62results about How to "Accurate mapping" patented technology

The invention relates to the technical field of battery management, and discloses a battery health state evaluation method and system for an electric tool energy supply device, and the method comprises the steps: obtaining multi-source sensor data in the operation process of an electric tool, and carrying out the preprocessing of the data; identifying and classifying multi-stage pulse discharge events, extracting multi-scale voltage response features and performing temperature compensation; equivalent circuit model parameter identification is carried out, abnormal identification results are checked and removed, and parameter aging characteristics are extracted; constructing a time sequence prediction model for prediction; evaluating the overall health state and the monomer consistency of the battery pack; defining a judgment standard of effective cycles, predicting the number of remaining effective cycles, calculating a confidence interval of a prediction result, and generating a battery management suggestion; formatting into a standardized evaluation report, carrying out data synchronization and model optimization through edge cloud collaboration, and recording a system operation log; according to the invention, accurate health state evaluation and residual life prediction are realized.

This invention discloses an online search method for particle spelling variants and properties usable by intelligent agents. The steps are as follows: inputting the baseline spelling of a particle and the constructed particle-specific prompt words into a large language model to generate a core variant corresponding to the particle; integrating the core variant of each particle with the authoritative benchmark information corresponding to the particle to form a full variant set for each particle; each record in the full variant set contains a unique identifier for a particle, a multi-scene benchmark name, a core variant, and extended attributes; dynamically mapping a remotely callable interface set on the server to a local proxy object on the client; after receiving a query request, the local proxy object parses the particle spelling parameters in the query request and performs multi-dimensional spelling matching in the full variant set to realize online search for particle spelling variants and properties. This invention effectively improves the ability of AI intelligent agents to handle domain-specific tasks.

The invention discloses a rapid magnetic resonance imaging reconstruction and segmentation method and system, a medium and a product, and relates to the technical field of image processing. The method comprises the following steps: decomposing original three-dimensional magnetic resonance data into a plurality of independent two-dimensional magnetic resonance data slices along a slice sequence; image reconstruction is carried out on the two-dimensional magnetic resonance data slices through a pre-trained forward generator in the frequency domain Schrodinger bridge diffusion model so as to generate a two-dimensional magnetic resonance image, and the forward generator integrates a Fourier convolution module and is used for carrying out frequency domain transformation and feature enhancement processing on feature mapping in the image reconstruction process; inputting each two-dimensional magnetic resonance image into a pre-trained segmentation model in sequence, performing segmentation of a target region and a preset dangerous organ, and generating a corresponding two-dimensional segmentation mask; all the two-dimensional segmentation masks are rearranged and stacked according to the slicing sequence, and a three-dimensional segmentation result is generated through three-dimensional fusion operation. By implementing the technical scheme, magnetic resonance imaging reconstruction and segmentation can be quickly and accurately carried out.

The invention relates to a video and map data mapping method based on three-dimensional geographic information, and the method comprises the steps: (1) obtaining the three-dimensional geographic coordinates of a starting point and a target point, respectively including the longitude, latitude and elevation data of each point, picking up the video pixel coordinates and the three-dimensional geographic coordinates of the target point, and constructing a serialized feature point pair; (2) according to the serialized feature point pairs, camera geographic calibration based on the feature point pairs is carried out; and step (3), mapping the three-dimensional geographic coordinates of all points in the geographic space in the video coverage area into video pixel coordinates based on a rotation matrix constructed after camera geographic calibration, or mapping the video pixel coordinates of all points in a camera picture into three-dimensional geographic coordinates.

This invention relates to the fields of laser additive manufacturing and digital twin technology, and discloses a multi-axis laser cladding topography digital twin system. The system includes a process parameter acquisition and equipment status mapping module, a two-dimensional topography prediction module, a real cladding process video module, and a virtual three-dimensional topography real-time update module. The process parameter acquisition and equipment status mapping module is used to acquire and synchronize process parameters, multi-axis motion status, TCP position, TCP feed direction, and laser switch status. The two-dimensional topography prediction module is used to call the laser cladding topography prediction model and output a two-dimensional cladding cross-sectional contour line. The real cladding process video module is used to acquire on-site images or video video information. The virtual three-dimensional topography real-time update module is used to map the two-dimensional cladding cross-sectional contour line to three-dimensional space and incrementally construct a triangular mesh model of the cladding layer. This invention can achieve real-time linkage updates and virtual-real synchronous display of equipment status, cross-sectional contour, and three-dimensional cladding topography without relying on online point cloud measurement of the cladding weld bead.

The invention discloses a method for simulating phosphorus and chromium migration during farmland irrigation with acid mine wastewater, which comprises the following steps: mixing a plant-derived organic material with deionized water to obtain a soluble organic matter; h2O2 oxidizes Fe < 2 + > to prepare pure Schwertmannite, and the pure Schwertmannite is placed in a phosphate solution to obtain phosphorus-loaded Schwertmannite; mixing the phosphorus-loaded Schwertmannite and the soluble organic matter with a chromate solution, carrying out oscillation adsorption, carrying out solid-liquid separation after adsorption, carrying out CrO and POconcentration change test on filtrate, and carrying out mineral characterization on separated solids; a three-dimensional fluorescence spectrum is adopted to track composition conversion of the soluble organic matter in the reaction process; and analyzing the component change of the supernate before and after the reaction by adopting Fourier transform ion cyclotron resonance mass spectrometry. The influence mechanism of DOM on phosphorus and chromium fate in mineral / water interface molecular fractionation is disclosed from the molecular level, and a scientific basis is provided for collaborative migration risk assessment of phosphorus and heavy metal in acid mine wastewater irrigation area farmland.

This application relates to the field of gas sensor packaging technology, specifically to an automated packaging method, system, and packaging device for gas sensors. The method includes: pre-establishing a packaging process parameter-gas-sensitive channel adaptation model; calculating the actual coaxiality deviation and correcting the sealing pressure reference value based on the gas-sensitive channel aperture; starting the integrated packaging unit, applying pre-pressure according to the corrected sealing pressure, and simultaneously collecting the temperature of the sealing area through an infrared temperature measurement module to determine whether dynamic adjustment of the welding temperature is needed; after welding, maintaining the corrected sealing pressure, and dynamically adjusting the pressure holding time based on the gas-sensitive channel length and the creep coefficient of the sealing material to complete the sealing process. This application achieves a precise balance between sealing performance and conduction efficiency by establishing a dynamic adaptation model of process parameters and gas-sensitive channel structure, overcoming the coupling imbalance bottleneck of existing technologies.

The invention provides a face acne skin lesion detection matching method, system and device, and relates to the field of image processing, and the method comprises the steps: calling a face key point detection interface, and obtaining face key point coordinates on face images at different angles; obtaining a first mapping transformation reference point of each face key point corresponding to the side face and the front face; according to the first mapping transformation reference point, generating a perspective transformation matrix of mapping the side face to the front face; according to the perspective transformation matrix and the human face key point coordinates, mapping the skin lesion detection frame on the side face to a position corresponding to the front face; matching the skin lesion detection frame on the front face with the skin lesion detection frame mapped to the front face by the side face; and unifying the skin lesion type labels of the skin lesion with the front face and the side face successfully matched. According to the invention, the accuracy of acne evaluation results can be improved.

The embodiment of the application provides a fracturing implementation deployment optimization method and an electronic device, and relates to the technical field of fracturing reconstruction. The method comprises the following steps: performing spatial division according to a borehole trajectory of a region to be analyzed and preset reconstruction information, and obtaining a plurality of sub-regions to be analyzed; obtaining a first coordinate of a model grid unit based on a three-dimensional reservoir sweet spot distribution model that has been constructed, and mapping the first coordinate to a current borehole local coordinate system by using a preset coordinate conversion algorithm to obtain a second coordinate of the model grid unit; obtaining a sweet spot index set corresponding to a current sub-region to be analyzed by position screening; and outputting fracturing implementation deployment information according to a plurality of sweet spot index sets corresponding to the region to be analyzed. By combining the borehole trajectory and the preset reconstruction information, the fracturing influence range is divided, and the three-dimensional reservoir sweet spot distribution model is mapped to the borehole local coordinate system, so that the analysis and effective identification of the recoverable potential of the far-well region fracturing are realized, and the accuracy of fracturing deployment is improved.

This invention relates to the field of CNC machine tool cutting, and particularly to a cutting force prediction method based on cutting parameter domain adaptive transfer learning. First, a dataset of cutting force signals and cutting parameters for both the source and target domains is constructed. Second, a dimensionless feature space for the target domain is established, the source domain cutting parameters are mapped, and the geometric centroid of the target domain is calculated. Then, combining Mahalanobis distance and entropy regularization distribution alignment algorithms, a transfer weight distribution between the source and target domains is generated based on an anisotropic metric matrix. Furthermore, using a cutting force prediction model and mechanical behavior feature parameters, a robust transfer objective function composed of weighted mean and weighted standard deviation is constructed. Finally, under physical property constraints, Bayesian optimization iteratively searches for the optimal feature parameters and outputs the predicted cutting force. This invention improves the generalization accuracy under varying working conditions, suppresses negative transfer, and achieves interpretability and reliable quantification of the prediction results.

The invention discloses a nanoindentation simulation design-based material indentation depth calibration method, device, equipment and medium, and relates to the technical field of material mechanics characterization, and the method comprises the steps of establishing a continuous gradient material finite element geometric model corresponding to a Brookfield indenter nanoindentation experiment, and constructing a continuous gradient material constitutive model with an elastic modulus continuously changing; combining the two models to perform indentation simulation at a plurality of preset maximum indentation depths to obtain simulation results; calculating an equivalent elastic modulus based on a load displacement curve in a simulation result to determine a material indentation depth corresponding to a preset maximum indentation depth of the indenter; and establishing a quantitative mapping model between the preset maximum indenter indentation depth and the material indentation depth so as to map a test result of the Brookfield indenter nanoindentation experiment at the preset maximum indenter indentation depth to the corresponding material indentation depth according to the quantitative mapping model. And the nanoindentation test result can be accurately mapped to the specific depth position of the continuous gradient material.

The application relates to a processing method and a processing system for reducing the roughness of an inner hole, and the processing method comprises the following steps: S1, establishing a finite element model of contact between a rolling tool and a workpiece, wherein the rolling tool is provided with a roller, and the workpiece is provided with an inner hole; S2, performing a first simulation experiment to simulate the simulation roughness of the hole wall of the inner hole under different combinations of different interference amounts and different chamfer radii of the roller; S3, performing an offline experiment to measure the actual roughness of the hole wall of the inner hole of the workpiece under different combinations of different interference amounts and different chamfer radii of the roller, and the parameters of different interference amounts and different chamfer radii correspond to the same during the first simulation experiment and the offline experiment; S4, optimizing the finite element model based on the simulation roughness and the actual roughness; and S5, performing a second simulation experiment to simulate the simulation roughness of the hole wall of the inner hole under different combinations of different interference amounts and different chamfer radii of the roller.

The invention relates to the technical field of medical image reconstruction, and discloses a bone joint three-dimensional reconstruction method and system based on deep learning. The method comprises the steps that a bone joint tomography image set is input, and multi-scale density slices and edge contour information are analyzed; deducing the two types of information space structures, and establishing an initial space field containing a bone tissue main body frame and a joint lacuna form; separating articular surface structure details and bone surface texture veins from the initial field; generating a network by using the three-dimensional structure which is obtained through separation and input and is trained to obtain a grid body with anatomical topological connection; and performing curved surface iterative smoothing based on biomechanical characteristics on the grid body, and outputting a final bone joint three-dimensional model.

The embodiment of the application discloses a decoding logic derivation method, a failed storage particle positioning method and related equipment, comprising: collecting all first error physical addresses generated by testing a same failed storage particle in a first physical slot to form a first error physical address set; collecting all second error physical addresses generated by testing the same failed storage particle in a second physical slot to form a second error physical address set; searching the first error physical address set and the second error physical address set to find k address bits, or a logical combination thereof, which is always a same value in binary logic values of all the first error physical addresses and is always an opposite value of the same value in binary logic values of all the second error physical addresses; and generating a Boolean function of the k address bits or the logical combination thereof as decoding logic. The application can automatically restore hidden physical address decoding logic and realize automatic, accurate and efficient positioning of the physical position of the failed storage particle.

A multi-objective optimization method for heating section parameters of an electromagnetic induction ethylene cracking furnace belongs to the field of ethylene cracking furnace optimization technology. It includes: determining key structural and electrical parameters of the heating section as optimization variables and setting their value ranges to construct a multi-dimensional design variable space; generating an initial sample set and initializing the particle swarm optimization using Latin hypercube sampling; establishing an electromagnetic field-heat conduction coupled simulation model to calculate the Joule heat distribution and furnace tube temperature field under different parameter combinations; constructing a multi-objective evaluation function based on temperature uniformity, electromagnetic heat transfer efficiency, and coil loss; using a multi-objective particle swarm optimization algorithm combined with non-dominated sorting and external archive mechanisms for iterative search to form a Pareto optimal solution set; and selecting the final heating section design parameter scheme according to engineering requirements. This invention can achieve multi-parameter collaborative optimization, significantly improving heating uniformity and energy utilization efficiency.

This invention relates to the field of materials analysis technology, specifically disclosing a method and system for detecting the content of aroma active substances in grapefruit hydrosol flower tea based on spectroscopy. The method involves constructing a simulated matrix sample library and collecting its first component characteristic spectra and sensory attribute quantification values ​​to establish a baseline prediction model. Then, by collecting the second component characteristic spectra and sensory attribute quantification values ​​of real samples, an enhanced prediction model is obtained through feature distribution adaptation and transfer learning techniques. Finally, volatile component features are extracted from the sample to be tested, and the target component characteristic spectra are input into the enhanced prediction model to directly output the sensory attribute quantification values ​​as the detection result. This invention effectively solves the problem of aroma contribution evaluation distortion caused by matrix-removal analysis in traditional gas chromatography-olfactometry, achieving accurate mapping from chemical components to sensory attributes, and significantly improving detection efficiency while ensuring detection accuracy.

The encoder counting wheel perimeter calibration structure comprises a supporting frame, a bottom plate is installed on one side of the upper portion of the supporting frame, a guide rail A is installed on the upper portion of the bottom plate, a sliding block A is installed on the guide rail A, a clamp fixing seat is installed on the upper portion of the sliding block A, a profile clamping clamp is movably installed in the clamp fixing seat, and the profile clamping clamp is movably installed on the lower portion of the supporting frame. A grating ruler parallel to the guide rail A is installed above the bottom plate and located on one side of the guide rail A. The principle utilized by the invention is basically consistent with that of manual calibration, and the difference is that the grating ruler is used for replacing the whole measurement process, a system program is used for replacing manual calculation and the whole calibration process, the whole measurement process can be fully automatically completed only by pressing a start button by a worker, manual participation is not needed in the process, the requirement on the technical capability of the worker is reduced, and the method is quicker, simpler and more convenient; and the grating ruler is used for surveying and mapping, which is more accurate than manual measurement with a tape measure, and the advancing distance of the material can be truly reflected.

This invention discloses a robot interaction method, device, electronic device, and storage medium. The method includes: detecting first pose parameters of the first facial target in response to a first condition being triggered by a first facial target; detecting first feature information of the first facial target in response to a angular difference between the facial orientation indicated by the first pose parameters and the optical axis of the target robot's camera being less than a preset angular difference, wherein the first feature information is used to indicate facial feature information and gesture feature information; determining the task intent associated with the first gesture feature information from multiple sets of task intents associated with the first gesture feature information based on the first gesture feature information in response to a matching degree greater than a preset matching degree of the first feature information and a third feature information among multiple sets of second feature information; and controlling the target robot to execute a corresponding feedback action based on the task intent associated with the first gesture feature information. This invention can improve the environmental anti-interference capability and intent recognition accuracy of robot interaction.

This invention discloses a multi-channel UAV pose perception system and method. The system includes a pose perception belt, a digital twin UAV attitude visual interface, and a UAV-side pose sensor. The pose perception belt includes a control unit, a wireless communication module, a vibration motor, a power supply module, and a belt frame. The UAV-side pose sensor collects UAV attitude data in real time and establishes an aerial attitude model of the UAV. The attitude data includes at least the angle and direction of UAV tilt. The angle of UAV tilt is defined as the tilt angle, which is the complementary angle γ between the UAV's XY plane and the ground. The direction of UAV tilt is defined as the drift angle, which is the angle α between the projection of gravitational acceleration on the UAV's XY plane and the X-axis. This invention significantly reduces the operator's cognitive load, enables rapid response to abnormal UAV attitudes, greatly shortens the operator's decision-making time, and reduces the risk of UAV loss of control, rollover, or crash.

This application discloses a file annotation method, apparatus, device, and medium based on PDFJS and MIMO, relating to the field of computer technology. The method includes: rendering the original PDF file onto a first canvas layer using the PDF.js library and creating a second canvas layer; monitoring client annotation operations on the second canvas layer to generate corresponding annotation operation data packets, and uploading these data packets to a preset server via a preset network channel based on a preset MIMO transmission strategy, so that the preset server associates and stores the annotation data packets with the unique identifier of the original PDF file; if a loading request for the original PDF file is received, the annotation description file is obtained using the unique identifier, and the annotation data within it is drawn onto the second canvas layer to reconstruct the annotations. This enables precise mapping of annotation coordinates, improves the efficiency of multi-channel real-time collaboration, and enhances the storage and management capabilities of annotation data in a Web environment.

The application discloses a kind of based on query enhancement relation big model's main steam temperature prediction method and system, belong to thermal power plant thermal control and intelligent prediction field.The method utilizes multi-scale feature refining module to construct multi-resolution feature pyramid by frequency domain cycle identification and hierarchical pooling, realize the noise suppression and feature enhancement of noisy industrial time series data;Phase perception double query modeling module adopts time query and relationship query double parallel structure, respectively extracts global cycle priori and variable dynamic physical coupling dependence, and realizes feature adaptive cooperation by phase guide gate fusion;Adaptive prediction module completes main steam temperature multi-step prediction and uncertainty quantification.Through the modeling paradigm of feature refining and relationship discovery decoupling, the problem that traditional method is sensitive to non-stationary disturbance under AGC flexible peak shaving scene, it is difficult to consider prediction accuracy and robustness, provides reliable technical support for safe and economic operation of coal-fired unit.

This invention relates to a method and system for monitoring the operating status of a transformer. The steps include: real-time monitoring and acquisition of key operating data of the transformer; preprocessing the key operating data; extracting key features from the preprocessed key operating data; constructing multivariate time series data; reconstructing the phase space using time delay embedding technology; constructing a chaotic attractor from the time series data; and conducting in-depth analysis of the morphology and dynamic evolution of the chaotic attractor through topological data analysis to identify abnormal states of the transformer. This invention, by introducing chaotic attractors and topological analysis, not only deepens the understanding of the complex behavior of transformers but also enables quantitative analysis of these behaviors to accurately identify abnormal states and provide early warnings before faults occur, thereby ensuring the safety and reliability of transformer operation.

The invention relates to the technical field of internet security, and particularly provides a black box graph fraud detection collusion model editing method based on a conditional diffusion model, which comprises the following steps: S1, constructing a local subgraph context coding mechanism; s2, establishing a condition diffusion generation model of the potential space; s3, designing a joint generation strategy of features and edges; and S4, collaborative optimization based on adversarial loss. Under the combined action of related technical schemes, the problem that in the prior art, a method for cooperatively generating nodes with collusion characteristics and edge attacks based on a conditional diffusion model under the black box and only local view constraint is lacked is solved; according to the method, real collusion attack simulation is realized, local consistency and high concealment are ensured, the problem of segmentation of feature-topology generation is solved, strict black box and local access constraints are met, potential security vulnerabilities in an industrial financial risk control system can be revealed, and a key technical support is provided for developing a next-generation robust defense mechanism.

This invention discloses a multi-scale method for assessing the residual strength of fiber-reinforced flexible pipes under tensile and bending loads, belonging to the field of strength assessment technology for composite material structures in marine engineering. The method includes: extracting fiber distribution characteristics using digital image processing based on scanning electron microscopy images; constructing a two-dimensional Reverse Velocity (RVE) geometric model of the fiber-reinforced structure with hygrothermal degradation using the Monte Carlo method to predict macroscopic elastic parameters; and developing a VUMAT user-defined material subroutine with dynamic damage based on Fortran, embedding damage initiation and evolution failure criteria for the fiber-reinforced structure, and simulating the nonlinear coupled evolution process of multiple damage modes, including fiber fracture, matrix cracking, and interface debonding. This invention constructs a multi-scale analysis framework of "material-damage-response" by coupling microscopic material composition, mesoscopic damage model, and macroscopic pipe structure analysis, solving the problem of the lack of multi-scale damage coupling analysis in traditional methods under complex loads, and improving the accuracy of residual strength assessment of pipes under tensile-bending combined loads.

This invention provides a simulation-based aerodynamic shape design method and apparatus for aircraft, relating to the field of aerodynamic shape design technology. The method includes: acquiring aerodynamic characteristic parameters of different airfoil aircraft to construct a multi-source aerodynamic database; establishing a neural network model based on the database, using airfoil geometric parameters as input, and training it with lift coefficient, drag coefficient, and lift-to-drag ratio as labels to obtain an aerodynamic performance prediction model; generating candidate combinations within the airfoil geometric parameter design space, predicting their aerodynamic characteristics through the model, optimizing the fitness value using dynamic weights, and selecting the combination with the highest fitness as the optimized airfoil parameters using a genetic algorithm; verifying the optimized parameters through simulation, extracting the simulation results and comparing them with the output of the prediction model; determining the optimized combination is effective when the error meets preset requirements, and completing the aerodynamic shape design accordingly. This method improves the accuracy of aerodynamic performance prediction and design efficiency.

The embodiment of the invention provides a holder position prediction method and device for a converter gas holder and a storage medium, and belongs to the field of holder position prediction of converter gas holders. The holder position prediction method comprises the following steps: acquiring historical production data and historical holder position data of a converter gas holder; the correlation degree between the historical production data and the historical cabinet position data is calculated, the historical production data with the correlation degree meeting a preset threshold value is screened out, and the historical production data and the historical cabinet position data are jointly input into a cabinet position prediction model; and on the basis of the cabinet position prediction model, encoding input data into a global context vector with a fixed length, and generating a multi-step cabinet position prediction sequence according to the global context vector. The method solves the problem of low prediction accuracy caused by the influence of working condition change on the converter gas holder in traditional time sequence prediction, effectively improves the prediction precision and efficiency, and is suitable for intelligent scheduling and safety control of a converter gas system.

This invention relates to the fields of medical informatics and data communication technology, specifically a CRRT online acquisition and intelligent monitoring system based on HL7. The system includes: a protocol cleaning and state mapping step: parsing the private protocol binary stream based on a virtual device state machine model to extract the device operating status and monitoring value vectors; a differential semantic analysis step: calculating the rate of change and deviation vector of the monitoring value vector relative to the historical time window; an adaptive message encoding step: selectively generating incremental maintenance messages or full semantic messages based on the comparison results of the rate of change and semantic fluctuation threshold; and a hybrid channel transmission step: dynamically allocating transmission channels and error correction coding strategies according to the message type to execute transmission. This invention solves the transmission contradiction between the real-time nature of high-frequency vital sign data and the redundancy of standardized protocols, balancing standard compatibility and real-time alarm capabilities under limited network conditions.

The invention discloses a dynamic outdoor environment-oriented scene graph semantic navigation method, which comprises the following steps: S1, constructing a multi-level ownership graph which comprises a plurality of types of nodes associated through a hierarchical clustering relationship; s2, receiving a natural language instruction, performing hierarchical semantic retrieval and reasoning on the natural language instruction and the node description of the multi-level avatar, and determining a target node corresponding to the natural language instruction from the multi-level avatar; s3, acquiring a node of the current robot, and performing global path planning according to the target node and the node of the current robot; and S4, acquiring local real-time sensing data, performing local trajectory planning and safety control decision based on the planned global path and the local real-time sensing data, and generating a control instruction. According to the method, semantic navigation guided by natural language instructions can be realized in a large-scale dynamic outdoor environment.

The application discloses a natural language and machine vision alignment method, which proposes a three-level alignment architecture, adopts a double-flow feature extraction network to extract local-global features of a visual scene and syntax-semantic features of natural language respectively, adopts a cross-modal alignment module with time-space attention enhancement to complete adaptive projection in a feature space by using a dynamic gating mechanism, constructs a joint optimization strategy based on contrast learning, optimizes the consistency of visual and language embedding spaces by using a multi-granularity contrast loss function, simultaneously introduces semantic topology constraints and visual causal reasoning to reduce the computational complexity and improve the task robustness, and achieves a Top-1 accuracy of 92.3% in image-text retrieval and a visual question answering F1 value of 83.4% through experimental test data, and the model parameter quantity is reduced by 40%, so that the method can be widely applied to intelligent interaction systems, automatic driving scene understanding, industrial quality inspection knowledge base construction and other fields, and significantly improves the semantic perception and reasoning capability of a multi-modal system.

The invention relates to the technical field of industrial automation communication protocol conversion, and discloses an AUTBUS-MVB protocol conversion device and method. The device comprises a bus protocol conversion module, an MVB communication module and an AUTBUS communication module, precise conversion of a protocol address is realized through an address mapping unit, a data structure conversion unit completes recombination of a data frame format, a communication time sequence coordination module adopts a soft clock scheduling mechanism to ensure the correctness of a data transmission time sequence, and the communication time sequence coordination module is used for realizing data transmission. And the buffering and flow control module effectively manages the data flow through a queue mechanism to prevent congestion. By means of the method, efficient and reliable data conversion between the AUTBUS and the MVB is achieved, and the requirement for interconnection of heterogeneous buses is met.