Techniques for facilitating testing analytics of imaging systems and methods using molds are provided. In one example, a system includes a mold temperature controller configured to apply a thermal signature to a mold of a target. The system further includes a focal plane array configured to capture an infrared image of the mold. The system further includes an image analytics device configured to determine thermal analytics associated with the mold based on the infrared image. Related devices and methods are also provided.

Described is a method for segmenting measurement data from measurement of an object that has at least one material transition region. The measurement data are used to generate a digital object representation that has the material transition region and a multiplicity of spatially resolved image information items relating to the object. The method may include: determining measurement data that have at least one small structure having an extent which is less than a predefined extent; determining at least two homogeneous regions in the measurement data and/or in the digital object representation, wherein at least one homogeneous regions has a small structure; analysing a local similarity of the multiplicity of spatially resolved image information items; adapting an extent of each homogeneous region until at least one border region is arranged at an expected position of a material transition region; and segmenting the digital object representation based on the adapted homogeneous regions.

Provided is the technique that allows an operator or the like to easily grasp a defect contained in a mold. A display control device is configured to carry out: a determination process in which a feature amount of each of defects contained in a mold is determined with reference to an image obtained by image capture of a mold; and a display process in which the image is displayed on a display such that each of the defects in the image is emphasized by a method which is determined according to the determined feature amount.

A molding system molding a sand mold includes a flask, a tank connected to a compressed air source, including an opened end part, and configured to internally store sand, a nozzle attached to the end part of the tank and configured to guide the sand in the tank into the flask, and a control unit configured to output information about clogging of the nozzle when, during sand filling in which the sand in the tank is introduced into the flask through the nozzle, a relationship where pressure inside the tank is higher than initial pressure during the sand filling in which the sand is introduced into the flask is satisfied.

A method for dynamically measuring deformation of a rotating-body mold, including: (S1) subjecting an overall outer surface of the rotating-body mold to three-dimensional measurement to acquire an initial point cloud data; (S2) shooting, by a multi-camera system, the mold from different angles to obtain three-dimensional coordinates of marking points and coding points on the overall outer surface of the rotating-body mold; (S3) rotating the mold, and repeatedly photographing the marking points and the coding points on the mold surface under different angle poses; and calculating three-dimensional coordinates of the marking points and the coding points; and (S4) predicting a point cloud data of the outer surface under different angle poses based on a conversion relationship among the marking points to analyze a deformation degree of the mold during a rotation process.

A position detector applies an image to be inspected to a position detection model generated by machine learning using image information of a training image to calculate a score for a portion of an image to be inspected. The position detector specifies a portion of the image where the calculated score is a score that satisfies a predetermined relationship to detect the position of a metal part in the image to be inspected. A position outputter outputs the position of the metal part detected by the position detector.

A method and system for performing inspection of a manufactured article includes acquiring a sequence of images using an image acquisition device of the article under inspection. The sequence of images is acquired while relative movement between the article and the image acquisition device is caused. At least one feature characterizing the manufactured article is extracted from the acquired sequence of images. The acquired sequence of images is classified based in part on the extracted feature. The classification may include determining an indication, of a presence of a manufacturing defect in the article, and may include identifying a type of manufacturing defect. The extracting and the classifying can be performed by a computer-implemented classification module, which may be trained by machine learning techniques.

There are described herein methods and system for generating an inspection image of an object from radiographic imaging. The method comprises obtaining a plurality of digital images of the object positioned between a radiation source and a photon beam detector, the digital images taken at different object-detector distances or source-detector distances to create unique grain diffraction patterns in each one of the digital images, and forming the inspection image from image features common to the digital images at a common scale and removing the unique grain diffraction patterns.

A three dimensional (3D) detection device has a detection supporter base to be disposed on a transmission device, ultrasonic transceiver modules disposed on at least one inner base surface of the detection supporter base and a controller. When a tested object is transmitted by the transmission device and then enters the detection supporter base, the ultrasonic transceiver modules emit ultrasonic signals to the tested object, and the tested object reflects the ultrasonic signals to the ultrasonic transceiver modules. The ultrasonic transceiver modules generate detection signals according to the reflected ultrasonic signals. The detection signals are sent to the controller, and the controller generates an ultrasonic image corresponding to a tested object according to the detection signals, and then compares the ultrasonic image to a pre-established original 3D image, so to achieve a surface detection objective.

One variation of a method for monitoring manufacture of assembly units includes: receiving selection of a target location hypothesized by a user to contain an origin of a defect in assembly units of an assembly type; accessing a feature map linking non-visual manufacturing features to physical locations within the assembly type; for each assembly unit, accessing an inspection image of the assembly unit recorded by an optical inspection station during production of the assembly unit, projecting the target location onto the inspection image, detecting visual features proximal the target location within the inspection image, and aggregating non-visual manufacturing features associated with locations proximal the target location and representing manufacturing inputs into the assembly unit based on the feature map; and calculating correlations between visual and non-visual manufacturing features associated with locations proximal the target location and the defect for the set of assembly units.