Method and system are disclosed for determining sample composition from spectral data acquired by a charged particle microscopy system. Chemical elements in a sample are identified by processing the spectral data with a trained neural network (NN). If the identified chemical elements not matching with a known elemental composition of the sample, the trained NN is retrained with the spectral data and the known elemental composition of the sample. The retrained NN can then be used to identify chemical elements within other samples.

Method and system are disclosed for determining sample composition from spectral data acquired by a charged particle microscopy system. Chemical elements in a sample are identified by processing the spectral data with a trained neural network (NN). If the identified chemical elements not matching with a known elemental composition of the sample, the trained NN is retrained with the spectral data and the known elemental composition of the sample. The retrained NN can then be used to identify chemical elements within other samples.

In one embodiment, an X-ray inspection system may access a first set of X-ray images of one or more first samples that are labeled as being non-conforming. The system may adjust a classification algorithm based on the first set of X-ray images. The classification algorithm may classify samples into conforming or non-conforming categories based on an analysis of corresponding X-ray images. The system may analyze a second set of X-ray images of a number of second samples using the adjusted classification algorithm. The second samples may be previously inspected samples that have been classified as conforming by the classification algorithm during a previous analysis before the classification algorithm is adjusted. The system may identify one or more of the second samples from the second set of X-ray images. Each identified second sample may be classified as non-conforming by the adjusted classification algorithm.

A system configured to detect defects in a first oxygen sensor is disclosed. The system is configured to detect defects in a first oxygen sensor. The system includes an X-ray imaging device configured to capture a production X-ray image of the first oxygen sensor and an electronic processor configured to use a trained oxygen sensor defect detection model to identify a defect of the first oxygen sensor by producing a pseudo X-ray image by simulating a projection of a fan beam through CT data of a second oxygen sensor. The electronic processor is also configured to measure, via the trained oxygen sensor defect detection model, a fan-beam distortion in the production X-ray image; select, via the trained oxygen sensor defect detection model, the pseudo X-ray image based on the fan-beam distortion; perform a comparison, via the trained oxygen sensor defect detection model, of the production X-ray image to the pseudo X-ray image; and, classify, based on the comparison, the production X-ray image as representing an improperly assembled oxygen sensor.

The disclosure provides an inspection method determining whether there is a defect in an electrode structural body including a cathode electrode layer, an electrolyte layer and an anode electrode layer electrode by an image processor. The inspection method includes a step of scanning the electrode structural body along a scanning direction to obtain a continuous transmission image, a step of digitizing a shade of each pixel of the transmission image, a step of calculating a difference value between a grayscale of a specific pixel and a median value of grayscales of comparison pixels located in front or rear of the specific pixel along the scanning direction, and a step of determining presence or absence of the defect according to the difference value and a predetermined threshold value.

In one embodiment, a computing system may access design data of a printed circuit board to be produced by a manufacturing process. The system may determine one or more corrections for the design data of the printed circuit board based on one or more correction rules for correcting one or more parameters associated with the printed circuit board. The system may automatically adjust one or more of the parameters associated with the design data of the printed circuit board based on the one or more corrections. The adjusted parameters may be associated with an impedance of the printed circuit board. The one or more corrections may cause the impendence of the printed circuit board to be independent from layer thickness variations of the printed circuit board to be produced by the manufacturing process.

Method for detecting at least one critical defect in a ceramic rolling element providing the steps of capturing a plurality of two-dimensional digital radiographic images of the ceramic rolling element; digitally filtering each radiographic image; delineating, on the basis of the filtered image, at least one region liable to comprise the critical defect; constructing stereoscopically a virtual model of the ceramic rolling element having the region; comparing the dimensions of the delineated region with a plurality of predetermined threshold values, and, when the dimensions are greater than the threshold values, generating an alarm signal.

An inspection device includes a ray source that irradiates an object to be inspected with energy rays, a detection unit that detects energy rays that have passed through the object to be inspected, a displacement mechanism that sets a relative position of the object to be inspected and the ray source by displacing at least one of the object to be inspected and the ray source in relation to the other, an internal image generation unit that generates an internal image of the object to be inspected based on a detection amount distribution of the energy rays detected by the detection unit, and a control unit that controls the displacement mechanism based on the detection amount distribution of the energy rays detected by the detection unit.

In one embodiment, an X-ray inspection system may nondestructively inspect a printed circuit board to measure a number of dimensions at a number of pre-determined locations of the printed circuit board. The X-ray inspection system may generate a data set for the printed circuit board based on the measured dimensions. The X-ray inspection system may calculate one or more drilling values based on the data set of the printed circuit board. The X-ray inspection system may provide, to a drilling machine, instructions for drilling a number of plated-through vias based on the calculated drilling values for the printed circuit board.

A method of inspecting a vehicle includes: acquiring a to-be-inspected image of an inspected vehicle (S11); acquiring a visual feature of the to-be-inspected image using a first neural network model (S12); retrieving a template image from a vehicle template library based on the visual feature of the to-be-inspected image (S13); determining a variation region between the to-be-inspected image and the template image (S14); and presenting the variation region to a user (S15). The system of inspecting a vehicle includes a radiation imaging device (150), a display device (130), an image processor (140), and a storage device (120). The present disclosure further includes a computer-readable storage medium.