13200 results about "Ray" patented technology

The invention relates to the technical field of non-destructive testing, and discloses a non-destructive testing method for enhancing defect detection efficiency through deep learning, which comprises the following steps: step 1, acquiring multi-modal data of a target material, including data acquired through X-ray imaging, ultrasonic detection and infrared thermal imaging; 2, signal denoising processing is carried out on the obtained multi-modal data, signal denoising is carried out through wavelet transformation, and the wavelet transformation comprises the steps that multi-scale decomposition is carried out on signals, and high-frequency noise is removed through a soft threshold method; and step 3, carrying out image enhancement processing on the de-noised multi-modal data. The internal structural features of the material are captured from multiple physical dimensions by fusing multi-modal data of X-ray imaging, ultrasonic detection and infrared thermal imaging. The multi-modal fusion can make up for the deficiency of a single detection technology, so that the defect identification in complex structures and materials is more comprehensive and accurate, thereby significantly improving the detection precision.

The invention provides a defect detection method for a metal code disc without coating, and relates to the technical field of information, and the method comprises the following steps: fusing an external geometric model of the metal code disc obtained by three-dimensional scanning with internal defect information of the metal code disc obtained by X-ray flaw detection, and constructing a three-dimensional model of the metal code disc containing internal defects; if a stress concentration phenomenon exists around the defect, carrying out stability analysis on the defect in the metal coded disc by utilizing a fracture mechanics theory, calculating a stress intensity factor at the tip of the defect, evaluating the risk of crack propagation of the defect under the action of external force, and determining the critical dimension and the safety margin of the defect; and obtaining a metal code disc defect distribution rule according to the internal defect information of the metal code disc, and carrying out optimization design on the structural layout and key dimension parameters of the metal code disc in combination with the metal code disc defect distribution rule and a safety evaluation criterion. The failure risk caused by internal defects of the code disc is reduced, and the use reliability and safety of the code disc are improved.

The invention discloses an automatic identification method and system for a wafer internal defect image of a 3D stacked chip, and belongs to the technical field of semiconductor manufacturing and detection. According to the method, optical, X-ray and ultrasonic image data are synchronously acquired based on a multi-modal imaging technology, imaging parameters are dynamically adjusted to adapt to different wafer levels and material characteristics, multi-modal features are extracted in combination with layered filtering and denoising, multi-resolution registration and a self-supervised deep learning method, and micron-sized defects are positioned by using an attention mechanism. And further constructing a defect-process parameter correlation model through reinforcement learning, generating a closed-loop process optimization instruction, and transmitting the closed-loop process optimization instruction to an execution system. The system comprises a multi-modal imaging module, a noise suppression module, a deep learning analysis module and a process optimization module, and supports edge computing deployment. According to the invention, the internal defect detection efficiency and precision of the multi-layer stacked chip are significantly improved, real-time closed-loop control of detection-analysis is realized, the wafer manufacturing quality risk is reduced, and the method is suitable for intelligent defect detection of an advanced packaging production line.

The invention relates to the technical field of industrial product defect detection, and discloses a defect detection method combining vision and X-ray detection technologies, which comprises the following steps of: synchronously acquiring vision image data and X-ray transmission data in a surface coverage area of a detection object, performing combined preprocessing to complete noise suppression, artifact elimination and time alignment, and then acquiring the X-ray transmission data; according to the method, surface texture features and internal structure features are extracted respectively, cross-dimensional information mapping is performed through a multi-modal association module to generate a fusion feature set, surface damage, internal holes and boundary discontinuous defects are identified, and finally, a hierarchical detection report is generated according to defect space distribution and severity and is updated continuously. According to the method, the advantages of vision and X-ray detection are integrated, cooperative detection of surface and internal defects is achieved, the comprehensiveness, accuracy and real-time performance of defect detection are improved through multi-modal data synchronous collection, feature fusion and dynamic report generation, and the method is suitable for part quality detection in the industrial manufacturing field.

The embodiment of the invention provides a three-dimensional ray drawing method and device, and a curve control point is dynamically generated through precise conversion of a geographic coordinate system and a projection coordinate system in combination with an azimuth angle and an earth surface distance. A curvature correction mechanism based on a curved surface projection model is innovatively designed, the influence of the earth curvature on a ray trajectory is considered, and smooth space trajectory generation is realized through a Bezier curve parameter model. According to the system, the coordinate transformation compensation and spherical projection technology is adopted, accurate mapping of a geodetic coordinate system and a display coordinate system is established, accurate rendering of a three-dimensional space curve under different scales and view angles is ensured, and a high-precision technical scheme is provided for geographic information visualization. According to the method, the limitation of traditional straight line drawing is broken through, and the real trajectory expression considering the earth curvature is realized.

An apparatus includes a plurality of stacked flat Bragg diffractors having at least a first flat Bragg diffractor and a second flat Bragg diffractor. The first and second flat Bragg diffractors are positioned sequentially along an x-ray propagation axis of an x-ray beam. The x-ray beam includes x-rays and has an angular beam divergence less than 30 mrad in at least one direction.

The invention provides a bionic polarization semantic SLAM (Simultaneous Localization and Mapping) method based on a neural radiation field. A system comprises three parts, namely a bionic polarization pose estimation module based on factor graph optimization, a dense mapping module based on the neural radiation field and a semantic information positioning module based on bionic polarization infrared rays. The system firstly collects multi-sensor data, establishes a state equation and a measurement equation, and optimizes and estimates the pose by using a factor graph. Secondly, dense mapping is carried out by using the estimated pose and laser radar data and by adopting a neural implicit representation (NeRF-LOAM) model constructed by a laser radar odometer and a map through voxel embedding map generation and grid reconstruction. And finally, processing the polarization infrared fusion image through Yolov8 and SegNeXt, and realizing semantic positioning in combination with laser radar features. According to the system, the anti-interference performance and the environmental adaptability are remarkably enhanced, the mapping training time is shortened, and the system can be applied to multiple fields such as automatic driving, intelligent transportation and intelligent logistics.

The invention belongs to the field of coal gangue recognition, and particularly relates to an intelligent coal gangue recognition and analysis system based on machine vision and image processing, which analyzes the conformity score of each target object relative to coal gangue by combining the first-order matching degree, the second-order matching degree and the third-order matching degree of each target object relative to the coal gangue so as to recognize whether each target object is the coal gangue or not. Wherein the first-order matching degree comprehensively considers color features, texture features and morphological features in appearance images of the target objects, and the second-order matching degree comprehensively considers a heat distribution effect, a heat boundary effect and a heat conductivity effect fed back in thermal images of the target objects; according to the method, the internal uniformity of X-ray imaging partitions and the uniformity between the partitions of each target object are comprehensively considered through the three-order matching degree, and the target objects are evaluated from different angles through the matching degrees of different orders, so that coal gangue recognition has strong complementarity and accuracy, and the matching degree of the target objects and the coal gangue can be known more deeply and more comprehensively.

The invention discloses an imaging method and system based on cosmic ray muon transmission, which are applied to a control mechanism, and the control mechanism is electrically connected with at least one detection module. The imaging method based on cosmic ray muon transmission comprises the steps that the response state of at least one detection module is obtained, the detection module comprises a plurality of sensor units, and the sensor units are arranged in a string shape. And preprocessing the response state to obtain muon flux in unit area, unit time and unit solid angle. Based on the topographic data, the landform data and the muon flux, the density distribution in the muon ray irradiation range is reversely deduced through a preset algorithm. And performing visual imaging based on a density distribution result. According to the method, the working efficiency of muon geological imaging is improved, the system complexity is reduced, the adaptability in a narrow working environment is remarkably enhanced, and an efficient and convenient solution is provided for the fields of geological exploration, engineering detection and the like.

A method and a device of designing an optical system, and a storage medium are provided. The method includes: S1. determining an initial structure parameter of the optical system according to a design requirement; S2. optimizing the initial structure parameter according to the ray tracing method, and obtaining a theoretical structure parameter; S3. performing a discretization on a phase of a metalens of the theoretical structure parameter and obtaining a discrete phase; S4. performing an optical field propagation simulation according to the discrete phase, and obtaining an imaging performance index; S5. if the image performance index meets the design requirement, obtaining a target structure parameter; if the image performance index doesn't meet the design requirement, re-optimizing the image performance index and obtaining the target structure parameter.

The invention provides a weight metering automatic classification and calibration method and system based on image recognition, and relates to the technical field of weight metering, and the method comprises the steps: carrying out the imaging of the surface of a weight through dual-light-path high-speed camera shooting, carrying out the gamma correction, and extracting contour features and surface defect features; internal density distribution is obtained through X-ray imaging; performing multi-scale feature fusion on the surface features and the density distribution to construct a holographic feature model; analyzing the dynamic change trend of the characteristic parameters based on a deep variational Bayesian network, and performing evaluation and scoring in combination with a gradient boosting decision forest to obtain an initial classification; establishing a dynamic evaluation model by adopting a self-organizing competitive learning network, determining a weight grade and setting calibration parameters; selecting a corresponding reference weight to establish a grading calibration compensation model, and determining an adaptive weight coefficient for dynamic adjustment by combining defect distribution; and predicting a performance degradation trend by adopting a Shenchang differential equation network, and outputting calibration parameters and generating early warning information when the calibration precision meets a threshold value requirement.

A technique for performing ray tracing operations is provided. The technique includes traversing a bounding volume hierarchy for a ray to arrive at a bounding box without use of a neural network; perform a feature vector lookup using modified polar coordinates characterizing the ray relative to the bounding box to obtain a set of feature vectors; and obtaining output with the neural network using the set of feature vectors.

The invention discloses a PCB detection method and device based on multi-modal fusion and an adaptive algorithm, and relates to the field of electronic manufacturing detection. The method comprises the following steps: acquiring optical imaging data by using an optical imaging unit, acquiring tomography data by using an X-ray unit, and acquiring three-dimensional point cloud data by using a laser unit; collecting a reference signal, and updating detection parameters of the optical imaging unit, the X-ray unit and the laser unit; performing feature level fusion to obtain multi-modal fusion data; and inputting the multi-modal fusion data into a detection model, and performing defect comparison in combination with a historical database to obtain a defect detection result of the PCB. According to the method, optical imaging, X-ray penetration and laser three-dimensional modeling technologies are combined, and full-dimensional defect detection of the surface, the interior and the three-dimensional structure of the PCB is covered, so that the defect accuracy is improved. Meanwhile, a traditional fixed parameter detection mode is broken through through a self-adaptive intelligent algorithm, dynamic parameter optimization and multi-scene self-adaption are achieved, and the detection efficiency is effectively improved.

The invention discloses a GIS (Gas Insulated Switchgear) tiny defect detection method and system based on X-ray multi-effect fusion, and the method comprises the following steps: firstly, exciting a latent defect in a GIS to generate partial discharge by using an X-ray photoionization effect, detecting a discharge signal by using an ultrahigh frequency method and an ultrasonic method, and after the discharge signal is processed by a noise reduction model, carrying out noise reduction on the discharge signal; and respectively obtaining an ultrahigh-frequency discharge phase spectrogram and an ultrasonic discharge phase spectrogram. Then, the imaging plate is placed on the back face of the GIS, digital DR imaging is carried out through X rays, and an X-ray image is obtained; the ultrahigh frequency discharge phase spectrogram and the ultrasonic discharge phase spectrogram are fused after being denoised, an X-ray image is combined to establish a GIS health state diagnosis model, and reliable defect detection is carried out on the GIS according to the evaluation score of the diagnosis model. According to the method, multiple effects of X-rays are fused, so that smaller GIS latent defects can be found, the detection sensitivity is remarkably improved, and the problem that the traditional method is difficult to identify the tiny latent defects is solved.

The invention relates to the technical field of spectral data processing, and provides a soil heavy metal content detection and correction method based on an X-ray fluorescence spectrum, which comprises the following steps: acquiring a plurality of XRF spectral signals of a to-be-detected soil sample as an original spectral curve; obtaining the overall similarity of each original spectrum curve and the initial interference weight of each peak point in the original spectrum curves; decomposing to obtain a plurality of component signals; constructing a plurality of local windows of each component signal; obtaining a noise interference factor of each local window in each original spectrum curve; obtaining an adjustment reference coefficient of each local window in each original spectrum curve; obtaining a filtering adjustment coefficient of each wavelength in each original spectrum curve; dynamically filtering and smoothing the original spectrum curve to obtain a to-be-measured spectrum signal; and detecting the soil heavy metal content based on the to-be-detected spectral signal. The invention aims to solve the problem of heavy metal content detection deviation caused by noise in an X-ray fluorescence spectrum.

A method of designing a passive metasurface system within an environment includes receiving a three-dimensional model of the environment including one or more transmitter locations and one or more target locations, and determining one or more metasurface designs and placements to achieve a given objective. The method may also include computing a received signal strength at the one or more target locations based on the three-dimensional model of the environment, computing the received signal strength at the one or more target locations based on the three-dimensional model of the environment and the one or more metasurface designs and placements, and / or calculating ray traces and / or using machine learning to determine the received signal strength at the one or more target locations on the three-dimensional model of the environment and the one or more metasurface designs and placements.

Disclosed in the present invention is a three-dimensional Gaussian splatting optimization method for an unposed input. The method comprises: for an input image, predicting a ray bundle distribution by using a ray prediction model, to obtain distribution features in the form of ray bundles; on the basis of the distribution features in the form of ray bundles, calculating a camera pose; for the ray bundle distribution, performing sampling on the basis of the volumetric density of light rays, to obtain an initial spatial distribution of a three-dimensional Gaussian point cloud focused on a visual center area; for the input image, obtaining a visible shell by means of view frustum projection and object-mask computation; on the basis of the initial spatial distribution of the three-dimensional Gaussian point cloud and the visible shell, performing three-dimensional Gaussian splatting scene training, to obtain a three-dimensional scene reconstruction model satisfying a preset loss function criterion, the loss function comprising a training regularization term for a camera pose parameter. The present invention provides important scene initialization information for three-dimensional Gaussian splatting training, and significantly improves the quality and the richness of detail of the final three-dimensional structure.

The invention provides a baricitinib phthalate crystal form, and relates to the technical field of crystal form drug molecules. The crystal form is radiated by Cu-K alpha, and an X-ray diffraction pattern represented by 2 theta has characteristic peaks at 6.20 + / -0.2 degrees, 6.53 + / -0.2 degrees, 14.53 + / -0.2 degrees, 18.29 + / -0.2 degrees, 18.53 + / -0.2 degrees, 18.70 + / -0.2 degrees, 19.44 + / -0.2 degrees and 26.95 + / -0.2 degrees; the crystallographic measurement parameters are as follows: an orthorhombic system is adopted, and the space group is Pbcn; the cell parameters are as follows: # imgabs 0 # alpha = 90 degrees, beta = 90 degrees, gamma = 90 degrees, and the cell volume # imgabs 1 #. The invention also provides a related preparation method and application. The baricitinib phthalate crystal form disclosed by the invention is good in stability and relatively high in solubility and permeability.

The invention relates to the technical field of ophthalmology optics, in particular to a myopia control lens optical system integrating ray tracing and aberration correction, which comprises a wavefront phase acquisition module, a wavefront feature statistics module, a ray tracing simulation module, a microstructure form regulation and control module and a feedback control module. According to the method, accurate identification and datamation description of wavefront change under a dynamic vision condition can be realized by acquiring an eyeball wavefront phase matrix, performing gridding partition analysis and extracting local phase offset amplitude and time sequence characteristics, and a light propagation path model is constructed by combining statistical characteristics of an abnormal wavefront region; the self-adaptive compensation is carried out on the local focus deviation, and the spatial distribution optimization of the refractive index and the curvature is further realized based on the microstructure form regulation and control, so that the real-time matching of the optical parameters and the wavefront state is maintained during the processing and use of the lens, and therefore, the imaging quality is stabilized, the visual definition is improved, and the myopia control reliability is enhanced.

An apparatus includes an x-ray source configured to generate x-rays, at least some of which impinge a sample and at least one diffractor configured to concurrently diffract at least some of the x-rays from the sample in a first direction and in a second direction substantially orthogonal to the first direction. The apparatus further includes at least one two-dimensional (2D) position-sensitive x-ray detector configured to receive at least some of the diffracted x-rays and to concurrently generate first spectral information of the x-rays diffracted in the first direction and second spectral information of the x-rays diffracted in the second direction. The apparatus further includes circuitry configured to receive the first and second spectral information and to generate a single x-ray absorption spectroscopy (XAS) spectrum using the first and second spectral information.

The invention discloses an implicit coding and geometric prior-based indoor three-dimensional scene reconstruction method and system. The method comprises the following steps of: performing data processing on image data to be reconstructed to obtain corresponding pre-processed data; calculating rays under a world coordinate system corresponding to pixels needing to be trained on the image data according to internal and external parameters of the camera; inputting a three-dimensional coordinate code and an observation angle code of a sampling point on a ray and an implicit appearance code of a corresponding image into the neural radiation field model to obtain a predicted density value and a predicted color value, and performing volume rendering prediction based on a symbolic distance function to obtain a pixel value so as to obtain a trained neural radiation field model; and obtaining a standard implicit appearance code based on the density value and the color value, and inputting data at least comprising the standard implicit appearance code into the trained neural radiation field model to obtain scene geometric information. According to the method, the dependence of the existing reconstruction scheme on the three-dimensional consistency of the acquired data can be reduced, and the robustness and representation capability of the algorithm in a complex scene can be improved.

The invention discloses a curved surface stress detection method, which comprises the following steps of: 1, fixing a detected piece on an object placing table by using a self-adaptive clamp; step 2, scanning the measured piece to generate three-dimensional shape data of the measured piece; 3, calibrating the initial position of the measured piece by a displacement sensor, and establishing a coordinate system; step 4, adjusting the position of the measured piece by using a self-adaptive clamp, emitting X-rays to the measured piece by using an X-ray tube, and collecting diffraction signals by using a second detector; and step 5, the calculation module calculates the stress distribution state of the measured piece. According to the curved surface stress detection method, the problems of low irregular surface positioning precision and poor adaptability of traditional equipment are solved, and the detection efficiency and reliability are remarkably improved.

Apparatus and method for efficient storage of BVH nodes in blocks. For example, one embodiment of an apparatus comprises: bounding volume hierarchy (BVH) construction circuitry to construct a BVH based on primitives of a graphics scene; and block allocation hardware logic coupled to or integral to the BVH construction circuitry, the block allocation hardware logic to allocate a plurality of nodes of the BVH into a plurality of blocks for storage in a cache or memory subsystem, the block allocation hardware logic to maximize a number of blocks which include a leading parent node and one or more corresponding child nodes of the plurality of nodes.

Systems and methods for efficient memory management during ray tracing are described. A ray tracing system assigns a memory stack to a ray. The ray, when intersection tested against objects of a node, accesses data that is stored in the memory stack. When data is to be consumed from the memory stack by the ray, the ray tracing system uses a memory pointer associated with the ray to locate the requested data. When data is to be stored to the memory stack, the memory allocation circuitry stores data in a free memory block and uses a linked list to link the memory block with other memory blocks storing additional data for the ray.

The invention discloses a rock debris lithology analysis method based on a multilevel fusion image algorithm and X-ray diffraction. The method comprises the following steps: S1, acquiring rock debris image data under different resolutions; s2, generating a multi-level rock debris image feature matrix; s3, preliminarily generating a lithology classification result; s4, generating supplementary data of X-ray diffraction analysis; s5, fusing the supplementary data of the lithology analysis and the preliminarily generated lithology classification result, and finally generating a comprehensive lithology classification result; s6, the comprehensive lithology classification result is input into a dynamic adaptive analysis system, the dynamic adaptive analysis system adaptively adjusts an analysis strategy according to the rock debris sample complexity, and parameters of a dual-path convolutional neural network model and a multi-modal analysis algorithm are optimized through a real-time feedback and learning mechanism; and S7, outputting an analysis report containing mineral distribution, crystal structure and comprehensive lithology classification results. The classification accuracy of different types of rock debris samples is improved by about 15%.

The invention provides a container multi-angle imaging quality detection method and system, and the method comprises the steps: carrying out the illumination and imaging of a target container from a plurality of preset visual angles through employing light sources with different wavelengths, and obtaining a refraction displacement fingerprint data set; carrying out regional division on the surface of the container according to the data set, calculating the refraction influence degree of each region under different visual angles, and generating a regional visual angle weight distribution diagram; performing optical path reverse tracking processing on the images acquired at each view angle by using the distribution map, constructing a light propagation path model, and performing position mapping and distortion compensation to obtain a corrected image; and finally, according to the corrected image and the regional view angle weight distribution diagram, defect detection is carried out by adopting a regional adaptive fusion algorithm. According to the method, through technical means such as region adaptive division, optical path reverse tracking and region adaptive fusion, multi-view images can be accurately aligned and fused, meanwhile, observation characteristics of different regions are considered, and the reliability of a defect detection result is ensured.

The invention discloses a vertex measurement device and method based on a spectral confocal technology, and the method comprises the steps: transmitting a plurality of light beams through a plurality of light-emitting apertures which are arranged in a preset geometrical shape, carrying out the dispersion of the plurality of light beams into dispersion light beams with different wavelengths through a dispersion lens, irradiating the dispersion light beams to the surface of a measured workpiece, receiving reflected light, and carrying out the measurement of the measured workpiece. The reflected light is transmitted to the spectrum analysis device through a corresponding optical fiber channel; the spectrum analysis device analyzes the light intensity and wavelength of each group of reflected light and extracts spectrum data; calculating the height or space coordinate of the vertex of the surface of the workpiece according to the change condition of the spectral data of each group of reflected light rays; the processing circuit outputs the calculated vertex height or space coordinate information; according to the method, the vertex information of the workpiece can be effectively derived through ingenious spectral analysis and geometric fitting technologies, and the method has wide applicability and is particularly suitable for vertex measurement scenes of high-precision spherical surfaces, aspheric surfaces and conical surfaces.

Dual-energy imaging of a recording region is provided by a recording arrangement with an X-ray tube assembly and an X-ray detector for receiving X-rays of an X-ray field emitted by the X-ray tube assembly in cone beam geometry. The field has a central beam, and the recording arrangement is rotated around the recording region for recording projection data of different directions of projection for two different X-ray spectra. For each X-ray spectrum, a three-dimensional image dataset of the recording region is reconstructed from the respective projection data. The projection data of the two X-ray spectra is recorded during the rotation that covers at least 360°. For each X-ray spectrum, an associated portion of the X-ray field is fixed over the rotation, and a corresponding, associated, fixed portion of the X-ray detector is used.

The invention relates to the technical field of scintillator materials and X-ray detection, in particular to a rare earth organic-inorganic hybrid complex scintillator and a preparation method and application thereof. The general formula of the rare earth organic-inorganic hybrid complex scintillator is [RE (L) 4] <->. [A] < + >, wherein RE is selected from Eu, Tb, Sm or Dy; l is a beta-diketone ligand; [A] < + > is selected from long-chain hydrophobic quaternary ammonium salt cations or heterocyclic quaternary ammonium cations which have the carbon atom number of C8-C20 and do not contain active functional groups. The rare earth organic-inorganic hybrid complex scintillator provided by the invention has good solubility and molecular-level dispersion capability. The scintillator film based on the rare earth organic-inorganic hybrid complex prepared by using the rare earth organic-inorganic hybrid complex has the characteristic of compatibility of high scintillator load and high light transmission, overcomes the problems of low scintillator load rate, poor transparency and limited imaging resolution of the traditional scintillator film, and has excellent practical value and popularization prospect.

The invention discloses a marine surveying and mapping method based on multi-beam sounding correction, and belongs to the technical field of marine surveying and mapping. The method comprises the following steps: acquiring sounding echo signals, sound wave propagation time delay data and temperature data through a multi-beam sonar array, an acoustic chromatography transceiving array and a laser Raman probe; and fusing the data to construct a dynamic refractive index field model, correcting sound ray refraction distortion by adopting an adaptive variable step size algorithm, carrying out weight allocation and data fusion on space-time adjacent beams to obtain high-confidence water depth, and generating an isobath topographic map. The problem of refraction distortion is solved through multi-source data fusion, the sound ray tracking step length is dynamically optimized, noise interference is suppressed through weighted fusion, and the precision and reliability of topographic surveying and mapping in complex environments such as a deep sea hydrothermal region are remarkably improved.