409 results about "High resolution imaging" patented technology

The invention relates to the technical field of shock absorber defect detection, and discloses an electric vehicle shock absorber defect detection method and system based on machine vision, and the method comprises the steps: collecting an initial image set under the irradiation of a multi-angle light source through high-resolution imaging collection equipment; performing denoising and filtering processing according to the initial image set to obtain clear image data; performing defect classification and spatial distribution analysis according to the clear image data to obtain surface feature vectors containing defect types and defect spatial distribution; carrying out vibration amplitude acquisition and phase angle measurement operation according to the surface feature vector, and carrying out spectral analysis to construct a performance parameter vector; performing data fusion according to the performance parameter vector and the surface feature vector to obtain a fusion feature; inputting the fusion features into a pre-constructed association prediction model to obtain defect prediction data; and performing defect influence degree analysis according to the defect prediction data to obtain a defect evaluation result. The method provides a basis for quality control and performance optimization of the shock absorber.

The invention provides a deep frequency shift super-resolution microscopic imaging chip and a deep frequency shift super-resolution microscopic imaging system for omni-directional ultra-high wave vector illumination, and belongs to the technical field of optical super-resolution microscopy. The chip comprises a substrate plated with an adhesion layer and multiple layers of films on the adhesion layer, and sub-wavelength-scale circular ring gratings are engraved on the substrate and the adhesion layer; exciting light enters the circular ring grating through the substrate, and evanescent waves of ultrahigh wave vectors in all directions are generated through the circular ring grating. The evanescent waves are coupled to the upper surface through the multi-layer thin film to excite surface plasmons with ultrahigh transverse wave vectors in the corresponding direction, and the surface plasmons are used for carrying out all-directional ultrahigh wave vector illumination and deep frequency shift super-resolution microscopic imaging on a sample placed on the upper surface of the multi-layer thin film. The system comprises an excitation module, a deep frequency shift super-resolution microscopic imaging chip for omni-directional ultra-high wave vector illumination, an imaging module and an excitation control and image acquisition module. According to the invention, omni-directional ultra-high resolution imaging of a complex fine structure sample can be realized, so that application requirements in related fields can be met.

The invention relates to the field of radar systems, in particular to directional drilling radar equipment, which comprises a transmitting unit provided with an angle-adjustable array antenna and capable of transmitting radar waves in any direction to realize directional coverage of a target area; the receiving unit adopts a multi-angle receiving array antenna and is combined with a signal filtering technology, so that the receiving sensitivity and accuracy of weak signals can be effectively improved; the positioning unit is provided with a high-precision inertial navigation system and a depth sensor, and accurate positioning and posture correction of equipment in a drill hole are ensured; the transmitting unit supports a high-frequency working mode and a low-frequency working mode which are respectively used for shallow high-resolution imaging and deep high-penetration detection. The invention provides directional drilling radar equipment and a detection method thereof, which are used for solving the defects of control host performance and directional drilling radar technology in the aspect of imaging technology in the prior art.

The invention discloses a method for predicting plant photosynthetic ability by using plant leaf traits, and relates to the technical field of agricultural science, and the method comprises the following steps: obtaining image data of a target plant leaf in a natural state through a high-resolution imaging device, and synchronously recording environment parameter information during collection; extracting multi-dimensional feature parameters of the leaf based on the image data, wherein the multi-dimensional feature parameters comprise a color index, a texture feature, an area, a thickness estimation value and an edge contour form; and carrying out stress feature identification on the character data by utilizing an association rule of the environmental parameters and the leaf characters. According to the invention, by introducing a stress identification and data correction mechanism, the accuracy of photosynthetic capability prediction is improved; the method has good environmental adaptability and crop universality, and is suitable for various agricultural scenes; and a prediction feedback closed-loop system is constructed, continuous optimization and intelligent adjustment of the model are realized, and the stability, reliability and practical application value of the system are remarkably enhanced.

The invention relates to the technical field of crop disease and insect pest image recognition, and particularly discloses a crop disease and insect pest image recognition method based on a large model, and the method comprises the steps: obtaining a multi-angle leaf image through high-resolution imaging equipment under a controllable illumination condition, and obtaining a target image in a unified format; extracting scab texture complexity features in combination with a local binary pattern and a gray-level co-occurrence matrix algorithm, and performing multi-channel statistical analysis on RGB and HSV color spaces to generate color heterogeneity feature vectors; further fusing the two types of features into a composite disease feature vector, inputting the composite disease feature vector into a probability model constructed based on a support vector machine and a Monte Carlo Dropout mechanism, and outputting probability distribution and confidence score of disease and pest categories; and dynamically adjusting a model training strategy according to a confidence level, triggering a feedback mechanism for a low-confidence sample, generating a synthetic image by using a conditional generative adversarial network, and optimizing model parameters in combination with incremental learning to realize stable identification modeling of rare or complex disease types.

The invention discloses an underwater focusing intense sound system and method based on phase control, and relates to the technical field of focusing intense sound, and the technical scheme is characterized in that a measurement and control upper computer is used for controlling the emission and detection of a trigger signal; the phase control signal generator is used for controlling a phase control signal of sound wave emission; the multi-channel power amplifier is used for driving the acoustic emission phased area array, and the acoustic emission phased area array is used for emitting acoustic waves; the area array calibration hydrophone is used for receiving signals of reflected sound waves; the target calibration sound source is used for transmitting a signal pulse width, the target sound field measurement hydrophone is used for receiving the signal pulse width transmitted by the target calibration sound source and forwarding the signal pulse width to the measurement and control upper computer, and the measurement and control upper computer receives the forwarded signal pulse width for system evaluation and correction. By generating the high-energy strong-focusing sound field and combining the actual underwater signal propagation process, accurate positioning and control of the underwater strong sound field can be completed, so that accurate focusing irradiation and high-resolution imaging of a long-distance small target are realized.

An apparatus includes, in some implementations, at least one image sensor, a plurality of metalenses, and readout and processing circuitry. The at least one image sensor includes a plurality of pixel arrays, each of the which is associated, respectively, with a different one of a plurality of optical channels configured for detection of incoming light rays of a particular wavelength or a particular range of wavelengths centered on the particular wavelength. Each of the metalenses is disposed, respectively, in a different one of the optical channels and is configured, respectively, to focus incoming light rays onto a different one of the pixel arrays. The readout and processing circuitry is operable to read out signals from the pixel arrays and to generate a respective lower-resolution image for each of the optical channels, and to process the lower-resolution images to obtain a higher-resolution monochromatic image. Methods of operation are described as well.

The invention discloses a multi-lens large-view-field high-resolution imaging method and device, equipment and a medium. The method comprises the following steps: synchronously acquiring images acquired by a central lens and all fisheye lenses; performing distortion correction processing on the images acquired by the fisheye lenses based on the camera calibration parameters to obtain corrected fisheye images; performing motion feature matching on the corrected fisheye image and the center lens image; registering the corrected fisheye image to the visual angle of the central lens image based on a motion feature matching result; carrying out fusion processing on the registered image; and post-processing the fused image to obtain a final image. According to the method, distortion correction processing is carried out on the fisheye lens, feature matching and registration are carried out on the fisheye lens and the center lens, complex scenes such as weak textures and violent or dynamic illumination change can be effectively dealt with, and robustness and imaging quality are improved.

The invention relates to the technical field of PTFE (polytetrafluoroethylene) membrane micropore defect detection, in particular to PTFE membrane micropore defect detection equipment based on machine vision, which comprises symmetrically arranged mounting side plates and sensor assemblies arranged on one sides of the mounting side plates at intervals, and an overturning assembly used for realizing driving is arranged between the two groups of mounting side plates. Adjusting assemblies are arranged on the outer side of the overturning assembly in an array mode, and detection modules used for detecting PTFE membrane micropore defects are arranged on the outer sides of the adjusting assemblies. And the adjusting assembly comprises clamping frames arrayed on the outer side of the overturning assembly, bent plates are symmetrically arranged on the sides, close to the overturning assembly, of the clamping frames, and quick connecting rods are installed on the inner walls of the bent plates at intervals up and down. The device has the beneficial effects that high-resolution imaging is carried out by adopting the intelligent sensor, the white light interferometer and the high-speed line scanning camera, micro-current detection is realized in combination with weak current released by the discharge piece, micropore defects can be accurately identified, and misjudgment or missing detection caused by a single detection mode is avoided.

The invention discloses a large-view-field high-resolution imaging system based on polarization regulation and control, the large-view-field high-resolution imaging system comprises a metasurface system array and a camera along the direction of a light path, and the metasurface system array comprises a plurality of pairs of metasurface systems which are distributed in an array; each pair of metasurface systems comprises a first metasurface system and a second metasurface system; the first metasurface system is used for performing high-resolution imaging and large-view-field imaging on a first polarization light beam and a second polarization light beam of an incident light beam respectively; the second metasurface system is used for performing large-view-field imaging and high-resolution imaging on the first polarization-state light beam and the second polarization-state light beam respectively; the camera is used for acquiring and fusing images formed by different metasurface systems so as to capture a high-resolution central region of interest and surrounding environment information of a wide field of view. The system can efficiently realize higher imaging quality.

The invention provides an imaging optical system for industrial visual inspection, which is characterized in that a first lens is mainly composed of nine lenses and has focal power, the object side surface of the first lens is a convex surface, and the image side surface of the first lens is a concave surface; the second lens has focal power; the third lens has focal power; the fourth lens has focal power; the fifth lens has positive focal power; the sixth lens has focal power, and the object side surface of the sixth lens is a convex surface; the seventh lens has focal power, and the object side surface of the seventh lens is a concave surface; the eighth lens has focal power; and the ninth lens has positive focal power, the image side surface of the ninth lens is a convex surface, and through the combination design of nine lenses and the reasonable configuration of the refractive power and the surface type of each lens, high-resolution imaging under a compact structure and a large aperture is realized, the aberration correction capability is particularly enhanced, and a relatively high MTF value is ensured in the whole zoom range. Accuracy and reliability of industrial detection are remarkably improved, and the system has the advantages of zooming, low distortion and low cost.

The invention discloses an air-ground cooperative excitation integrated time-frequency receiving aviation electromagnetic detection system and method, and belongs to the technical field of aviation geophysical detection. The electromagnetic detection system comprises a time frequency receiver, a helicopter aviation time domain transmitter, a time frequency receiving coil and a ground frequency domain transmitter. According to the electromagnetic detection method, time-domain pulses are transmitted in the air through the helicopter, frequency-domain continuous waves are transmitted on the ground, the time-domain pulses and the frequency-domain continuous waves are excited synchronously and received in a full-aviation mode, and helicopter aviation time-domain electromagnetic data and ground-air frequency-domain electromagnetic data are obtained through one-time flight based on the frequency point splitting and data decoupling technology. The electromagnetic detection system integrates the high-resolution imaging capability of helicopter aviation time domain electromagnetism to a hectometer-level shallow part and the strong penetration characteristic of ground-air frequency domain electromagnetism to a deep part, and is particularly suitable for large-range resource exploration under complex surface conditions such as mountainous areas and water areas; the method can realize shallow geologic structure refining considering large-depth geologic structure detection.

The invention discloses a terahertz continuous wave wind power blade defect imaging method based on an unmanned aerial vehicle platform, relates to the technical field of blade defect imaging, and solves the problems that in the prior art, when a crawling robot serves as a contact type mobile platform to detect a wind power blade, the process is tedious and time-consuming, and safety risks exist. According to the method, an efficient and flexible non-contact detection mode is provided, the unmanned aerial vehicle is adopted as an aerial autonomous bearing platform, contact dependence on the surface of the blade is overcome, rapid deployment, long-distance maneuvering and flexible arrival of detection equipment are achieved, and the detection operation efficiency and safety of the high-altitude and in-service wind power blade are greatly improved; the invention further provides a split type terahertz transmission imaging method capable of being integrated with an unmanned aerial vehicle platform, visual and high-resolution imaging of bubbles, layering and other defects in the blade is achieved by means of the penetrating characteristic of terahertz waves to a composite material, and the defect that in the prior art, the internal defect detection capacity is insufficient is overcome.

The invention provides a bistatic ISAR imaging arc section selection method for an air moving target, and relates to the technical field of bistatic radar imaging, and the method comprises the steps: obtaining the position information of a transmitting station, a receiving station and the air moving target, and converting the position information of the transmitting station, the receiving station and the air moving target into the coordinates of an earth-centered earth-fixed coordinate system; establishing a translation simulation model, a rotation simulation model and an echo model of the air moving target; the method comprises the following steps: determining a first constraint condition and a second constraint condition of a double-base-angle change rate of an air moving target according to a translation simulation model, a rotation simulation model and an echo model of the air moving target; selecting a target imaging arc section according to the earth-centered earth-fixed coordinate system coordinates of the transmitting station, the receiving station and the air moving target; therefore, the high-resolution imaging of the air moving target can be quickly and accurately obtained according to the target imaging arc segment, and the processing efficiency and the image quality can be effectively improved.

The invention discloses a scattered wave seismic acquisition and imaging method based on a full random observation system, which belongs to the technical field of seismic exploration and comprises a quasi-Monte Carlo random observation array design step, a scattered wave intelligent identification and enhancement step, a sparse wave field reconstruction step and a multi-target optimization imaging step. The limited equidistant property is ensured through the random observation array design based on a low-difference sequence, intelligent separation and enhancement of scattered waves are realized by using a physical constraint neural network, a sparse reconstruction problem is solved by using an alternating direction multiplier algorithm, a multi-target optimization imaging framework is constructed to realize high-resolution imaging, and high-resolution imaging is realized. The four core steps form a closed-loop cooperative system, sparse reconstruction quality evaluation feedback optimizes observation array design, imaging quality measurement feedback adjusts scattered wave identification parameters, and cooperative interaction is achieved.

The invention relates to a method and system for gradient drying of butyronitrile gloves after impregnation in the field of intelligent manufacturing, and the method comprises the steps: obtaining surface and internal moisture content data of an adhesive film through a sensor array, generating a real-time moisture distribution matrix, and determining a moisture gradient change trend; if the moisture gradient change trend exceeds a preset threshold value, calculating a local moisture evaporation rate according to the distribution matrix to obtain a dynamic temperature and humidity regulation and control parameter; obtaining an adhesive film surface image through a high-resolution imaging system, detecting micro-crack and white point defect areas, and determining defect distribution characteristics; adjusting power distribution of the composite heating system according to the lowest energy consumption operation parameters, and generating an efficient drying operation mode; updating data of the dynamic regulation and control parameters and the defect distribution characteristics are obtained through a feedback control algorithm, and final drying process parameters are determined; and generating a production control instruction from the final drying process parameters, and outputting the production control instruction to a drying equipment controller to finish uniform diffusion of moisture of the adhesive film and elimination of surface defects.

The invention discloses a nanoscale saw blade shape optimization and production method adopting a neural network. The nanoscale saw blade shape optimization and production method comprises the following steps: S1, performing high-resolution imaging and modeling on an initial shape of a nanoscale saw blade by utilizing a scanning electron microscope and a three-dimensional confocal microscopic measurement technology; s2, constructing a shape optimization model based on a convolutional neural network; s3, generating a virtual saw blade shape data set by using the generative adversarial network, and training an optimization model in combination with experimental data; s4, performing multi-scale performance verification on the optimized saw blade shape by adopting a finite element analysis and molecular dynamics simulation technology; s5, realizing high-precision manufacturing based on a femtosecond laser nano processing technology; s6, performing shape measurement and surface roughness evaluation on the processed saw blade by using an optical interferometer and an atomic force microscope; and S7, integrating an automatic shape detection and feedback adjustment module through the programmable logic controller, and correcting the machining deviation in real time. The method has the advantages of being high in design precision, high in machining consistency and high in production efficiency.

The present invention discloses a sparse aperture ISAR maneuvering target imaging and calibration method, comprising the following steps: establishing a maneuvering target ISAR sparse aperture signal model, characterizing the maneuverability of the target by constructing a variable scale non-uniform Fourier two-dimensional dictionary containing MTRC; constructing a parameterized sparse imaging model by maximum a posteriori estimation, expressed as a cost function of joint target parameter estimation and sparse imaging; finding the target rotation parameter by the minimum entropy method, and implementing a rough estimation of the maneuvering target rotation parameter by performing parameter iteration by the coordinate descent method; and implementing high-quality imaging with MTRC correction and accurate parameter estimation by combining sparse ISAR imaging and target rotation parameter estimation, decomposing into sparse imaging and dictionary learning, and iterating and solving in sequence. The present invention realizes the use of sparse aperture echo data to solve the problem of high-resolution imaging of ISAR maneuvering targets, greatly increasing the implementation scope and application scenarios of radar imaging.

The invention discloses an organic rare earth luminescent complex scintillator as well as preparation and application thereof. The molecular structural formula of the complex is L13ML2, M is Tb, Eu or Er metal ions, and the valence state is + 3; l1 is a tetraphenyl diphosphine imide anion ligand (tpip) or a substituted tpip ligand; l2 is unsubstituted or substituted 2, 2 '-bipyridyl, 1, 10-phenanthroline and a non-ionic chelating group containing a polyheterocycle / fused heterocycle. The organic rare earth luminescent complex scintillator can effectively convert high-energy X-rays into narrow-band visible light and near-infrared light, and is suitable for being applied to the fields of high-energy ray detection and high-resolution imaging.

The invention relates to the technical field of tumor fluorescence contrast agents, and particularly provides a conjugate of indocyanine green and multi-arm polyethylene glycol or pharmaceutically acceptable salt of the conjugate and a preparation method and application of the conjugate, the conjugate has the structural formula shown in the formula (I), the binding capacity of the conjugate and serum protein is remarkably reduced, and the conjugate can be applied to tumor fluorescence contrast agents. According to the present invention, the tumor targeting property is significantly improved, and the tumor is accumulated and detained in the tumor tissue, such that the targeted treatment or the high-resolution imaging is achieved so as to achieve the accurate tumor positioning and diagnosis, the high application value is provided, and the new method is developed for the tumor imaging and the treatment.

The invention relates to the technical field of medical imaging, and discloses a peripheral lung cancer pleural invasion evaluation system based on ultrasonic targeted radiography, comprising: a double-frequency ultrasonic probe configured to independently work at different frequencies to realize depth imaging and high-resolution imaging of lung tissues and suitable for different types of lung lesions; the signal processing module can receive, analyze and process echo signals transmitted by the ultrasonic probe, generate images in real time and extract feature information; and the dynamic motion compensation module is used for automatically adjusting the emission time sequence and parameter setting of the ultrasonic signal based on the real-time breathing motion state of the patient. By adopting the design of the double-frequency ultrasonic probe and the core-shell structure, high-resolution imaging and depth detection of lung tissues are realized. By dynamically adjusting the thickness of the probe shell to be matched with the frequency, the system can adapt to complex tissue environments under different physiological conditions, and image definition and stability are ensured.

A camera-based optokinetic motor device (OMR) for assessing visual acuity in rodents, consisting of: a. a two-chamber structure consisting of: ◯ an outer rotating chamber with an inner surface of alternating black and white vertical stripes, designed to produce an optokinetic visual stimulus; ◯ an inner static chamber, which is transparent and centrally positioned within the outer chamber and configured to accommodate the test object, wherein the inner chamber contains a centrally arranged, non-rotating platform for placing the rodent; b. a motorized rotation mechanism, comprising: ◯ a stepper motor that is operationally coupled to the outer chamber to enable controlled rotation at a fixed and adjustable speed; ◯ a switch-controlled rotation direction system that enables bidirectional movement, allowing both clockwise (CW) and counterclockwise (CCW) rotation at a predefined speed of 10 revolutions per minute (rpm); c. a high-resolution imaging system, consisting of: ◯ a high-resolution (HD) camera positioned at an optimal height above the device to capture the rodent's movement response in real time; ◯ a motion tracking module, either software-based or hardware-integrated, to analyze and quantify the subject's spatial frequency threshold (SFT) in response to the moving stimulus; d. a closed test environment, consisting of: ◯ a non-transparent housing surrounding the dual-chamber structure, forming a closed box configuration approximately 45 cm long and wide and 30 cm high to minimize interference and distractions from external light; ◯ an internal white LED lighting system on the inner wall of the housing, which ensures uniform lighting conditions and thus guarantees the clarity of the recorded visual data; e. a data acquisition and processing module configured to: ◯ Record the video data received from the HD camera; ◯ Processing and analyzing rodent movement patterns using the rotating stimulus to determine the optokinetic reflex (OKR) and visual acuity response; ◯ Save and export the collected data for later statistical analysis.

The invention relates to the technical field of radar target characteristic analysis, in particular to a radar near-field target polarization characteristic analysis method based on a vector Green function. Firstly, a target three-dimensional scattering point model is constructed, a coordinate-based scattering coefficient is defined, a full-polarization observation mode is designed, a near-field measurement matrix is calculated based on a vector Green function, and an observation model is constructed. Secondly, designing a fusion far-field constraint orthogonal matching pursuit (OMP) algorithm, realizing high-precision inversion of scattering coefficients, calculating a target far-field single-station RCS (HH / HV / VV mode) through dynamic polarization-based projection and phase compensation, and establishing a near-far field scattering characteristic mapping model; according to the method, near-field three-dimensional imaging and far-field polarization characteristic analysis are fused, the problem of insufficient cross polarization component recovery in a traditional method is solved, and the method has the advantages of high-resolution imaging, multi-physical field collaborative optimization, adaptive noise suppression and the like, and can be applied to the fields of stealth target recognition, radar cross section testing, unmanned aerial vehicle navigation and the like.

The invention discloses a satellite-borne ultrahigh-resolution SAR (Synthetic Aperture Radar) system and a working method thereof. The system comprises a signal processor, a frequency multiplication unit, a receiver, a synthesis network front end, a traveling wave tube amplifier group, an amplitude limiting low noise amplifier, a magic T, a waveguide switch, a circulator, a waveguide load and an umbrella antenna, the system is loaded on an agile satellite platform, and large-angle scanning imaging of a target area is achieved by means of maneuvering of the platform. Various working methods are provided through combination of output signals of different ports of the magic T. The ultra-high resolution imaging system has the advantages that ultra-high resolution imaging superior to centimeter-level resolution is realized, the working mode is flexible, the reliability is good, the system composition is simple, the volume and the weight of the product are reduced through centralized transmitting and receiving, the weight is light, the heat consumption is small, and the engineering development cost and difficulty are reduced.

The invention relates to a color laser printer printed product identification system and method, and the system comprises a scanning module which is used for scanning a printed product printed by a printer to form a first image, and the printed product is provided with a special mark; the image processing module is used for preprocessing the first image to obtain a second image; the transcoding module is connected to the image processing module or the scanning module, and is used for identifying a special mark in the first image or the second image to obtain a single mark matrix representing printing information; and the decoding module is used for interpreting the single mark matrix to obtain printing information corresponding to the printed product. The scanning module captures special marks on the surface of a printed product through a high-resolution imaging technology, and complete extraction of tiny marks is ensured. The image processing module performs preprocessing such as noise reduction, contrast enhancement and geometric correction on an original image, so that the definition and identifiability of a mark are remarkably improved, and interference factors such as paper wrinkles and stains are effectively handled.

The application discloses a kind of nnUNet zebra fish juvenile whole brain vascular system segmentation methods based on autonomous data set training, it is related to high-resolution imaging technology, image processing and medical image segmentation field, the method makes full use of zebra fish live transparency and fluorescent label advantage, obtains high-resolution whole brain three-dimensional vascular image data, and constructs high-quality segmentation truth value database by semi-automatic segmentation and artificial correction, training is carried out using nnU-Net deep learning model, realize the three-dimensional automatic segmentation of zebra fish brain vascular system signal.The application method significantly improves the degree of automation and precision of image segmentation, effectively solves the problems of low efficiency, high artificial dependence and poor repeatability of traditional brain vascular segmentation.The method is suitable for large-scale high-throughput data processing, can provide efficient, standardized image processing scheme for zebra fish brain vascular development mechanism and brain vascular disease model research, and has wide application prospect.

The invention relates to an aliasing image target recognition and positioning algorithm based on sub-view-field shape modulation coding, relates to the technical field of aliasing image target recognition and view field judgment and positioning, and solves the technical problem that the scale and view field of a detector cannot be considered when large-view-field and high-resolution imaging is realized under the condition of a limited detector in the prior art. The algorithm comprises the following steps: identifying a foreground target; tracking a target rotation state; and judging the relevance between the target motion trail and the light spot shape change trend and inversely solving the actual spatial position. According to the aliasing image target recognition and positioning algorithm based on sub-view-field shape modulation coding, space-based early warning and large-width detection are achieved through the advantages of low power consumption and low cost of a small target surface detector, and the bottleneck that large-view-field imaging of an infrared optical system is limited by the manufacturing process of an infrared detector is broken through. According to the invention, through continuous frame light spot morphological feature extraction and trajectory-shape double-domain correlation modeling, unique determination and high-precision positioning of a view field of an object space where a target is located are realized.

The invention relates to the technical field of machining, and discloses a single-crystal high-temperature alloy grinding machining plastic deformation layer thickness identification method and system, and the method comprises the steps: collecting a port section image through the high-resolution imaging capability of a scanning electron microscope, and carrying out the preprocessing of the collected image, utilizing a Canny edge detection algorithm to accurately identify edge information in the image; performing crystal edge frame identification by using a Hough LinesP rectangular detection algorithm to calculate the crystal direction angle of each crystal in the image to distinguish the crystals in an undeformed area and a deformed area and the maximum depth value of the crystals in the corresponding area, and combining a preset crystal angle identification threshold value in a plastic deformation area after the single crystal high-temperature alloy material is ground and processed to identify the crystal edge frame of the single crystal high-temperature alloy material. And obtaining the thickness value of the plastic deformation area after the single-crystal high-temperature alloy material is ground. According to the method, the thickness value of the plastic deformation area of the ground single-crystal high-temperature alloy material can be accurately analyzed, and powerful technical support is provided for control and optimization of material machining quality.

The invention belongs to the technical field of radar imaging, and particularly relates to a radar sparse three-dimensional imaging and resource scheduling method based on ring array nesting, which comprises the following steps of: establishing a sparse imaging model under an OFDM (Orthogonal Frequency Division Multiplexing) framework; providing a sparse two-dimensional imaging method; proposing a pitch angle reconstruction method based on phase interference; calculating imaging parameters required by resource allocation in the multi-target imaging scene; and establishing an adaptive resource scheduling optimization model and providing a solving method. According to the radar sparse three-dimensional imaging method based on circular ring array nesting, three-dimensional high-resolution imaging is achieved under the condition that a small number of radar resources are consumed. And a self-adaptive resource scheduling algorithm is provided, so that a multi-target imaging self-adaptive resource scheduling model is established by taking time saving, improvement of array element and frequency band utilization rates and balance of radiation intensity of a mode selected by each target as optimization targets, and reasonable allocation of limited radar resources is realized.

The invention relates to the technical field of semiconductor testing, and discloses a semi-automatic PIN correction method for an MEMS probe card, which comprises the following steps: fixing the probe card on a fixed platform, and adjusting the focal length and magnification of a large tool microscope through an operation interface, so that a probe is displayed in an image acquisition system; starting an image acquisition and processing system, acquiring initial images of the probe and the target PIN point, and extracting position and size parameters of the probe; the device comprises a large tool microscope which is used for carrying out high-resolution imaging on a probe and observing the relation between the probe and a target PIN point; and the probe card fixing platform is used for fixing the probe card. The technical scheme based on high-resolution image acquisition and real-time feedback adjustment is adopted, accurate alignment between the probe card and the target PIN point is achieved, and it is ensured that the probe card can be accurately in place in each step in the calibration process through real-time image feedback and accurate path optimization.