106results about How to "Restore accurately" patented technology

The invention relates to the technical field of data processing, and discloses a vehicle-mounted head-up display visual focus prediction method and device, equipment and a medium, and the method comprises the steps: collecting an activity video of eyeballs of a user; determining a historical movement track of the sight focus based on the activity video, and calculating the delay time of the vehicle-mounted head-up display system according to the historical movement track; predicting a screen projection position corresponding to the sight line focus of the next frame according to the delay time to obtain predicted coordinate information; and controlling the vehicle-mounted head-up display system to execute projection operation according to the predicted coordinate information. The problem that the screen projection position is not matched with the actual visual focus position of the driver due to delay in the AR-HUD system in the existing eyeball tracking technology is solved.

The invention discloses a visual detection precision improving method and system based on a high-resolution image. The system comprises a plurality of modules such as image acquisition equipment, a lighting system, an image processing unit and a mechanical positioning system. The image acquisition equipment adopts a high-precision industrial camera to acquire high-resolution images, and the illumination system provides uniform and adjustable illumination. Through the steps of image preprocessing, gradient calculation, Canny algorithm application and the like, the edge and geometric features of a detected object are accurately extracted, and size measurement, precision evaluation and defect detection are achieved. The visual detection precision can be effectively improved, the method is widely suitable for detection of various products such as automobile parts and electronic products, dimensional deviation and defects can be found in time, the production efficiency and the product quality are improved, and the method has important practical value and wide application prospects.

The invention discloses an offset cancellation circuit, which comprises a signal conditioning unit used for processing an input signal and outputting a first current signal, an offset cancellation unit used for removing offset current in the first current signal and outputting a second current signal, and a signal processing unit used for processing the second current signal and eliminating offset voltage, the detuning elimination unit specifically comprises a chopper, a digital analog converter, a successive approximation register logic module and a comparator which are connected in sequence, and through multi-level detuning elimination, the precision of the whole circuit is improved, the processing capacity for weak signals is enhanced, the anti-interference capacity is improved, and noise is reduced; the method ensures the stability of long-time operation, and has a wide application prospect in the field of high-precision signal processing.

The invention belongs to the technical field of textile traceability, and particularly relates to a textile traceability method and system based on a block chain, and the method comprises the steps: analyzing the textile data integrity based on a block chain network, judging whether the textile data is complete or not, analyzing the textile traceability access confidence, and judging whether the textile traceability access behavior is credible or not. And analyzing the textile traceability query result, comparing to obtain textile traceability data, analyzing the textile traceability data state, and comparing to obtain a textile traceability data risk point. According to the method, the problems of inaccurate and missing data possibly existing in traditional textile data traceability related information and incomplete judgment of the textile data traceability access verification state are solved, the whole production resume of a product can be restored more accurately, risk points in a supply chain can be found and positioned favorably, and the quality of the product is improved. And a basis is provided for improvement.

The invention relates to the technical field of magnetic suspension compressor assembly, and particularly discloses a magnetic pollution source prevention and control optimization method in a magnetic suspension compressor assembly process, which comprises the following steps: in a pretreatment stage of magnetic suspension compressor assembly, dynamically optimizing thermal cycle parameters in a low-temperature environment by adopting a self-adaptive genetic algorithm; ferromagnetic impurities hidden in microdefects of the compressor component are accurately induced to be released in advance; carrying out feature extraction and pattern recognition on the released impurity signals in combination with wavelet packet transformation and a neural network algorithm; according to the method, a low-temperature thermal cycle process optimized by a self-adaptive genetic algorithm is constructed in the pre-assembly treatment stage, ferromagnetic impurities hidden in microcracks are accurately induced to be released in advance, and accurate removal of the impurities before entering the assembly link is realized by combining wavelet packet transformation and targeted pulse demagnetization driven by a neural network; the limitation that impurities in the microdefects cannot be touched by a traditional cleaning and demagnetizing method is broken through, and the hidden danger of magnetic pollution which cannot be found by initial detection is eliminated from the source.

This invention discloses a concrete testing device for road and bridge construction, relating to the field of concrete testing. It includes a sample holder and a movable pressure plate. Vertical plates are fixed to both sides of the upper surface of the sample holder, and top plates are fixed to the top of each of the two vertical plates. A limiting groove for placing concrete blocks is formed at the center of the upper surface of the sample holder. The pressure plate is located above the limiting groove, and a groove is formed at the center of the upper surface of the pressure plate, in which a liquid storage cylinder is fixed. Liquid permeation holes are formed at the groove and at the bottom of the liquid storage cylinder on the lower surface of the pressure plate. A pressure application component and two transmission components are provided above the liquid storage cylinder. The two transmission components are symmetrically arranged on the pressure application component. Each of the two rope-winding rollers has an inner sprocket tooth on one corresponding spoke. This invention achieves simultaneous testing of concrete compressive strength and impermeability, shortens the testing cycle, and restores the stress environment of road and bridge concrete during actual service, improving the comprehensiveness and reliability of the test data.

The application discloses a kind of based on deep neural network's tire ground pressure distribution form prediction method, method includes: generating simulation sample;Calibration is carried out to simulation sample, and calibration sample is obtained;Performing physical information-driven data enhancement operation, integration generates multi-working condition sample library;Deep neural network model is built;Deep neural network model is iteratively trained and model weight solidification is completed, and prediction model is obtained;It is predicted;The deep neural network of the application is constructed by encoder-decoder architecture, and the tire ground pressure distribution calculation that traditional finite element simulation needs several hours to complete is compressed to millisecond order, and the technical bottleneck of time-consuming physical simulation is broken through.In the absence of any physical sample, only by inputting structure design parameters and working condition parameters, the pressure distribution form covered in full working condition can be obtained in real time, supporting the rapid screening and optimization iteration of hundreds of tire structure schemes in a single day, significantly shortening the tire development cycle.

This invention relates to the technical field of simulation analysis methods for downhole tools in oil and gas fields, and discloses a high-precision dynamic simulation analysis method for full-size drilling and milling tools based on an adaptive FEM-SPH coupled algorithm. The method includes three processes: model establishment, model solving, and performance evaluation. The first process is model establishment, which involves obtaining the geometric model of the drilling and milling tool through model reconstruction technology, and establishing a high-precision dynamic simulation analysis model for the full-size drilling and milling tool based on a wear prediction model and the adaptive SPH-FEM coupled algorithm. The second process is model solving, which involves solving the model after successively changing the drilling pressure and rotational speed, and batch processing the simulation results using Python. The third process is performance evaluation, which evaluates the performance of the drilling and milling tool from three aspects: efficiency, safety, and lifespan. This invention improves simulation accuracy from three aspects: geometric modeling, wear simulation, and solution algorithm, and evaluates the performance of the drilling and milling tool from three aspects: efficiency, safety, and lifespan.

The application is suitable for the technical field of data processing, and provides a negative feedback monitoring method applied to media data, which comprises the following steps: step S1: media data collection and fusion: collecting media data and user interaction behavior data from different channels, and constructing a unified user session sequence model to time-correlate multi-modal data within a single user session; step S2: multi-modal negative feedback feature fusion: processing the media data, extracting negative feedback features of text, vision, audio and user behavior modes, and analyzing the correlation between different modal negative feedback features by using a cross-modal correlator. The application effectively avoids the problem of cross-session data fragmentation by limiting the operation range of the user session sequence model to a single continuous access period.

The invention relates to an industrial internet data compensation method, which comprises the following steps of: monitoring industrial internet data, performing real-time data anomaly detection by utilizing a machine learning algorithm, and processing at a data source in combination with an edge computing technology, so that delay and bandwidth consumption are reduced; an algorithm for adaptively adjusting a compensation strategy according to data characteristics and historical trends is developed, the compensation accuracy and efficiency are improved, multi-dimensional integrity verification is carried out on data in combination with methods of checksum, hash functions and digital signatures, and more comprehensive safety guarantee is provided; according to the data compensation method provided by the invention, the overall change trend of real data and the accuracy of a single data point can be accurately restored, enough precision is provided, and meanwhile, the method can be applied to a plurality of industrial internet scenes and shows good performance.

The invention provides an urban skyline live-action visual touch interaction optimization method based on multi-scene simulation. The method comprises the following steps: acquiring three-dimensional live-action data of an urban target area; uploading the three-dimensional live-action data to a digital twinborn visual platform, and reconstructing a skyline lightweight live-action model of the urban target district; recording and translating behavior and instruction information of a user for adjusting the skyline model one by one by using a wearable device, and summarizing the behavior and instruction information into preference training data; defining each building monomer in the skyline model as an agent, defining the action and reward function of the agent, and solving the skyline optimization problem of the skyline model by adopting multi-agent deep reinforcement learning; judging whether the loss function and the reward function meet requirements or not; and storing the output scheme, outputting the output scheme to a holographic sand table for operation and display, and performing secondary accurate adjustment. According to the invention, the behavior data of the skyline model can be adjusted based on the user, and the city skyline optimization scheme better meeting the user demand can be quickly generated.

This invention relates to a super-resolution reconstruction method for UAV images of kiwifruit sunburn. Compared with existing technologies, it solves the problems of poor model generalization due to the lack of accurate modeling of the actual physical degradation of UAVs, and the difficulty of feature extraction networks in simultaneously considering global semantics and local high-frequency lesion details, resulting in blurred reconstruction. The invention includes the following steps: acquisition and preprocessing of UAV images of kiwifruit sunburn; generation of multi-scale paired datasets; construction of a super-resolution reconstruction model for kiwifruit sunburn images; training of the super-resolution reconstruction model for kiwifruit sunburn images; acquisition and preprocessing of UAV images; and super-resolution reconstruction of UAV images. This invention significantly eliminates boundary artifacts in image processing by constructing a multi-scale attention and spatial-frequency fusion mechanism, accurately restoring the high-frequency edge texture details of small lesions at different scales, and reducing data acquisition time.

The present application relates to a kind of light path attenuation dynamic compensation methods of full spectrum water quality multi-parameter measurement, to solve the nonlinear light path attenuation influence caused by light source aging, optical window pollution and water body suspended particles.The technical scheme includes constructing three-dimensional attenuation fingerprint library, real-time acquisition and fusion multi-dimensional spectral characteristics, through double-branch encoder discriminant attenuation source mixed attribution probability, and then weighted generation full-waveband dynamic attenuation mapping relationship, to realize waveband by waveband reverse compensation and absorbance reconstruction.Residual high-frequency energy distribution monitoring and fingerprint library adaptive updating mechanism are used to automatically capture and fuse abnormal working conditions, achieving closed-loop optimization without periodic manual calibration.The scheme can significantly improve the spectral data correction accuracy and system parameter inversion reliability, and enhance environmental adaptability and long-term stability.

The embodiment of the invention provides a medical knowledge graph construction method and device. In the method, a page in an electronic file of a first medical literature is input into a large model, entity data of entities in the page are obtained through recognition, the recognized entity data are combined into a constructed knowledge graph through semantic similarity matching, the combination comprises the steps that the entities serve as nodes, knowledge points serve as attributes of the nodes, and the attributes of the nodes serve as attributes of the first medical literature. And constructing a typeless connection edge between the entity and the associated entity thereof. And when the entity data corresponding to all the pages of the electronic file are merged into the constructed knowledge graph, obtaining the medical knowledge graph of the first medical literature. Wherein the entity data comprises entity names, entity types, associated entities and knowledge points related to the entities. The knowledge point text is an original sentence of text content in a page or a slightly modified text, and contains complete and rich association relationship information between associated entities. Private data need to be protected in the construction process.

The application provides a three-section data processing method, which comprises the following steps: according to the time channel sequence of downhole data to be processed, processing time spectrum data corresponding to each time channel based on a first compression rule; when the time spectrum data corresponding to a certain time channel meets a second compression rule, processing time spectrum data corresponding to each time channel based on the second compression rule from the current time channel; and when the time spectrum data corresponding to a certain time channel meets a third compression rule, processing time spectrum data corresponding to each time channel based on the third compression rule from the current time channel. In the construction idea, the application customizes a new three-section data compression and packaging method according to the actual situation of the downhole logging instrument measurement curve, and the method can better adapt to the downhole logging instrument compared with the common compression algorithm in the prior art.

The present invention relates to the field of signal encryption technology, specifically to an aviation data bus signal encryption method and system based on FPGA, comprising the following steps: based on the input three-dimensional tensor signal data, extracting slices at fixed intervals by the time index of the aviation data bus, and segmenting after the amplitude of the signal channel is sorted in ascending order. In the present invention, the processing logic of matrix decomposition and characteristic curve generation optimizes the feature extraction and dimensionality reduction process, improves the distinguishability and representation ability of feature information, and the key generation method combining dynamic perturbation factors with encryption parameters enhances the randomness and anti-cracking ability of the key, ensures the security of signal transmission, and combines amplitude superposition with frame-by-frame storage to realize the dynamic and efficient signal encryption process, reduce the risk of signal tampering and eavesdropping, and ensures the accurate restoration of signal amplitude through feature reconstruction and point-by-point matching processing in the decryption stage, and ensures data integrity and anti-interference ability.

The invention discloses an impact response spectrum time domain conversion method, a computer readable storage medium and a program product, and relates to the field of mechanical environment design of aircrafts, and the method comprises the steps: carrying out the time domain conversion of a reference impact response spectrum, obtaining a basic waveform y0, defining the whole waveform duration time of the basic waveform y0 as t0, and enabling the basic waveform y0 to adopt a sine wave xsin as a fundamental wave, the waveform delay time of the fundamental wave relative to the zero moment is tdi; a manual intervention waveform y '0 adopts an attenuation sine wave xexp as a fundamental wave; when t is smaller than or equal to t0, t is controlled to be equal to tdi, a manual intervention waveform y '0 is obtained, and the specified impact action time of the manual intervention waveform y' 0 is defined as t '0; 0 lt; the manual intervention waveforms y '0 and t' 0lt within the time interval t < = t '0; and combining the basic waveforms y0 in the time interval t < = t0 to obtain a target time domain waveform y. Defects of a traditional method can be effectively avoided, the accurate prediction requirement of an aircraft impact environment is met, and the effectiveness of an aircraft impact assessment test is supported.

This invention relates to the field of gas pipeline safety monitoring technology, and discloses a method for predicting the risk situation of underground gas pipelines based on neural network 3D modeling. The method includes: collecting multi-source heterogeneous data of the pipeline network and preprocessing it to generate a standardized fusion dataset; extracting spatial and temporal features based on a fusion neural network of CNN and LSTM, and generating a 3D model of the pipeline network by combining GIS coordinates; analyzing the risk factor weights using the Grey-DEMATEL-ISM method, and using the N-K model to calculate multi-factor coupled risks to generate the coupled risk level of each pipe segment; predicting the risk situation based on the 3D model features and coupled risk results, and outputting graded early warning information.

The application discloses a method for supporting multi-terminal touch screen information collection and restoration. A data collection terminal collects touch screen data on different signing terminals. A handwriting data conversion module in a data processing layer pre-processes the touch screen data obtained from the different signing terminals, converts multi-terminal handwriting data into standard handwriting data packets in a screen coordinate system, determines key frames of the touch screen data, fills in the blank between adjacent point positions of the touch screen data by using a tweening animation algorithm to ensure that there is no broken line, calls a Bezier curve algorithm to determine the intermediate frame inserted between the two key frames, so that the handwriting is smooth, and the obtained touch screen data is converted into lines close to the natural handwriting habit of a person. A rendering layer determines the size of a handwriting point according to the coordinates of a current point position on a canvas, real-time pressure data and a predetermined thickness, renders a handwriting track, and generates an electronic signature.

The application provides a nuclear fuel grid micro-oscillation fatigue failure evaluation method, and relates to the technical field of nuclear fuel grids, and comprises the following steps: obtaining an elastic wave signal and a normal clamping force of the nuclear fuel grid, then removing noise information in the signal to extract a pure high-frequency micro-oscillation impact signal, combining the normal clamping force to construct a time-domain load spectrum, calculating fatigue damage according to the load spectrum, and judging whether the grid fails or not. Through effective noise reduction and feature extraction on the elastic wave signal in a strong noise background, the real time-domain characteristics of the micro-oscillation impact can be accurately restored, so that the key time node of the transition of the contact surface from adhesion to sliding can be accurately positioned, the accuracy and reliability of the nuclear fuel grid micro-oscillation fatigue failure evaluation are significantly improved, the traditional offline estimation is realized to the full life cycle online evaluation based on the real dynamic load, and the structural integrity of the nuclear fuel assembly under the long-term service condition is effectively ensured.

The application discloses a yaw determination method and device, computer equipment and a storage medium, the method comprises the following steps: when the target vehicle yaw, obtaining the original trajectory point information, the actual yaw time, the path information of the re-planned path and the time of the re-planned path of the target vehicle; based on the original trajectory point information, determining the actual driving path of the target vehicle; based on the actual yaw time, the time of the re-planned path and the actual driving path, determining the yaw trajectory; based on the yaw trajectory and the planned path before the target vehicle yaw, determining whether the target vehicle is in an error-prone scene; if the target vehicle is in an error-prone scene, determining whether the yaw misjudgment occurs. Not only can the driver's driving path be restored more accurately, but also the original trajectory point can be compatible with the complex scenes such as the road network equidistance deviation and the parallel road, so as to determine whether the current yaw determination of the navigation engine is wrong, thereby improving the accuracy and integrity of the yaw determination of the navigation engine.

The invention belongs to the technical field of high-temperature coke ignition time measurement, and particularly relates to a device and a method for measuring high-temperature coke ignition time delay. The device for measuring the ignition time delay of the high-temperature coke comprises a plane flame burner, an image acquisition unit and a data processing unit, in the plane flame burner, a top preset section of a central powder feeding pipe extends into a hearth; the image acquisition unit is used for acquiring a motion trail diagram that coke particles output by the top preset section are gradually heated to be on fire; and the data processing unit is used for performing brightness data extraction according to the motion trail diagram to obtain ignition time, and taking the time interval from the time when the coke particles are output into the hearth from the top preset section to the ignition time as ignition time delay output of the high-temperature coke. According to the invention, the technical problem that only the ignition delay of normal-temperature pulverized coal can be effectively measured and the high-temperature coke with a certain temperature cannot be accurately measured in the prior art is solved.

The application provides a kind of iterative reconstruction network framework construction method based on reversible diffusion model, it is related to wireless communication technical field, its technical key points are as follows: the construction method steps are as follows: the sparse measurement value and environmental information of target area are obtained, the initial estimate to the original channel gain map is generated by the back projection of the adjoint operator of its measurement operator, and is used as the initial state of iterative process;Initial estimate is sent into a cascade network composed of T reconstruction steps for iterative optimization;The framework includes the core U-Net noise estimator weight, the learning parameter in two-stage reversible architecture and the related parameter of diffusion process, and all are optimized end to end by back propagation.The channel gain map construction method based on IDM proposed in the application reconstructs channel gain map from sparse measurement value using pre-trained diffusion model.The generated channel gain map is highly consistent with the real map in vision.

The utility model discloses a substitute body for dental implant, the substitute body is made of resin material and comprises a butt joint part, a positioning section and a fixing section, the butt joint part is arranged inside the fixing section, the butt joint part is connected with an abutment, the positioning section is connected with a dental cast body, the positioning section, the connecting part and the fixing section are arranged along the same central axis, and the butt joint part is connected with the positioning section. A butt joint groove is formed in the center of the butt joint part, the butt joint groove comprises a transition section and a clamping groove with the cross section being in a regular polygon shape, arc-shaped protrusions are arranged on the outer surface of the positioning section, the number of the protrusions is the same as that of the sides of the clamping groove, and the positions of the sides of the clamping groove correspond to the positions of the protrusions in a one-to-one mode. The oral cavity replacement device is reasonable in structural design, conditions in the oral cavity of a patient can be restored more sufficiently after the base is installed on the replacement body, and the replacement body can be installed and adjusted more conveniently; a dentist technician accurately restores the condition in the oral cavity of a patient through the replacement body, and the manufactured false tooth is excellent and is more adaptive to the oral cavity of the patient.

The embodiment of the invention discloses a page code generation method and device, a storage medium and a computer program product, and the specific implementation scheme is as follows: inputting a page design drawing into a drawing code model to generate an initial page code; converting the initial page code into a page effect picture; determining difference information between the page design drawing and the page effect drawing; the difference information and the page design drawing are input into a drawing code model to generate a target page code, and the target page code is used for generating a target page corresponding to the page design drawing. Based on the scheme, the page code of the corresponding target page can be automatically generated according to the page design drawing, the development efficiency of the page code is improved, the page code can be optimized according to the difference information of the generated page effect drawing and the original page design drawing, the quality of the page code is improved, and the user experience is improved. And accurate restoration of the page design drawing is realized.

This invention discloses a cable production identification and monitoring system and method based on cable images, belonging to the field of image recognition technology. The system includes: acquiring a sequence of cable surface depth images to construct a grayscale surface map along the cable surface depth direction; using the central ridge of the grayscale surface map as a dynamic axis of symmetry, detecting candidate pixels through multi-scale morphological top-hat transformation to form a symmetrical residual distribution map; combining the eight-neighbor gradient direction field and Hessian matrix curvature to remove false defect points, obtaining an effective image, and inputting it into a pre-trained multi-task neural network to simultaneously output a defect segmentation mask and category label; generating a three-dimensional mesh model with dimensional accuracy through Poisson surface reconstruction; and finally, using the physical coordinates of the defect center to drive a laser marking machine to mark a QR code containing key information, which is then associated and stored in a blockchain database. This application improves the accuracy and efficiency of defect identification, realizing the quantitative characterization and full lifecycle management of defects.

The invention provides a special-shaped part discrimination algorithm based on 3D target detection, and belongs to the technical field of logistics, and the algorithm comprises the following steps: 1, installing a plurality of 3D cameras according to the installation requirements; 2, respectively obtaining wrapped RGB images and depth images of three visual angles through a camera, and aligning the RGB images and the depth images; step 3, marking package coordinates and bottom coordinates thereof, modifying a yov8 segmentation model and training; 4, reasoning is carried out, and parcel coordinates, bottom surface coordinates and calculation projection coordinates of the parcel coordinates and the bottom surface coordinates are obtained; 5, fitting the calculated projection coordinates of the bottom surface and the coordinates of the bottom surface of model regression, and performing weighted fusion to obtain the final position coordinates of the bottom surface; 6, calculating the coordinates and curvature of the bottom surface through a bottom surface reduction algorithm, and correcting the shape of the bottom surface; 7, comprehensively judging the package of the special-shaped part to obtain a conclusion whether the package is a special-shaped part or not; the bottom surface features of the parcels can be comprehensively captured, the parcel feeding accuracy is improved, and the probability of wrong sorting is reduced.

The invention provides a video generation method and device, equipment and a storage medium, and belongs to the technical field of computers. According to the method, multiple pieces of reference information are coded respectively, the feature of the reference object instance corresponding to each piece of reference information and the feature of the description text can be bound, and the features of different pieces of reference information are unbound, so that the confusion of different pieces of reference information is avoided; therefore, the attribute of each reference object instance can be accurately restored in the generated video. Moreover, the scheme does not depend on regional constraints, so that the generated video has diversity and motion smoothness.

A carbon brush detection device of the present invention comprises a main body, a length detection assembly, a processor and a pressure detection assembly, the length detection assembly comprises a fixed probe rod, a movable probe rod, a displacement sensor and a driving assembly, one end of the fixed probe rod is arranged on the main body, the other end of the fixed probe rod is provided with a top plate, and the movable probe rod is movably arranged on the main body. The displacement sensor is arranged on the fixed feeler lever to detect the moving distance of the movable feeler lever, and the driving assembly is connected with the movable feeler lever to drive the movable feeler lever to move; the processor is electrically connected with the displacement sensor; the pressure detection assembly comprises a tension meter and a fixing band, the tension meter is slidably arranged on the main body, and the fixing band is arranged at the measuring end of the tension meter. According to the carbon brush detection device, the pressed state of the carbon brush in the actual state is accurately restored, deviation of detection data can be effectively avoided, the detection accuracy of the device is improved, meanwhile, in the detection process, multiple detection tools do not need to be used, and use is more convenient.

The invention discloses a full-flow microsecond-level measurement method and system based on data plane micro burst measurement, and the method specifically comprises the steps: carrying out the time-slot flow statistics of a data flow in a data plane, and obtaining a current time-slot flow observation value and a previous time-slot flow observation value; calculating a first-order difference based on the current time slot flow observation value and the previous time slot flow observation value to obtain a flow rate variable quantity; on the basis of the flow rate variable quantity and the historical cumulative variable quantity, lightweight chi-square testing is executed through a logarithmic projection technology, and a burst score is calculated; comparing the burst score with a preset threshold value, and if the burst score exceeds the preset threshold value, generating a burst report and reporting the burst report to a control plane; and receiving burst reports on a control plane, filling data between adjacent burst reports, and reconstructing a continuous flow rate curve of a data stream. According to the method, the contradiction among communication overhead, hardware adaptability and measurement granularity of the existing method is solved, so that high-fidelity and low-overhead microsecond-level telemetering is realized.