A method (100) for classifying an etch indication (11) of a component (10), the method including the steps of: providing a captured image (13) of the at least one etch indication (11); detecting at least one criterion (15) of the etch indication (11) based on the captured image (13); comparing the determined criterion (15) to at least one criteria data set (16) of etch indications (11) that is stored in a database; and classifying the etch indication (11) into at least one predetermined defect class (D) based on the comparison.

In an inspection support device that organizes a captured image including damage to a structure and includes a processor, the processor acquires image data including information regarding a structural drawing of a target structure on a medium, and damage identification information regarding the damage and captured image identification information regarding the captured image of the target structure having the damage that are added by a user on the medium, recognizes the damage identification information through image recognition from the image data, recognizes the captured image identification information through image recognition from the image data, associates the damage identification information corresponding to a predetermined damage and the captured image identification information for the target structure having the predetermined damage, acquires the captured image corresponding to the captured image identification information, and associates the damage identification information and the captured image with each other.

The invention relates to the field of battery swap technologies, and specifically provides a detection method for battery swap in a battery swap station. The invention aims to solve the following problem: Potential safety risks are caused by no prevention of a foreign matter on an upper surface of a battery, a damage on a battery in a process of battery swap, and no prevention of circulation of a battery with a damaged lower surface in a battery swap station, because a battery surface is not monitored before and after battery mounting in existing battery swap stations. To this end, the detection method for battery swap in the invention includes the following steps: obtaining a first image of a used battery at a first preset position; determining, based on the first image, whether the used battery is in a first anomalous state; selectively uploading the first image to a server based on a determination result; obtaining a second image of the used battery at a second preset position; determining, based on the second image, whether the used battery is in a second anomalous state; and selectively uploading the second image to the server based on a determination result, so that the server receives and stores the first image and the second image.

A fluorescent optical system and a fluorescent image inspection system are provided. The fluorescent optical system includes a platform, at least one light source device, and at least one first filter. The platform is configured for placement of a sample to be inspected. The at least one light source device is configured to illuminate the sample to be inspected, so that the sample to be inspected is stimulated to generate a fluorescent light. The at least one first filter is correspondingly arranged in an optical path of the at least one light source device, so that an excitation light passes through the at least one first filter. An incident angle is formed between the excitation light and the platform, and the incident angle is less than 90 degrees.

The operational state of a surface inspection system for detecting defects on the surface of semiconductor wafers is monitored by: providing a reference wafer having defects of a particular number, size, and density on an examination surface; conducting a reference inspection of the reference wafer and at least one control inspection of the reference wafer by the surface inspection system, the position and size of defects on the examination surface being measured; identifying defects which, because of their position, are regarded as common defects of the reference inspection and of the control inspection; for each common defect, determining a size difference obtained from comparing its size from the reference inspection and from the control inspection; and assessing the operational state of the surface inspection system on the basis of the size differences.

A system includes a dishwasher, an image capturing device designed to capture an image of washware arranged in the washing chamber, with the image including a plurality of sub-images, each of which having different spectral information of the washware. An illumination unit illuminates the washware in the washing chamber, and an image analysis unit receives the captured image from the image capturing device and to carry out a chemical analysis of soiling on the washware based on the plurality of sub-images of the received image and to ascertain a dirt characteristic of soiling as a result of the chemical analysis. A control device carries out a washing program for washing the washware in the washing chamber. The control device receives the dirt characteristic from the image analysis unit and adapts the washing program for washing the washware as a function of the received dirt characteristic.

Provided is a defect inspection apparatus including a plurality of detection optical systems for collecting illumination scattered light from the surface of a sample, a plurality of sensors for converting the illumination scattered light collected by the corresponding detection optical systems into electrical signals and outputting detection signals, and a signal processing device for processing the detection signals input from the plurality of sensors, wherein the signal processing device generates a first signal group including an integrated signal obtained by adding a plurality of detection signals in a predetermined combination based on a group of detection signals input from the plurality of sensors, generates a second signal group by performing the filtering processing on each signal that configures the first signal group, generates a third signal group including separated signals separated according to a predetermined rule from the signal corresponding to the integrated signal based on the second signal group, and detects or classifies defects based on the third signal group to store defect inspection data in a memory.

The present disclosure proposes a method for classifying defects and the like by using a learning device that has been suitably trained, a system, and a computer-readable medium. As one aspect thereof, the present disclosure proposes (see FIG. 1) a defect inspection method, etc., in which one or more computers are used to inspect a defect on a sample on the basis of output information from detectors that detect scattered light produced via the irradiation of the sample with light, wherein defect information is outputted by: receiving output from a plurality of detectors disposed at a plurality of angles of elevation with reference to the sample surface, and at a plurality of sample surface-direction orientations with reference to the irradiation points of the light on the sample; and inputting the output information of the plurality of detectors into a learning device that has been trained using the output information from the plurality of detectors and the defect information.

A defect inspection device is provided with an illumination optical system that irradiates light or an electron beam onto a sample, a detector that detects a signal obtained from the sample through the irradiation of the light or electron beam, a defect detection unit that detects a defect candidate on the sample through the comparison of a signal output by the detector and a prescribed threshold, and a display unit that displays a setting screen for setting the threshold. The setting screen is a two-dimensional distribution map that represents the distribution of the defect candidates in a three dimensional feature space having three features as the axes thereof and includes the axes of the three features and the threshold, which is represented in one dimension.

A method for detecting defects includes directing a scanning beam to a location on a surface of a transparent sample, measuring top and bottom surface specular reflection intensity, and storing coordinate values of the first location and the top and bottom surface specular reflection intensity in a memory. The method may further include comparing the top surface specular reflection intensity measured at each location with a first threshold value, comparing the bottom surface specular reflection intensity measured at each location with a second threshold value, and determining if a defect is present at each location and on which surface the defect is present. The method may further include comparing the top surface specular reflection intensity measured at each location with a first intensity range, comparing the bottom surface specular reflection intensity measured at each location with a second intensity range, and determining on which surface the defect is present.