166 results about "Visual modeling" patented technology

The invention relates to the field of digital twinborn modeling, and discloses a digital twinborn visual modeling method and system based on a neural network, and the method comprises the steps: collecting the multi-dimensional perception data of a target physical system, carrying out the format unification and normalization processing of the original data of a sensor through a heterogeneous data fusion module, and obtaining a data fusion module; constructing a high-dimensional input feature set for neural network modeling by combining a structured embedding algorithm; carrying out stability pre-evaluation on the constructed input feature set, and screening core features by adopting a disturbance sensitivity analysis mechanism; a dynamic residual feedback mechanism is introduced to carry out enhanced training on the preliminary twin model, and modeling is carried out on the space-time dependency relationship of different components through a graph neural network; tracking a stability index of visual representation in real time in a model training process; and according to a multi-dimensional visualization result output by the final twin model, performing interpretation in combination with an industrial scene semantic rule base. The method has the advantage of improving the practicability of the twin model in the industrial scene.

The invention relates to the technical field of building information modeling, in particular to a building drawing geometric feature extraction and visual modeling method and system, and the method comprises the steps: carrying out the self-adaptive noise reduction, contrast enhancement and line refinement processing of an original building drawing image, and carrying out the automatic layer separation based on colors and line types; linear geometric features and specific symbol geometric features in the drawing image are extracted, and a geometric feature set is constructed; component instantiation, attribute assignment and topological relation reasoning are carried out by using a predefined building component semantic rule base, and a building component semantic network is generated; and mapping the semantic network to a parameterized three-dimensional modeling engine, calling an IFC standard three-dimensional template, performing parameter driving and automatic assembly, generating a three-dimensional building model with semantic information and a spatial structure, and performing visual output. According to the method, efficient and standardized conversion from a two-dimensional building drawing to a three-dimensional building model can be realized, and the method has the remarkable advantages of processing complex drawings and high-precision modeling.

The invention provides a pavement crack detection method and apparatus, and an electronic device. The method comprises the steps of obtaining a crack image and a crack prediction model obtained by pre-training; wherein the crack prediction model comprises a visual modeling model, an inference model and a dynamic multi-modal fusion network; performing hidden space global visual modeling on the crack image based on a visual modeling model to obtain hidden space global visual features; generating a semantic mask matrix guided by global scene semantics for the crack image based on an inference model; and inputting the hidden space global visual features and the semantic mask matrix into a dynamic multi-modal fusion network, and predicting to obtain crack information. According to the invention, pixel-level prediction of the crack can be carried out, accurate detection of the pavement crack is realized, and technical support is provided for pavement maintenance.

The invention relates to the technical field of digital twinning, in particular to a storage space utilization rate optimization method and system based on digital twinning, and the method comprises the steps: determining three-dimensional visual modeling input data of a storage digital twinning body according to an obtained environment data set of a storage space and an operation state data set of storage equipment; performing feature extraction processing on the three-dimensional visual modeling input data to generate a storage feature set, and generating a three-dimensional visual model of the storage digital twin based on the storage feature set; calling a spatial layout simulation analysis algorithm, performing joint simulation processing on shelf distribution characteristics, equipment moving path characteristics and goods access frequency characteristics in the three-dimensional visual model, and generating a spatial layout simulation result set; and generating a warehousing operation adjustment strategy set according to the path conflict simulation result and the space idle simulation result in the space layout simulation result set, and indicating a warehousing control system to perform space layout optimization processing based on the warehousing operation adjustment strategy set.

A method and system for providing enhanced holographic communication is disclosed. Visual modeling data and verbal communication data of a conference participant in a current time frame are obtained as a current sample. The current sample is encoded into a first vector comprising a plurality of states for the current sample as an encoded result. At least one of the plurality of states is updated by inputting the encoded result to a generative artificial intelligent model as a prompt, and the updated plurality of states are obtained as a predicted result. The visual modeling data is then updated based on the predicted result for rendering a three-dimensional (3D) representation of the conference participant in the current time frame or in one or more future time frames.

The invention discloses a road slope three-dimensional visualization modeling method and device, a medium and equipment, and relates to the technical field of three-dimensional visualization. Comprising the following steps: collecting point cloud data of a road slope, and obtaining a feature vector of each point based on the point cloud data; dividing each point into a plurality of different classes based on the similarity of the feature vectors, wherein each class comprises a plurality of sub-clusters dispersed in geographic space positions; obtaining a confusion feature value used for representing the confusion degree of the point cloud data in each sub-cluster and the number of sub-clusters belonging to other categories in the neighborhood of each sub-cluster; setting the number of triangular meshes in direct proportion to the disordered feature value and the number of the sub-clusters belonging to other categories for each sub-cluster; and on the basis of the set number of the triangular meshes, using a triangulation method to connect the midpoints of the sub-clusters into non-overlapping triangular meshes, and obtaining a road slope three-dimensional model.

The invention discloses a small sample industrial defect image segmentation method and system based on text background perception enhancement, and a storage medium. The method comprises the following steps: constructing a corresponding support-query pair according to an industrial defect image set; establishing a text background perception enhancement model; utilizing all support-query to train a text background perception enhancement model; and inputting a query image to be segmented, the corresponding support image and the mask label into the trained text background perception enhancement model, and obtaining an output result of the few-sample segmentation model as a segmentation prediction result of the corresponding query image. Through fusion of a multi-modal language-visual modeling mechanism and a joint activation graph optimization strategy, the precision and efficiency of defect detection are greatly improved, small-sample and low-cost detection is realized, and the generalization ability is high.

The invention relates to the technical field of explosion-proof performance detection, and discloses an explosion-proof performance evaluation method and system for explosion-proof equipment. The method comprises the steps that a geometric model of the explosion-proof equipment is established, stress distribution of the surface of a shell in the explosion-proof equipment test process is obtained through a finite element analysis method, a finite element reduced-order model and a stress distribution agent model are constructed based on finite element analysis results, and the two models are fused to construct an optimization model. And inputting a data-level fusion result of the multi-source heterogeneous data into the optimization model, and predicting the stress distribution condition of the explosion-proof equipment shell. And inputting the measured data and the calculated data into the multi-modal fusion evaluation model to obtain the safety level of the explosion-proof equipment. And finally, realizing visual display of the explosion-proof equipment performance detection test in the digital twin system by adopting a three-dimensional visual modeling method. According to the invention, the comprehensiveness and reliability of the performance evaluation of the explosion-proof equipment are improved.

The invention belongs to the technical field of weld pipelines, and particularly relates to a weld three-dimensional visual modeling method based on big data analysis. Comprising the following steps: step 1, building a pipeline plane; step 2, carrying out 3DMAX data modeling; 3, UNITY3D manufacturing is carried out; step 4, determining to publish WEBGL; and 5, carrying out three-dimensional visual analysis. The method has the advantages that data display is flexible, the Linear Regression algorithm and the PageRank algorithm are combined for extraction, display and analysis, all the three-dimensional models can serve as carriers of big data analysis, and data circulation, display and analysis are conducted by achieving big data analysis in the three-dimensional models; 2) the expansibility of the three-dimensional model is realized, and the design mode is beneficial to the expansion of the platform model; and for newly added welding seams in the later-period service inspection process, valve management and the like which are newly added according to other requirements can be integrated in a plug-pull mode on the basis of an original model, and the subsequent development cost is reduced.

The invention relates to the technical field of geographic models, in particular to a road engineering visual modeling method and system based on the BIM technology, and the method comprises the steps: obtaining a complete road surface range based on the splicing result of depth images obtained through multiple times of measurement; and then combining the construction state and terrain complexity of different areas in the pavement range to obtain the degree of demand of the different areas for modeling precision, thereby adjusting the model precision of the different areas, realizing dynamic matching of the road model and the construction progress, effectively retaining detailed information and improving the modeling precision.

The invention provides a method and a system for reconstructing a high-precision complete shape and texture of an object in a scene. The method comprises the following steps: acquiring a visual three-dimensional grid G, optimizing the visual three-dimensional grid G, performing visual modeling of a three-dimensional scene space, and acquiring a three-dimensional grid optimization visual model; through decomposition type nerve implicit reconstruction of the generation diffusion model prior, the potential generation diffusion model prior is used for filling object missing information of an object invisible area or an occluded area, and combined scene reconstruction is carried out; optimizing a visibility model through a three-dimensional grid, dynamically adjusting the prior loss weight of a potential generation diffusion model, forming a generation prior consistent with the input in a visible region, and performing object shape enhancement; and after the object shape enhancement is completed, three-dimensional grid representation is exported from the implicit field, object texture enhancement is carried out, and a high-precision complete object 3D model with complete texture of each object is precisely reconstructed.

The invention provides a crane full-state monitoring method based on digital twinning, and relates to the technical field of digital twinning, and the crane full-state monitoring method comprises the following steps: firstly, establishing a crane geometric model, obtaining a finite element analysis result of a crane by adopting finite element analysis, arranging stress sensors based on the finite element analysis result, and constructing a load identification neural network model; and constructing a structural stress prediction neural network model and a structural deformation prediction neural network model based on a finite element analysis result. Actual measurement data of the structural stress are acquired and analyzed by adopting a sensing and communication technology, and the actual measurement data are input into the load identification neural network model to obtain the hoisting load and the hoisting position of the crane. And inputting the hoisting load and the hoisting position of the crane into the structural stress prediction neural network model and the structural deformation prediction neural network model, and predicting the stress and the deformation of the whole structure of the crane. And finally, realizing real-time visual display of full-state detection of the crane in a digital twin system by adopting a three-dimensional visual modeling method.

The invention relates to the technical field of visual lane modeling, and discloses a business data processing method and system based on visual lane modeling, and a multi-task prediction model based on multi-source historical business chain data training graph neural network and Transform fusion. A plurality of groups of lane layout and event configuration schemes are generated in combination with user real-time operation captured by a design interface, an optimal scheme is screened through simulation evaluation and then is visually displayed, finally, visual lane modeling is executed according to user feedback, and through automatic data processing, high-precision model prediction, real-time interaction optimization and visual modeling, the optimal lane layout and event configuration scheme is obtained. According to the method, the service chain design efficiency and quality are improved, meanwhile, artificial experience deviation is avoided through model prediction based on historical data, the comprehensive requirements of complex equipment development for real-time performance, reliability and resource efficiency are met, and efficient technical support is provided for landing of model-based system engineering in the field of complex equipment.

A method and system for providing enhanced holographic communication is disclosed. Visual modeling data and verbal communication data of a conference participant in a current time frame are obtained as a current sample. The current sample is encoded into a first vector comprising a plurality of states for the current sample as an encoded result. At least one of the plurality of states is updated by inputting the encoded result to a generative artificial intelligent model as a prompt, and the updated plurality of states are obtained as a predicted result. The visual modeling data is then updated based on the predicted result for rendering a three-dimensional (3D) representation of the conference participant in the current time frame or in one or more future time frames.

The invention discloses a design and simulation integration method based on SysML (System Markup Language) and Modelica. According to the method, the existing Modelica is changed into a calculation component of SysML, and complex verification calculation can be carried out in a design stage by virtue of the strong calculation simulation capability of the Modelica model. An existing Modelica model is directly converted into a Block object of the SysML for modeling, and mixed modeling of the SysML and Modelica is achieved. The method does not need to use a Modelica modeling tool to modify a model after the Modelica simulation model is generated in the SysML, and achieves the integration of design and simulation in the aspect of visual modeling. A SysML model is converted into a Modelica model, so that consistent transmission from design to simulation knowledge is realized.

The invention relates to the technical field of network geographic information systems, and discloses a visual modeling method, system and device for a spatial analysis process and a medium. The method comprises the following steps: constructing a visual component library; in response to a canvas interaction instruction input by a user, performing parameter configuration and component connection based on the visual component library to obtain workflow logic of the canvas; analyzing the workflow logic in real time based on a directed acyclic graph to generate a spatial analysis code and obtain an analysis result of the spatial analysis code; and performing result visualization and export on the analysis result based on the visual component library. According to the method, component dragging, parameter configuration and connection mechanisms suitable for WebGIS spatial analysis are defined, and visual workflow construction is achieved. Based on a directed acyclic graph process analysis algorithm, efficient and executable spatial analysis codes are automatically generated, and dynamic optimization and parallel computing are supported, so that visual modeling and automatic execution of a spatial analysis process are realized.

The invention discloses a Java enterprise-level rapid development method based on visual modeling. The method comprises the steps that modeling behaviors are collected to generate a cognitive map, a view is constructed, and operation behaviors are collected to generate cognitive feature data; generating a semantic constraint model, and fusing the cognitive features and the node features to construct the semantic constraint model; semantic consistency detection is executed, design and implementation differences are automatically compared, and bidirectional correction is triggered; generating a project engineering structure, and generating a structured code and an interface document according to the correction model; zero-shutdown migration evolution is executed, a migration relation graph is constructed, and seamless switching is carried out in a gray level mode; and performing semantic self-correction updating in the operation period, monitoring semantic offset and backfilling design content for closed-loop synchronization. According to the method, intelligent modeling and uninterrupted evolution of Java enterprise-level applications are realized through cognitive map driving and a multi-mode migration mechanism.

The invention provides an intelligent detection and visual representation system for solid engine grain defects. The system comprises a two-dimensional slice data preprocessing module, a three-dimensional visual modeling module and a model post-processing and analysis module. According to the system, by fusing a multi-modal image processing algorithm and a three-dimensional modeling technology, sub-voxel-level three-dimensional reconstruction and spatial quantitative analysis of defects such as air holes and cracks are realized, and coordinate distribution, geometric dimensions and quantity statistics of the defects in a grain three-dimensional space can be accurately positioned; the technical bottleneck of a traditional two-dimensional detection method in the aspects of defect deep analysis and multi-parameter coupling analysis can be solved. All the core modules cooperate to improve the accuracy and efficiency of detecting the defects of the air holes in the solid engine, accurately detect the spatial positions and shapes of the air holes in the grain, and ensure the integrity and safety of the SRM grain structure.

The invention provides a visual modeling method for a ship pipe network program based on a YOLOv8 target detection technology, and the method comprises the following steps: S1, constructing a human-computer interaction visual interface of a ship pipe network system in the form of an SVG base map and a control position map through employing a WPF interface generation technology; s2, identifying the pipe network elements in the human-computer interaction visual interface by using a YOLOv8 target detection technology, and obtaining an identification result; s3, using a Python optimization algorithm to carry out classification arrangement and model recombination on identification results, generating an architecture model containing pipe network elements and control spatial positions and attribute parameters by a system, and storing the architecture model in a standard CSV file form; and S4, converting the architecture model stored in the CSV file into a mathematical model by using a C # programming language, performing real-time calculation, and outputting a calculation result to a human-computer interaction visual interface. According to the invention, the integrated operation of the ship pipe network system from design to simulation is realized, the design efficiency is obviously improved, and the operation is more convenient.

The invention provides a three-dimensional ventilation digital twinning system, which comprises a ventilation information investigation module, a three-dimensional visual modeling module, a ventilation system analysis module and a ventilation system optimization module, and is characterized in that the ventilation information investigation module collects underground ventilation system engineering, production operation, ventilation structures and ventilation equipment materials, combines mining area ventilation lines, and optimizes the ventilation system engineering, the production operation, the ventilation structures and the ventilation equipment materials; temperature, humidity, air volume and wind direction information parameter detection is carried out on main nodes of an underground ventilation system; the three-dimensional visual modeling module is used for establishing a three-dimensional visual model of the whole mine ventilation system according to 1: 1 in combination with ventilation information basic data and related materials; the ventilation system analysis module diagnoses and analyzes air volume distribution, air speed standard reaching, ventilation resistance distribution and a diesel oil equipment tail gas diffusion path in a multi-dimensional mode based on a ventilation numerical value analysis model; the change condition of the mine ventilation system can be scientifically and reasonably predicted, and the mine ventilation cost and working conditions can be quantitatively analyzed.

The invention relates to the technical field of construction methods, and discloses a construction method of a visual modeling job flow scheduling engine, which comprises the following steps: S1, defining a job flow model: defining the job flow model including job nodes, connecting lines and job attributes, the job nodes representing each link in the job flow, the connecting lines representing each link in the job flow, and the job attributes representing each link in the job flow; the connecting line represents a logical relationship between the operation nodes; and S2, constructing a visual modeling interface: constructing the visual modeling interface according to the workflow model, and providing dragging and connecting functions, so that a user can conveniently construct the workflow. Through an intelligent scheduling algorithm, dynamic adjustment can be carried out according to real-time resource conditions and job flow characteristics, and the execution efficiency and the success rate of the job flow are improved; through reasonable resource allocation and monitoring, resources can be fully utilized, and resource consumption and waste are reduced; through the visual modeling interface, the user can conveniently construct and manage the workflow, and the user experience and satisfaction degree are improved.

The invention provides a roadway geology visual modeling method and system under a joint method, and the method comprises the steps: constructing a stratum curved surface model through employing a Kriging interpolation algorithm and an inverse distance weighting method, and employing a TIN-based surface model modeling method; acquiring intersecting lines of the fault and the stratum when each stratum is cut by the same fault so as to determine a control point set of the fault plane, and constructing a three-dimensional geologic model of the fault plane; taking a contour line of a local coordinate system established on each control point along the center line as a section, and carrying out tunneling roadway geometric modeling by using a section expansion modeling method; and performing dynamic prediction and model updating based on the static data of the modeling area and the dynamic data collected in the tunneling process to realize model visualization. According to the method, the form and internal attributes of the geologic body can be taken into consideration, hidden information and feature representation of data can be mined while sample data is learned by means of deep learning, and geological information can be learned and progressively predicted more accurately.

The invention provides a mineralization domain spatial distribution prediction method and system based on geological priori knowledge, and relates to the technical field of mineral exploration, and the method comprises the steps: obtaining drilling core test analysis data and magnetic measurement data of a target mining area; processing the geochemical data to obtain an element concentration data set, and performing potential field conversion on the magnetic measurement data to generate a magnetization direction data set; identifying geochemical anomaly information from the concentration data set by using a fractal algorithm, determining an anomaly range, fusing the anomaly range and the magnetization direction data set, performing three-dimensional visual modeling, and constructing a three-dimensional geologic model; and finally, extracting feature data in the three-dimensional geologic model, and inputting the feature data into a machine learning prediction model for processing to obtain a distribution diagram representing the existence probability of the mineralization domain in the mining area space. According to the invention, the accuracy of blind mineralization domain spatial position prediction is improved.

The invention discloses a method for automatically processing a business process embedded with a man-machine interaction node, and relates to the technical field of business process processing. Modeling is carried out according to BPMN2.0, node logic and data formats are defined, visual modeling is carried out through a tool, and version control is carried out; identifying a manual intervention scene, embedding an interaction node, configuring a multi-trigger condition, and adapting to multiple terminals and an interaction template; deploying a process engine, configuring parameters and mapping a system interface; the task is pushed when the interaction node is triggered, and the engine drives the process after user operation; abnormal and operation logs are recorded, stored and analyzed; and generating an execution report, regularly analyzing the bottleneck, and optimizing the process and parameters. According to the method, the man-machine interaction node is flexibly embedded, and the process execution flexibility and stability are improved; priority and response time efficiency are optimized, and risk management and control are enhanced; authority is refined, data are integrated, the operation and maintenance and iteration efficiency is improved, and the multi-service scene requirement is met.

The invention discloses a SysML-based satellite constellation architecture modeling method and system and a storage medium, and the method comprises the steps: analyzing a satellite constellation system strategy scene and a target described by a natural language, and building a satellite constellation architecture system layer model by using a SysML language; based on a system capability demand model in the constructed system layer model, building the system layer model by combining an RFLP (Restriction Fragment Length Polymorphism) method and a SysML (Systematic Modeling Language); analyzing designed functions in the constructed system layer model through a system forward design method, and respectively establishing a satellite platform model and a satellite load model by using an RFLP (Restriction Fragment Length Polymorphism) method and an SysML (SysML) modeling language; and extracting parameters from the constructed satellite parameter model, platform parameter model and load parameter model to carry out orbit design, and establishing a satellite orbit model by using an SysML language. According to the method, comprehensive and visual modeling of the satellite constellation from a macroscopic system to a microcosmic component is realized, the standardization, consistency and understandability of the model are greatly improved, and the modeling efficiency is improved.

The invention provides a salt lake resource dynamic monitoring system based on a Kriging interpolation method. Comprising a drilling deployment module, a resource reserve initial exploration module, a multi-source data acquisition and preprocessing module, a spatial interpolation algorithm module and a three-dimensional visual modeling and rendering module. According to the method, the Kriging interpolation method and the Co-Kriging interpolation method are combined, the main and auxiliary variable spatial correlation is utilized to improve the reserve estimation accuracy, the limitation of dependence on a large number of samples traditionally is broken through, center encryption and peripheral control drill hole arrangement is combined with uncertainty evaluation to optimize the exploration cost, comprehensive evaluation is supported by a small number of samples, the model is dynamically updated by the system monthly, and the exploration efficiency is improved. The problem of traditional data lag is solved, the resource dynamic state is visually presented through the three-dimensional visual modeling and rendering module, a basis is provided for decision making, the resource utilization rate is improved, and premature exhaustion is avoided.

The present application relates to the technical field of three-dimensional geological visualization modeling, and discloses a mine geological structure intelligent analysis method and system based on three-dimensional visualization modeling, which comprises the following steps: acquiring continuous drilling process parameters along a drill hole, establishing a parameter fingerprint library to identify the causes of parameter changes, identifying effective physical beacon points capable of representing real geological discontinuity, and then generating a geological reality guide field in three-dimensional space using the beacon points as a source, and imposing constraints on the weight across potential geological boundaries when performing spatial interpolation. The present application converts long-neglected drilling process data into effective geometric constraints for the three-dimensional modeling kernel, changes the model construction from pure mathematical filling to a form closer to the engineering reality guided by the physical process, and ensures the reliability of the constraint source through an internal anti-fake mechanism, thereby improving the structural reality of the final geological model.

The invention discloses a visual software modeling method for a computer software view, which relates to the technical field of computer software and comprises the following steps of preparation before modeling, selection of a visual modeling tool according to software requirements, introduction of a code generation modeling tool, modular modeling, subdivision of a software model into various functional modules and complexity evaluation. The method comprises the following steps of: dividing a software model into functional modules, dynamically adjusting the module dependency, evaluating the overall dependency of the functional modules through an overall evaluation algorithm, and verifying the model, thereby improving the evaluation accuracy, optimizing the modular design, reducing the system complexity and improving the maintainability by subdividing the software model into the functional modules and utilizing a complexity evaluation algorithm and an influence coefficient; through the dependency algorithm, the dependency relationship between the functional modules is quantified, the interaction weight is adjusted, the coupling degree is reduced, the performance bottleneck is avoided, the resource utilization efficiency is optimized, the dependency algorithm is adjusted in real time, the excessive coupling is reduced, the system maintenance cost is reduced, and the modeling efficiency is improved.

The invention discloses a big data visualization modeling method, device and equipment based on machine learning, and relates to the technical field of big data modeling, the method comprises the following steps: accessing an external data source to an initialized multi-source data directory, and registering external data in the multi-source data directory to a public data directory; training the established initial machine learning model by using the data in the registered public data directory to obtain a target machine learning model; constructing a visual big data model based on the data in the registered public data directory, a data processing tool operator and the target machine learning model; and performing preview debugging on the visual big data model to determine operator parameters of the visual big data model. According to the method, the operator parameters of the model are determined by previewing and debugging the visual big data model, the model prediction result can be previewed, and data from different sources and formats can be processed by supporting access of a multi-source data directory.

The application relates to the technical field of visual lane modeling, and discloses a business data processing method and system based on visual lane modeling, wherein a multi-task prediction model of a graph neural network and a Transformer fusion is trained based on multi-source historical business chain data, a plurality of groups of lane layout and event configuration schemes are generated in combination with real-time operations of a user captured by a design interface, the optimal scheme is selected through simulation evaluation and filtering, and visual display is performed, and finally, visual lane modeling is executed according to user feedback, through automatic data processing, high-precision model prediction, real-time interactive optimization and visual modeling, the design efficiency and quality of a business chain are improved, meanwhile, model prediction based on historical data avoids artificial experience deviation, meets the comprehensive requirements of real-time performance, reliability and resource efficiency for complex equipment development, and provides efficient technical support for the landing of model-based system engineering in the field of complex equipment.