The disclosure provides a structure diagnosis system and a structure diagnosis method. The structure diagnosis system includes: a lidar scanner scanning a structure to generate a point cloud data; an input interface receiving the point cloud data; and a processor receiving the point cloud data and generating a point cloud data set. The processor executes a surface degradation and geometry abnormal coupling diagnosis module to: marking a first point cloud range of a surface degradation area according to color space value of the point cloud data set; marking a second point cloud range of a geometry abnormal area according to coordinate value of the point cloud data set; when an abnormal area includes the first point cloud range and the second point cloud range at least partially overlapping each other, determining surface degradation or geometry abnormal occurring at the abnormal area and mark the abnormal area with a predetermined mode.

A method for inspecting an object includes determining guide image data of the object from a determined orientation, the guide image data including a guide image pixel array and a pixel property for at least one guide image pixel in the guide image pixel array. The method also includes receiving inspection image data indicative of an inspection image and associating the inspection image data with the guide image data with a processor of a computing device. Additionally, the method includes determining a property of the object based on the guide image data and the associated inspection image data.

A product inspection system includes an image acquisition system having a camera generating an inspection image of a product arranged between a plurality of mirrors. The inspection image has a plurality of sub images of different sides of the product. The inspection system has a calibration member with a plurality of correction patterns on different sides; the camera receives light from the calibration member reflected by the mirrors to generate a calibration image of the calibration member. A computer of the product inspection system receives the inspection image and the calibration image and determines a relative mirror position relationship between the mirrors. The computer forms a single spliced image of the product.

Various examples include systems, apparatuses, and methods to perform an automated visual-inspection of components undergoing various stages of fabrication. In one example, an inspection system includes a number of robots, each having a camera, to inspect a component for defects at various stages of fabrication. Generally, each of the cameras is located at a different geographical location corresponding to the various stages in the fabrication of the component. At least some of the cameras are arranged to inspect all surfaces of the component that are not facing a table upon which the component is mounted. The system also includes a respective data-collection station electronically coupled to each the number of robots and an associated one of the cameras. A master data-collection station is electronically coupled to each of the data-collection stations. Other systems, apparatuses, and methods are disclosed.

A computer-implemented method of automatically generating inspection templates of a plurality of known good fasteners to identify fasteners at an inspection station is provided. The method includes providing a data entry mechanism to provide content needed to identify a plurality of unidentified mixed fasteners. The method also includes storing the content in a database, extracting the content from the database and creating the inspection templates from the extracted content. Each of the templates including a fastener profile and a set of features. Each of the features includes a range of acceptable values. Each of the templates has a fastener identification code associated therewith.

An aviation component inspection device includes a camera, a display, an input device, and a computer. The camera is configured to capture images of an aviation component under inspection. The computer is configured to receive an image from the camera, evaluate the image with one or more machine-learning aviation component-detection models. Each machine-learning aviation component-detection model is previously trained to output at least one confidence score indicating a confidence that a corresponding aviation component is present in the image. The computer is configured to present, via the display, a list of candidate aviation components based on corresponding confidence scores output by the one or more machine-learning aviation component-detection models, and add data previously-associated with a selected candidate aviation component from the list to a digital inspection report responsive to receiving user verification, via the input device, confirming the selected candidate aviation component is present in the image.

The invention concerns a system for evaluating the surface of a tyre (10), comprising: a region (21) for entry of the tyre into the system, a capture region, and an exit region (22), distinct from the entry region, means for moving (23) and for holding a tyre in position, means for illuminating the tyre allowing the illumination of a sidewall of the tyre and of the crown of a tyre in the capture region, means for acquiring a visual image of the tyre in the capture region, means for processing the acquired image, at least one acquisition means being installed on a shaft that is movable with respect to the tyre installed in the capture region.

The present disclosure relates to an inspection apparatus for visually inspecting a substantially dark area. The inspection apparatus includes an inspection casing having a sidewall extending between a casing inspection end and a connecting end, an omnidirectional video camera mounted to the casing inspection end of the inspection casing; and a light-emitting assembly at least partially contained in the inspection casing. The sidewall of the inspection casing has a light-permeable section extending along 360 degrees and the light-emitting assembly is configured to emit light through the light-permeable section and from the casing inspection end, and away therefrom. An inspection system is also described.

An illumination device has a light source unit, a lens unit, and a filter unit An imaging device receives object light, generated by the illumination light, from the measurement object at a predetermined observation solid angle, and pixels of the imaging device can each identify the different light wavelength ranges. A processing device includes an arithmetic unit configured to obtain a normal vector at each point of the measurement object corresponding to each pixel from inclusion relation between the plurality of solid angle regions, constituting the object light, and the predetermined observation solid angle, and a shape reconstruction unit configured to reconstruct the shape of the measurement object.

An optical imaging and processing system includes an optical element and a processor configured to process the plurality of image frames to generate a three-dimensional model of at least a portion of the turbine component interior. The system may also include a display coupled to the processor to display the three-dimensional model. An operator may view and analyze the three-dimensional model on the display for defects. The processor may further be configured to automatically navigate the three-dimensional model to determine defects within the turbine component interior. The system may also include a repositioning device configured to reposition the optical element such that the optical element may capture the plurality of image frames from multiple vantage points within the turbine component interior.