3113 results about "Mirror image" patented technology

The invention belongs to the field of data analysis, and discloses a data analysis method for engineering consultation digital intelligent management, which comprises the following steps: mapping multi-project heterogeneous data to a unified three-dimensional space-time grid through space-time grid division to form a grid mapping data set; detecting data format and attribute conflicts based on neighborhood correlation analysis, and distributing calibration data through dynamic weight; missing values and abnormal fluctuations are processed by using a time sequence autoregression model and a smoothing technology, and a complete data set with continuous time is constructed by combining linear interpolation and multi-dimensional data fusion; key indexes are extracted to construct a digital mirror image containing spatial positions, time sequences and attribute association, real-time data are synchronized, and outlier grid points are corrected; and multi-scene operation conditions are constructed based on the mirror image data, and a dynamic adjustment scheme is realized. According to the method, heterogeneous data are integrated through space-time grids, digital twinning and multi-scene simulation technologies are combined, and full-period management and risk intelligent decision-making of engineering data are achieved.

The present application belongs to the technical field of material processing, and relates to a mold-free mirror image filament laying method and a mold-free mirror image filament laying system. The method lays a filament ribbon in a mirror image symmetry, without a mold, thereby improving production flexibility and efficiency. The method acquires the temperature and pressure of the filament ribbon in real time, calculates the output power of a heater and the modification value of a filament laying end motion mechanism path by using temperature and pressure differences, and optimizes controller parameters through reinforcement learning, so as to realize stable control of the temperature and pressure. The system comprises a hardware part and a control system. The hardware part includes pressure and heat source components. The control system adjusts through real-time feedback to ensure the quality of filament laying. The present application solves the problem that the temperature and pressure are difficult to accurately control in the process of mold-free mirror image filament laying, and improves the performance of composite products.

The invention relates to an ERP non-core service migration method based on K8s dynamic resource scheduling, and belongs to the technical field of cloud computing containerization and ERP system optimization. The method comprises the following steps: identifying a non-core module based on business criticality, and generating a migration list; an internal interface is transformed into a standard API gateway route, and strong dependency communication is asynchronously decoupled through a message queue. Historical resource load data is collected, a periodic rule is extracted by using a time sequence decomposition model, a reference value is set, and a K8s scheduling parameter is generated. Adopting multi-stage construction to separate compilation and operation environments, and generating a lightweight mirror image; and implementing security reinforcement, and dynamically updating the health examination probe and configuration. Selecting a controller according to stateless and persistent requirements; the locality of NUMA domain resources is optimized through topology awareness scheduling; dynamic storage binds a persistent volume according to QoS; the network policy implements container-level traffic isolation. And dynamically adjusting the resource quota and the number of copies. The efficient and safe migration of the ERP non-core business in the K8s environment is realized.

The invention discloses a visual combined infrared precast beam appearance defect detection method, and relates to the technical field of civil engineering structure detection and nondestructive testing, and the method comprises the following steps: establishing an illumination time sequence observation layer, collecting multi-dimensional optical parameters aiming at the surface of a precast beam, and generating a dynamic reflection fingerprint baseline; and performing coherent phase decomposition based on the dynamic reflection fingerprint baseline, separating the specular reflection signal from the material texture signal, and calibrating light spot track and intensity evolution data in the unified baseline. According to the method, an illumination time sequence observation layer is constructed to generate reflection fingerprints, coherent phase decomposition and anti-fact playback are combined, reflection interference is stripped, and crack boundaries are recovered; time coordinates are reconstructed through double-mirror-image anchor points, and crack evolution is accurately recovered; phase conjugate projection and light field traction are combined, a dynamic threshold optical fence is established, the exposure rhythm is controlled in a closed-loop mode, and precise detection of the defects of the precast beam is achieved.

The invention discloses a multi-dimensional dynamic model sieve path platform construction method based on digital twinning. The method comprises the following steps: S1, constructing a multi-dimensional dynamic digital twinning model based on sieve path basic information; s2, screen channel operation data are collected in real time and mapped to the digital twinborn model to generate a dynamic twinborn mirror image; s3, based on the digital twinborn model and the screen way real-time operation data, analyzing the dynamic deviation between the digital twinborn model prediction parameters and the actual screen way operation data; s4, generating a parameter regulation and control instruction based on a dynamic deviation analysis result, adopting a closed-loop feedback mechanism to perform self-correction on parameters of the digital twin model, and synchronously optimizing operation parameters of a physical entity sieve channel to form construction of a sieve channel platform; according to the system, a closed-loop link of data acquisition, model diagnosis, parameter optimization and feedback execution is constructed, so that the problem of static parameter mismatch caused by working condition change of a traditional digital twin model is effectively solved, and the abnormal working condition identification response time is shortened.

The invention provides a data synchronization method which can be applied to the technical field of computer communication. The data synchronization method comprises the steps that a synchronization request initiated by a local server is responded, a virtual disk mirror image generated by converting a target file through the local server is received through a preset transmission channel, and the synchronization request carries an editing mode identifier of the target file; mounting the virtual disk mirror image to a serial bus control port of a remote server, so that the virtual disk mirror image can be identified as a removable storage device; if the editing mode identifier represents that the target file is in an editable state, acquiring change information generated by modifying the target file by a local server and / or a remote server by monitoring a file change event on the removable storage device in real time; and dynamically updating the virtual disk mirror image based on the change information to complete modification synchronization of the target file. The invention further provides a mirror image mounting method and device and a storage medium.

The invention relates to the technical field of metal material detection, in particular to a titanium alloy bar machining quality detection method and system, and the method specifically comprises the steps: carrying out the superpixel segmentation of the section of a titanium alloy bar, constructing a mirror image edge texture saliency value of a superpixel block based on the proportion of edge points in the superpixel block and the edge gradient, and carrying out the detection of the machining quality of the titanium alloy bar. Constructing the mirror image texture intensity of the titanium alloy bar by combining the gray level distribution concentration characteristics of the titanium alloy bar, and performing image segmentation on the section of the titanium alloy bar; and in each segmented region, based on the edge line fuzzy degree difference and the pixel gray level difference of each super-pixel block and the rest of super-pixel blocks, combining a mirror image edge texture saliency value to construct a segregation evaluation value of each super-pixel block, and based on the segregation evaluation value, carrying out titanium alloy bar segregation quality defect detection. The titanium alloy bar segregation defect identification capability is enhanced, the titanium alloy bar segregation defect detection accuracy under the titanium alloy bar mirror image scene is improved, potential problems can be found earlier, missing detection is avoided, and the defective rate is reduced.

The invention relates to the technical field of intelligent detection and identification of metal elbows based on image processing, and discloses an intelligent detection and identification method of metal elbows based on image processing. According to the method, mirror image filling 3 * 3 median filtering is carried out on an original image in a two-dimensional coordinate system of an original point of the upper left corner, and salt and pepper noise and boundary artifacts are removed; calculating horizontal and vertical gradients, amplitudes and directions by using central difference; bilinear interpolation is carried out on the positions of the sub-pixels in the smooth direction to suppress non-maximum values, and a 75% percentile threshold value is taken in a local pane to screen seed points; according to dynamic step length, forward and reverse tracking is carried out to extract a ridge line, and a complete edge is obtained by combining end point Euclidean combination and length elimination; and finally, calculating a turning angle point by point, accumulating a total bending angle, comparing the total bending angle with a single section and a total threshold value, and completing accurate anti-noise bending qualification judgment on line in real time.

The invention discloses a model training data construction method and device and a storage medium, and the method comprises the steps: obtaining an initial image data set comprising a plurality of initial images, and obtaining a to-be-modified region in the initial image for each initial image in the initial image data set; and for each to-be-modified area, modifying the to-be-modified area according to a preset automatic modification method to obtain a target image, and constructing training data based on the target image. The preset automatic modification method comprises at least one of text replacement, image mirroring, information erasing, cross-graph modification, noise addition and modification through a diffusion model, manual modification is not needed, and the training data construction efficiency is high. And the training data set comprises a plurality of methods for automatically modifying the image, so that the image detection model trained according to the training data set is used for detecting the image, and the accuracy of an obtained detection result that the image is tampered is relatively high.

The invention provides a notebook computer pre-installed environment simulation test method and system based on a virtualization technology, and the method comprises the steps: firstly creating a virtualization environment instance which is matched with a target notebook computer hardware architecture and comprises a pre-installed operation system and a preset software set, and then injecting a simulation user operation behavior sequence according to a predefined environment configuration strategy, the method comprises the steps of generating a dynamic test case set, executing and monitoring running state data in a virtual environment instance, generating an environment compatibility analysis report by extracting an abnormal response mode in the running state data, and finally adjusting resource configuration parameters of the virtual environment instance according to the environment compatibility analysis report. And generating the optimized pre-installed environment mirror image file, so that efficient and comprehensive simulation test on the notebook computer pre-installed environment is realized, and the test efficiency and accuracy are effectively improved.

The invention discloses a generative zero sample learning method based on two-state collaborative decoupling and semantic refining, and belongs to the field of generative zero sample learning. According to the method, static features such as a background, a structure and details of an image are decoupled, and dynamic common features are extracted by a cross-modal label generation module, so that complementary expression of the static and dynamic features is realized; the feature focus is dynamically adjusted according to different confusion types, the feature discrimination is enhanced, and cross-class interference is relieved; on the semantic level, by constructing a vision-semantic mirror image cross attention mechanism, bidirectional alignment between semantic features and visual features is achieved, and the multi-granularity capability and adaptability of semantic representation are further improved. According to the method, feature structure decoupling, confusion adaptive regulation and control and dynamic semantic alignment are taken as the core, the cross-category generalization ability and the generated sample quality are effectively improved, the performance bottleneck of traditional generative zero sample learning is broken through, and the method has high theoretical value and wide application prospects.

The invention relates to the technical field of defect detection, in particular to a bonding wire process defect detection method and system, and the method comprises the following steps: detecting coordinate positions of a bonding wire track starting point and a bonding wire track ending point, extracting and analyzing a tangential direction formed by continuous pixel line segments, determining a mirror symmetry center candidate point, and recording a direction change angle in a path segment. Bending deformation defect coordinates are positioned, cracking risk points are judged, and a bonding wire indentation type identification set is generated. According to the method, the starting point and the ending point of the bonding wire track are detected and extend to determine the symmetric offset point of the track through accurate measurement of the direction angle, so that potential tiny defects can be found earlier, the uniformity of the wire diameter is evaluated through the change of the distance between transverse and longitudinal coordinates, and the material strength is directly predicted through the change of the physical size; the product quality can be evaluated and optimized on a more microscopic level, the production efficiency and cost management are directly influenced, and meanwhile, the safety guarantee of a user is improved.

The invention discloses an intelligent power grid optimization scheduling method based on digital twinning, and relates to the technical field of power grid optimization scheduling, and the method comprises the steps: building a dynamic power grid mirror image model according to a standardized power grid data matrix, and generating an evolution trajectory prediction report through a quantum magnetic coupling mechanism; establishing a variable association network based on the evolution trajectory prediction report, and generating an optimization scheduling instruction set in combination with the standardized data matrix; executing an optimization scheduling instruction set to obtain magnetic potential gradient distribution, and generating a topology reconstruction scheme by identifying a magnetic potential change trend; and inputting the topology reconstruction scheme into the dynamic power grid mirror image model to generate an electromagnetic field evolution trajectory, and generating a safety scheduling report in combination with magnetic potential energy gradient distribution. According to the method, the power grid magnetic field data is coded into an evolution trajectory prediction report through a quantum-magnetic coupling mechanism, and high-precision risk pre-judgment is realized; a topology reconstruction scheme is dynamically generated according to the electromagnetic energy gathering trend, and the power grid optimization scheduling efficiency is improved.

The invention relates to a digital twin simulation and optimization method for a large-scale stamping production line, and the method comprises a rapid lightweight modeling technology, a multifunctional fault indicator feedback technology, a three-dimensional dynamic real-time driving simulation technology, and a big data analysis intelligent optimization decision technology. According to the method, virtual-real fusion and a three-dimensional dynamic technology are combined, a three-dimensional visual user interface oriented to the whole manufacturing process is developed based on Unity, the whole stamping production line is simulated in real time, potential problems are predicted and solved through real-time monitoring of the stamping production line, various problems influencing the production efficiency in the production process are optimized, and the manual management and control difficulty is reduced.

The invention discloses a method for preventing a PCIe switch internal link state from being recognized to be abnormal by an OS, and relates to the field of link state recognition anomalies, a high-risk link is recognized by obtaining a historical data set, configuration processing and algorithm optimization are carried out, an injection verification mirror image is obtained, and accurate link training control analysis is carried out based on the injection verification mirror image, so that the reliability of the PCIe switch internal link state is improved. Carrying out intelligent topology mapping management on the final link stability score to obtain an optimized topology; carrying out anomaly detection and hierarchical response control on the optimized topology to obtain a response action set; and carrying out repair or degradation processing on the link based on the response action set. And finally, the link state and the topological structure are updated according to the processing result to obtain a repair result and the updated topological structure, so that the high-risk link can be identified, the OS link state can be accurately judged, the system availability is improved, the misjudgment risk is reduced, and a dynamic degradation and active repair mechanism based on the actual risk levels (high, medium and low stability) of the link is provided.

The invention discloses a motion vector refinement for oversampling of time domain spread. A residual network is used to predict a set of residual motion vectors that provides additional motion data for portions of frames for which motion vectors are not provided, such as animation textures, mirrored / reflective objects, and / or moving objects without motion information.

The invention relates to the technical field of industrial automation and intelligent manufacturing, and discloses an industrial big data simulation verification system based on digital twinning, and the system comprises a physical entity module which is used for deploying an industrial sensor array and collecting the real-time parameter data of production equipment; the digital twin mirror image module is linked with the physical entity module through a data mapping engine, and synchronously updates a virtual mirror image model at a millisecond level according to the parameter change of the physical entity; and the data transmission module is used for transmitting the data acquired by the physical entity module to the digital twin mirror image module and the multi-source data fusion module through a 5G or industrial Ethernet, and is used for cleaning the acquired multi-modal industrial data and eliminating noise data. Through the physical entity-digital twin mirror image real-time linkage design, the limitation that traditional simulation is disjointed with entities is broken through. The industrial sensor array is combined with the edge calculation module, so that rigid linkage of physical production equipment, a real-time database and a digital twin mirror image is realized.

The invention relates to a mirror image file processing method and device, and relates to the technical field of container mirror image generation. The method comprises the steps of obtaining target file system directory information of a target container in response to a mirror image file export request for the target container; the target file system directory information of the target container is used for representing file system directory information of a writable layer of the target container; comparing the target file system directory information of the basic mirror image with the target file system directory information of the target container to obtain a difference file of the target container relative to the basic mirror image; constructing a layer file of a new incremental layer based on the difference file; writing a layer file of the incremental layer into a mirror image layer file directory of the basic mirror image, and updating a list file and an index file of the basic mirror image to obtain a mirror image file of the target container; the manifest file comprises metadata of each mirror image layer in the basic mirror image, and the index file comprises metadata of the manifest file. By adopting the method, the export efficiency of the container mirror image file can be improved.

The invention discloses an ERP (Enterprise Resource Planning) data intelligent supervision method based on the Internet of Things, which relates to the technical field of enterprise informatization, and comprises the following steps: constructing a time sequence integrity observation layer in an Internet of Things data acquisition link, embedding a mirror image time anchor in each sensor sampling point, recording electromagnetic interference, time service offset and queuing delay, generating a phase fingerprint time baseline, and obtaining a phase fingerprint time baseline; constructing a unified time reference framework; operating a causal coherent analysis mechanism based on a unified time reference frame, comparing instantaneous offsets of a mirror time anchor and a real-time timestamp, identifying a phase inversion region, extracting information of a corresponding sampling node, a production line position and an energy consumption unit, generating a high-risk time slice list, and determining a time correction boundary. According to the method, a time sequence observation layer and a time reference frame are constructed, phase abnormity is identified, a data trend is reconstructed, a regulation and control instruction draft is generated, sampling time sequence recovery and scheduling convergence are realized through time inversion control, data consistency and decision accuracy are improved, and a closed-loop control system is constructed.

The invention discloses a continuous overturning and pouring device for saggars, which relates to the related technical field of material conveying and blanking and comprises an overturning unit, a driving unit and a cover pushing unit. The overturning unit comprises a rotating motor, a rotating roller is arranged at the output end of the rotating motor, a baffle is arranged at one end of the peripheral side of the rotating roller, a bottom supporting plate is arranged at one end of the baffle, and a top supporting plate is arranged at the other end. The driving units are arranged on the two sides of the baffle in a mirroring mode, each driving unit comprises a second linear mechanism arranged at one end of the peripheral side of the rotating roller, a vertical L-shaped plate is arranged at the output end of the first linear mechanism, a transverse L-shaped plate is arranged at the upper end of the vertical L-shaped plate, and a cover blocking block further extends from the upper end of one short side of the C-shaped clamp. The cover pushing unit is arranged below a driving unit, a transverse rod is arranged at the output end of the fourth linear mechanism, and a pair of triangular blocks with right-triangle-shaped sections is arranged on one side of the transverse rod. According to the saggar overturning and discharging device, the saggar can be automatically overturned and discharged, and the saggar can be automatically overturned and put back to the roller conveyor.

The invention relates to the technical field of chip development, and discloses a transplanting method and device of a swan gap system, a storage medium and computer equipment, and the method comprises the steps: constructing a swan gap system to be transplanted based on a target chip, obtaining a corresponding source code, and then configuring a compiling configuration file in the source code, the compiling subsystem is used for establishing a compiling environment based on configuration information in the compiling configuration file, performing transplantation adaptation on a kernel layer in the compiling environment to generate a kernel mirror image, configuring the starting recovery subsystem, generating a root file system mirror image based on the file system configuration file, and starting the starting recovery subsystem. And finally burning the kernel mirror image and the root file system mirror image to a target chip, and performing function verification and test on the target chip. According to the method disclosed by the present invention, the swan-gap system transplantation including kernel layer transplantation, subsystem adaptation and root file system customization is designed and realized, so that the swan-gap system is successfully adapted to the target chip, and the accelerator equipment carrying the target chip can stably and reliably operate.

The invention relates to the technical field of medical data analysis and rehabilitation, in particular to a cerebral apoplexy patient rehabilitation exercise analysis system based on medical big data, which comprises a data acquisition module used for acquiring electromyographic signals, exercise data and behavior data of a patient to form a data set; the data processing and fusion module is used for preprocessing the electromyographic signals in the data set, normalizing motion and behavior data and fusing the motion and behavior data into a multi-modal feature vector; the hierarchical analysis module is used for performing motion intention recognition according to the preprocessed electromyographic signals and outputting an intention classification result, recognizing the motion intention and predicting a rehabilitation effect through a double-flow Transform encoder, and evaluating a behavior risk level in combination with a risk factor formula; the optimization module is used for dynamically adjusting the mirror image treatment intensity according to the risk level and optimizing the prediction model by adopting incremental learning; and the interaction module is used for generating a thermodynamic diagram superposition rehabilitation curve in the X-Y coordinate system, and marking doctor intervention suggestions to complete visual interaction.

The invention relates to the technical field of optical network operation and maintenance, and particularly provides an optical network fault prediction method and system based on MEMS characteristic embedding and digital twinning, and the method comprises the steps: collecting multi-physics field coupling parameters of optical network operation in real time through an MEMS multi-physics field coupling sensing unit which is disposed at an optical network key node and is embedded in a physical layer device; constructing an optical network cross-scale digital twin, inputting parameters to realize real-time synchronization and fault rehearsal of a physical entity and a virtual mirror image, and outputting a rehearsal result; constructing a fault prediction model based on an optical network physical mechanism, inputting parameters and rehearsal results to complete feature fusion and trend analysis, and outputting a fault prediction result; an intervention strategy is generated and subjected to twinborn virtual simulation verification; and after the verification is passed, driving the physical layer to execute intervention, and feeding back effect data to dynamically update twin model parameters. A closed loop of perception, modeling, prediction, intervention and feedback is formed, and the problems of prediction lag and low operation and maintenance efficiency in the prior art are solved.

The utility model relates to folding door equipment suitable for a laser cutting machine, which comprises an equipment outer frame, intervention ports are distributed in the equipment outer frame, guide devices are installed on the inner side of the equipment outer frame and located at the upper ends and the lower ends of the intervention ports in a mirror image mode, and folding door devices are connected to the guide devices. One end of the folding door device is connected with an inner frame on one side of the intervention opening through a hinge device, the folding door device comprises a first door body connected with the inner frame, the first door body is connected with a second door body through the hinge device, the second door body is connected with a guide device, and a sensing device is arranged on the inner side of the second door body. An in-place feedback device is installed at the corresponding position of the inner side of the equipment outer frame. Therefore, the second body and the first door body are opened in a folding mode, the space of the access opening is not occupied as much as possible, and large workpieces can be conveniently machined, taken and placed. The guiding device participates in opening and closing, so that a user can operate with one hand conveniently, and less force is applied.

The invention relates to the technical field of video recognition and analysis, and discloses a video recognition and analysis method based on physical characteristics. Video frame pixels are mapped to a two-dimensional coordinate system with the upper left corner as an original point, and mirror image expansion and median filtering are carried out on a gray level image; constructing a binary image based on a gray threshold value, and analyzing and extracting a target region by using a four-neighborhood connected domain; using neighborhood search and polar angle sorting to close the tracking contour, and generating equidistant re-sampling points based on Euclidean distance and an interpolation method; the curvature of the re-sampling points is estimated through a three-point difference algorithm, and zero denominator is avoided through numerical protection; performing discrete Fourier transform on the curvature sequence to extract a frequency spectrum, and normalizing an amplitude to form a standardized feature vector; and finally, inter-frame similarity is calculated based on the feature vector, and the most similar frame is automatically retrieved. By processing unified data standards in stages, edge noise is suppressed, sampling uniformity is ensured, and feature stability and cross-frame comparability are improved.

The invention discloses an adjustable flat plate type ozone generating device and an adjusting method thereof. The adjustable flat plate type ozone generating device comprises an ozone generating assembly, a radial magnetic field adjusting assembly and an axial magnetic field adjusting assembly, the radial magnetic field adjusting assembly comprises a radial rail base and a spiral line base disc, a plurality of radial rails are arranged on the surface of the radial rail base at equal intervals in the circumferential direction, and magnets are arranged in the radial rails in a sliding mode. The axial magnetic field adjusting assembly comprises a base and an axial track, the radial track base is installed on the base, and the base is driven by a ball screw mechanism to move on the axial track in a reciprocating mode. By arranging the radial and axial adjustable magnetic fields, the motion trail and energy distribution of high-energy electrons in the discharge channel are optimized, the activity of ozone generation reaction is effectively enhanced, and the device can maintain high ozone output efficiency for a long time in actual operation due to the establishment of a magnetoelectric cooperative discharge environment; meanwhile, through a mechanical adjustment structure of the electrode spacing and area, discharge parameters can be optimized in real time according to different working condition changes, the fluctuation of ozone yield is remarkably reduced, and the continuity and stability of system operation are ensured.

A method of brain imaging detection includes: dividing a brain image into a left brain medical image and a right brain medical image and obtaining the grayscale values of multiple pixels thereof, respectively; mirror-flipping one of the left and right brain medical images; performing a grayscale value subtraction with the mirror-flipped medical image and the other medical image to obtain a plurality of grayscale differences of the pixels; determining whether the grayscale difference of each pixel exceeds a grayscale difference threshold and whether a number of the pixels having the grayscale different exceeding the grayscale difference threshold is greater than or equal to a pixel number threshold; and when the number of the pixels having the grayscale difference exceeding the grayscale difference threshold is greater than or equal to the pixel number threshold, determining that the brain image is abnormal.

The invention discloses an atmospheric and vacuum distillation unit intelligent optimization method and system based on deep reinforcement learning, and relates to the field of oil refining and chemical engineering, and the method comprises the steps: collecting historical operation data from a distributed control unit and a real-time database of an atmospheric and vacuum distillation unit, and carrying out the preprocessing, and obtaining a preprocessed historical data set; constructing a process mechanism feature network through a graph neural network by using the preprocessed historical data set, mining an association relationship among equipment parts, extracting abstract features representing a process principle, and constructing a digital twin environment; in a digital twin environment, a meta-reinforcement learning algorithm is adopted to train a deep reinforcement learning agent, so that the deep reinforcement learning agent obtains meta-strategies adapted to different crude oil properties. According to the method, safe, stable and efficient intelligent optimization control is realized through a closed-loop operation mechanism of safe mirror image drilling and credibility driving, and the problem of optimization response lag caused by manual model adjustment due to crude oil property change in a traditional optimization technology is solved.

The invention discloses an image recognition system for cable joint forming defect detection, and particularly relates to the field of image recognition, which comprises an acquisition module, an interference modeling module, a comparison module, a feature fusion module and a screening module, the acquisition module is used for acquiring a cable joint image, constructing a triple identifier for each frame of image and a corresponding time sequence identifier, a workpiece number and an acquisition equipment number, writing the triple identifier into an identifier area in image data, and generating an image identity vector; the interference modeling module is used for receiving the lens parameters, the illumination parameters and the edge structure data of the previous frame of image, and constructing an incident path model according to the lens parameters and the illumination parameters. By constructing an image identity binding mechanism and an interference feature modeling link and combining a structural difference analysis and ghosting removal process, a non-ontology region is identified and isolated in an image coordinate domain, so that the problem of target misjudgment caused by a mirror image secondary image in image acquisition is solved.

The invention relates to the technical field of machine tool spindle performance testing, in particular to a high-precision spindle performance testing method and system, and the method comprises the steps: initializing a mirror image prototype of a spindle in a performance testing platform according to the main structure and working condition environment constraints of a spindle body; establishing a load control instruction set according to the mirror image prototype and based on the motion state of the main shaft body in the composite performance test scene; according to the load control instruction set, dynamic disturbance is executed on the spindle body, and performance change characteristics of the spindle body are captured in the disturbance process; combining the performance change characteristics with the mirror image prototype, executing self-organizing calibration of prototype parameters of the main shaft body, and generating an enhanced mirror image body with working condition adaptability; and a load control instruction set is newly calculated based on the enhanced mirror body weight, dynamic disturbance of multi-axis linkage is triggered, and a performance detection result is output. According to the invention, the problem of real-time mismatch of main shaft performance simulation and actually measured data under the high variable load condition is effectively solved.