A method for mapping and analyzing a GaN substrate to identify areas of the substrate suitable for fabrication of electronic devices thereon. Raman spectroscopy is performed over the surface of a GaN substrate to produce maps of the E.sub.2 and A.sub.1 peaks at a plurality of areas on the substrate surface, the E.sub.2 and A.sub.1 peaks being associated with known concentrations of defects and charge carriers, so that areas of the GaN substrate having relatively high resistivity or conductivity which make those areas suitable or unsuitable for fabrication of electronic devices can be identified. The devices can then be fabricated only on suitable areas of the substrate, or the size of the devices can be tailored to maximize the yield of devices fabricated thereon. Substrates not meeting a threshold level of defect and/or charge carrier concentration can be discarded without fabrication of poor-quality devices thereon.

Even under a different light source, such as outdoor light source, diagnosis of surface states of a diagnosis target object is performed with a high accuracy without measuring spectral distribution information about the light source at the time of measuring a diagnosis target object. A spectral reflectance calculation section (22) calculates, based on pieces of spectral distribution information measured for different surface states of a diagnosis target object and spectral distribution information measured for a reference object with an already-known reflectance, spectral reflectances of the surface states; a reference setting section (23) sets, from a spectral reflectance of a surface state showing a deteriorated state, among the spectral reflectances of the surface states, a wavelength range within which reflectances at the same wavelength are within a predetermined range and the reflectance as a reference wavelength range and a reference reflectance; and a dictionary registration section (24) registers the spectral reflectances of the surface states, the reference wavelength range, the reference reflectance and pieces of spectral distribution information about a plurality of light sources with a dictionary (30).

An image processing apparatus, an image processing method and a recording medium capable of detecting a plurality of breaks in a coating material and an inclined break of the coating material are provided. The image processing apparatus includes a grouping unit for extracting coating areas representing a coating material from an input image acquired by imaging an inspection object linearly coated with the coating material and grouping the coating areas for each sequence of linear parts, a calculation unit for calculating a line width in an orthogonal direction of a linear part for each of the linear parts in a plurality of portions of the coating area including end portions of the linear parts, a break detecting unit for detecting a break in the coating material based on the calculated line widths, and an output unit for outputting an indication representing occurrence of the break when the break is detected.

An apparatus displays a plurality of lines representing a plurality of cracks occurring in a structure on a display unit, accepts an instruction to change a display state of the plurality of lines on the display unit, assigns order in which the display state is changed based on the instruction to each of a plurality of lines constituting one connecting point among the plurality of lines, and changes the display state of each of the plurality of lines constituting the one connecting point based on the order assigned by the assignment unit in response to acceptance of the instruction.

A convolutional neural network may be trained to inspect subjects such as carbon fiber propellers for surface flaws or other damage. The convolutional neural network may be trained using images of damaged and undamaged subjects. The damaged subjects may be damaged authentically during operation or artificially by manual or automated means. Additionally, images of undamaged subjects may be synthetically altered to depict damages, and such images may be used to train the convolutional neural network. Images of damaged and undamaged subjects may be captured for training or inspection purposes by an imaging system having cameras aligned substantially perpendicular to subjects and planar light sources aligned to project light upon the subjects in a manner that minimizes shadows and specular reflections. Once the classifier is trained, patches of an image of a subject may be provided to the classifier, which may predict whether such patches depict damage to the subject.

A turbine section according to an example of the present disclosure includes, among other things, a component including a coating on a substrate, and at least one sensor positioned a distance from the component, the at least one sensor configured to detect radiation emitted from at least one localized region of the coating at a first wavelength and configured to detect radiation emitted from the substrate corresponding to the at least one localized region at a second, different wavelength. The first wavelength and the second wavelength are utilized to determine a heat flux relating to the at least one localized region. A method of measuring a gas turbine engine component is also disclosed.

A method of generating a spatial map of sensor data collected during additive manufacturing, in which a plurality of layers of powder are selectively melted with an energy beam to form an object. The method includes receiving sensor data collected during additive manufacturing of an object, the sensor data including sensor values, the sensor values captured for different coordinate locations of the energy beam during the additive manufacturing of the object, and generating cell values for a corresponding cell-based spatial mapping of the sensor data. Each of the cell values is determined from a respective plurality of the sensor values extending over an area/volume comparable to an extent of the melt pool or the energy beam spot.

A system and method for monitoring a track and/or rail employs one or more imagers mounted to a railcar and directed to image the track and/or rails wherein the images are geo-tagged with location data. Geo-tagged images are processed to determine at least track gauge and/or at least rail fastener integrity. The system and method may also determine other track and/or rail integrity issues including, e.g., rail fastener integrity, rail profile, rail alignment, center point dip, cross level, rail cant, wheel wear, wheel integrity, rail wear, rail defects, and/or rail temperature. The system and method may also determine when inspection and/or maintenance of the track is indicated, and provide selected records of where and/or when such inspection and/or maintenance is indicated.

An apparatus according to the present disclosure acquires a display condition for displaying at least a part of target data as a display image on a display unit, determines, in a case where the display image is changed, whether to store the display condition according to a changed display image in a storage unit, based on an index relating to the change of the display image, and stores, in a case where the display condition is determined to be stored, the display condition according to the changed display image in the storage unit.

An inspection system includes one or more processors that obtain a first image of a work piece that has a fluorescent dye thereon in an ultraviolet (UV) light setting and a second image of the work piece in a visible light setting. The first and second images are generated by one or more imaging devices in the same position relative to the work piece. The one or more processors identify a candidate region of the first image based on a light characteristic of one or more pixels, and determine a corresponding candidate region of the second image that is at an analogous location as the candidate region of the first image. The one or more processors analyze both candidate regions to detect a potential defect on a surface of the work piece and a location of the potential defect relative to the surface of the work piece.