of vision images and thermal images are acquired. While acquiring the thermal images, a desired region is heated. After the thermal images and the vision images in a dynamic state are reconstructed into a time-spatial-integrated thermal image and a time-spatial-integrated vision image in a static state, respectively, an overlay image is generated by overlaying the two images. A deterioration region of a coating is detected, and coating deterioration is classified by characteristics. A size of the coating deterioration region is quantified. A thickness of the coating is inspected by analyzing thermal energy measured from the time-spatial-integrated thermal image. A coating grade is calculated by comprehensively evaluating a coating deterioration inspection result and a coating thickness inspection result. A state evaluation report for the steel structure is automatically created.

Systems and methods disclosed herein include one or more computing devices configured to obtain one or more images of a material that has been placed at least partially within a CNC machine, where the one or more images are captured via one or more sensors associated with the CNC machine, determine one or more edges of the material based on the one or more images of the material, and determine whether the material can accommodate one or more placements of a design on the material based at least in part on the one or more edges of the material. Some embodiments additionally or alternatively include determining one or more material margins based on the one or more material edges, and determining whether the material can accommodate one or more placements of a design on the material based at least in part on the one or more material margins.

The present invention relates to a system and process carried out after a process of separating fragments of steel from pieces of ore that come out of a semi-autogenous grinder for grinding ores, and which consists of a system formed by one or more instruments for capturing images, each one being sensitive to light of different wavelengths, which point to the surface of an element for receiving the steel fragments or a channel that receives the steel balls and the fragments thereof from the separation process, through which the steel balls and fragments thereof move when they are discharged from this process, with the possibility of directing each image sensor such that it is not parallel to the others.

By digitally processing the images obtained with the one or more sensors, the dimensions and morphology of the balls and ball fragments discharged from the separation process can be determined.

A method for designing a material for an aircraft component includes training a neural network to correlate microstructural features of an alloy with material properties of the alloy by at least providing a set of images of the alloy to the neural network. Each of the images in the set of images has varied constituent compositions. The method further includes providing the neural network with a set of determined material properties corresponding to each image, associating the microstructural features of each image with the set of empirically determined data corresponding to the image, and determining non-linear relationships between the microstructural features and corresponding empirically determined material properties via a machine learning algorithm, receiving a set of desired material properties of the alloy for aircraft component, and determining a set of microstructural features capable of achieving the desired material properties of the alloy based on the determined non-linear relationships.

A defect inspection apparatus (100) is configured to approximate a difference value or an absolute value (Ia) of the difference value between a pixel value in at least three captured images (A) captured by an imager in at least three different phases of an elastic wave and a pixel value in a reference image (A.sub.ave) separate from the captured images (A) so as to acquire an approximate value for defect inspection corresponding to an amount of change in the pixel value in the captured images (A).

A control system includes a vision system including an imaging device and a VAR monitoring system configured to determine a power adjustment phase of the VAR process based on the images from the vision system and a process parameter. The VAR monitoring system includes a vision analysis module configured to analyze the images from the vision system to detect a melt marker based on a remelt image process model, and a prediction module configured to predict an operational characteristic of the VAR process that is associated with the power adjustment relative to a melt marker location and a remelt prediction model. The VAR monitoring system is configured to initiate the power adjustment phase in response to the melt marker satisfying a predetermined melt marker condition, the operational characteristic of the VAR process satisfying a predetermined operational condition, or a combination thereof.