Embodiments of the disclosure include a remote inspection system for detecting and assessing the alkali-silica reaction (ASR) in situ in concrete, the system including an image acquisition device capable of excluding ambient light from a concrete surface and being placed against and imaging the concrete surface, the image acquisition device comprising a mirrorless camera and daylight and short-range UV light sources wherein the light sources and mirrorless camera are capable of being controlled remotely.

Aspects of the present disclosure includes a method of inspecting in situ the level of ASR present in concrete, including placing an image acquisition device as described above. In yet another aspects, the method further includes acquiring at least one image of said concrete surface prior to treatment with uranyl acetate to assess natural fluorescence in the concrete and acquiring at least one image of said concrete surface after treatment with uranyl acetate.

An imaging system for acquiring time-resolved images of crack propagation in glass samples includes a light source and data camera in a shadowgraph detector configuration, and a trigger camera to acquire images over an appropriate time window to capture crack propagation. Suitable software-based processing and analysis methods facilitate identifying individual cracks, branchpoints, and fragments in the images, as well as measuring their individual and statistical properties.

A system and a method include a light emitter configured to emit light onto or into a part to illuminate the part. A detector is configured to acquire one or more digital images of the part as illuminated by the light. A control unit is in communication with the detector. The control unit is configured to receive the one or more digital images of the part as illuminated by the light from the detector, and automatically analyze the one or more digital images of the part (to normalize out, such as by removing, known geometric features) as illuminated by the light to one or both of detect one or more defects of the part, or determine a porosity of the part.

A misalignment detection method and apparatus for battery tabs, and a battery electrode plate winding system, are disclosed. The method includes winding a battery electrode plate onto a winding shaft. For an Nth layer (where N is an integer greater than zero) of the electrode plate section wound on the winding shaft, an image including a battery tab region is acquired during the winding period. A relative positional relationship between a battery tab and a reference part on the winding shaft is determined from the image. Based on this positional relationship and the layer number of the Nth electrode plate section, a misalignment amount of the battery tab is calculated for when the wound electrode plate is later pressed into a battery cell. The method enables real-time monitoring of tab alignment during winding, improving accuracy in battery cell assembly.

A misalignment detection method and apparatus for battery tabs, and a battery electrode plate winding system, are disclosed. The method includes winding a battery electrode plate onto a winding shaft. For an Nth layer (where N is an integer greater than zero) of the electrode plate section wound on the winding shaft, an image including a battery tab region is acquired during the winding period. A relative positional relationship between a battery tab and a reference part on the winding shaft is determined from the image. Based on this positional relationship and the layer number of the Nth electrode plate section, a misalignment amount of the battery tab is calculated for when the wound electrode plate is later pressed into a battery cell. The method enables real-time monitoring of tab alignment during winding, improving accuracy in battery cell assembly.

Method and system for optically checking molded parts (10) in a transmitted light method, more particularly closures or the like produced by thermoforming or compression molding methods, comprising transporting the molded parts (10) from a transport device (50) through an optical checking area, and recording at least one image of the molded part (10) using a recording device (20), whereby the molded part (10) is located between the recording device (20) and an illumination device (30) and is illuminated by same, whereby the image is evaluated using processing means (40) in such a way that defects of the molded part (10) and/or statistical deviations from a normal distribution are able to be determined, from which conclusions are able to be drawn about a manufacturing process of the molded parts (10) in a molding tool having a cavity, whereby the conclusions are able to be used to control the manufacturing process.

Some embodiments of the present disclosure relate to systems and methods for detecting and quantifying residues on a surface, such as a windshield, for a vehicle. In some embodiments, a system may include a light source assembly, a camera assembly, and a computing device. The light source assembly can direct a polarized light toward the surface. The camera assembly can capture the polarized light reflected from the surface to generate an image. The computing device can process the image to generate a processing result indicative of cleanliness of the surface.

In an embodiment of the disclosed principles, a method of analyzing a rope to estimate its residual break strength (RBS) is provided. The method entails training a multi-layered neural network to recognize rope damage and estimate an RBS for a rope under study by collecting high-resolution visual data of a plurality of sample ropes, extracting visual features of damaged areas of each rope, resolving each visual feature into a damage type and clustering damage type exemplars, breaking each sample rope to determine an actual RBS for each rope and classifying the visual data via determined RBS, specific to product type/damage mode. Job and product data are entered for the rope under study, the rope is paid out, and high-resolution visual data is captured while spooling back the rope. The correlated data is provided to the multi-layered neural network to generate an estimate of RBS for the rope under study.

Disclosed is a defect inspecting apparatus including a memory that stores computer-executable instructions, and at least one processor that executes the instructions by accessing the memory. The at least one processor obtains a first feature point and a second feature point, which serve as a basis for rotation of a solid shape, from an input image associated with the solid shape targeted for defect inspection, obtains a target image, in which the first feature point and the second feature point are included in a predetermined area, by rotating the solid shape based on the first feature point and the second feature point, and obtains information about whether the solid shape has a defect, by applying the target image to a defect inspection model.

According to various embodiments, techniques and mechanisms are provided to enhance damage detection for objects such as vehicles in vehicle tunnels. In some implementations, a striped lighting tunnel is configured with cameras for capture of object or vehicle surface images when illuminated by striped lighting in a vehicle tunnel. Multiple vehicle surface images may be captured from a variety of perspectives. The vehicle surface images illuminated by striped lighting can be analyzed potentially with a vehicle object model. Each vehicle object model may include numerous object model components. Damage may be determined using striped lighting illuminated vehicle surface images to identify the type, likelihood, and extent of damage.