In one embodiment, a system for inspecting an object comprises a first camera for inspecting a first surface of the object, and a second camera for inspecting a second surface of the object. The object may be placed upon a support structure during simultaneous inspection by the first camera and the second camera. At least one roller is arranged to selectively engage the object when the object is placed upon the support structure, wherein the at least one roller is adapted for circumferential rotation relative to the support structure. Rotation of the at least one roller causes a corresponding circumferential rotation of the object relative to the first and second cameras.

A flexible inspection system includes a robot with a plurality of scanners and a robot controller. The robot controller is configured to receive a vehicle inspection protocol (VIP) for a vehicle being assembled on an assembly line. The VIP includes checkpoints to be scanned on the vehicle and the checkpoints correspond to components installed on the vehicle and connections between components installed on the vehicle. The robot controller commands the robot to move the plurality of scanners per the VIP such that the checkpoints are scanned. A characteristic of each checkpoint is recorded and compared to a reference characteristic such that a pass or no-pass determination of each checkpoint is provided. A vehicle inspection report with the pass/no-pass determinations is provided to an operator such that operator inspections and/or repairs of the checkpoints are made.

An artificial neural network-based method for detecting a surface type of an object includes: receiving a plurality of object images, wherein a plurality of spectra of the plurality of object images are different from one another and each of the object images has one of the spectra; transforming each object image into a matrix, wherein the matrix has a channel value that represents the spectrum of the corresponding object image; and executing a deep learning program by using the matrices to build a predictive model for identifying a target surface type of the object. Accordingly, the speed of identifying the target surface type of the object is increased, further improving the product yield of the object.

In one embodiment, systems and methods include using a workforce augmenting inspection device (“WAND”) to measure a parameter of an aircraft. The WAND comprises a body, wherein the body comprises one or more buttons configured to actuate the WAND to perform one or more functions. The WAND further comprises a head comprising a camera and a light source, wherein the light source is disposed around the camera operable to produce light in conjunction with operation of the camera, wherein the camera is operable to capture an image within a scope of view of the camera. The WAND further comprises a standoff wheel, wherein the standoff wheel is operable to rotate independently of the head. The WAND further comprises a power source operable to provide power to the WAND, wherein the power source comprises a controller configured to actuate the head, camera, and light source.

An artificial neural network-based method for selecting a surface type of an object includes receiving at least one object image, performing surface type identification on each of the at least one object image by using a first predictive model to categorize the object image to one of a first normal group and a first abnormal group, and performing surface type identification on each output image in the first normal group by using a second predictive model to categorize the output image to one of a second normal group and a second abnormal group.

A laser shearography end effector for inspection in an automated inspection and repair system for composite parts. A laser shearography system including an excitation system and a laser shearography camera is supported on a frame for movement with the frame. A slave tool changer is secured to the frame for releasably and operatively connecting the inspection tool to an industrial robot such that the industrial robot can move the inspection tool along a work piece as the laser shearography system inspects the work piece and such that the laser shearography end effector is interchangeable with at least one other automatic inspection end effector or repair end effector of the automated inspection and repair system.

A method for inspecting a preservation layer of a motor vehicle component during the manufacture of a motor vehicles. A preservation medium is applied having fluorescent additives to a component of the motor vehicle in a coating region. An inspection head having at least one camera and a UV light source is then caused to move adjacent to an inspection region that is a partial region of the coating region. The UV light source is the caused to emit radiating light onto the inspection region and the at least one camera is concurrently caused to record at least one image of the inspection region. An examination of the at least one recorded image is then conducted for a faulty coating with the preservation medium.

A apparatus is provided for carrying out an optical test method for a gearwheel. The testing apparatus includes a first camera for capturing image data of a first type of tooth flanks of the gearwheel to be tested, a position sensor for determining a rotational position of the gearwheel to be tested, a control device for evaluating the rotational position determined by this position sensor and for controlling the camera on the basis of this turning position, and a first illuminating device designed for illuminating an area of the gearwheel to be tested, which area is provided for capturing the image data.

Slit light is irradiated onto an object to be photographed (for example, an automobile body) in order to obtain a source image. Next, either one of a maximum value filtering process or a minimum value filtering process is performed on the source image to thereby obtain a first filter-processed image. Furthermore, after obtaining a second filter-processed image by carrying out a remaining one of the minimum value filtering process or the maximum value filtering process with respect to the first filter-processed image, a difference is determined between the second filter-processed image and the source image, and a difference image is obtained. Thereafter, a binarization process is implemented with respect to the difference image.

A handheld device for making 3D topography measurements of surface discontinuities in high performance structures, such as aerostructures (e.g., aluminum fuselages). Lights illuminate the discontinuity from multiple angles, and a camera captures images of the discontinuity. A thickness sensor generates thickness data regarding a thickness of the base material and the top protective coating. A position sensor generates position data regarding a location of the discontinuity on the structure. A processor generates geometry data regarding a geometry of the discontinuity based on the images, performs an analysis of the geometry, thickness, and position data, and communicates a result of the analysis on a display. A conforming membrane and/or a gel and an opaque lubricant may be applied over and conform to the discontinuity in order to make more uniform a reflectivity difference and a color difference between the discontinuity and an adjacent portion of the structure.