65 results about "Component modeling" patented technology

The invention relates to the technical field of three-dimensional modeling in engineering surveying, in particular to a point cloud building component modeling method and system based on feature extraction. Three-dimensional point cloud data of building components are obtained, a multi-scale local neighborhood calculation covariance matrix is constructed with each point as the center, eigenvalues are decomposed, an edge probability graph is generated, corresponding component categories are semantically output, and corresponding key feature point sets are screened; taking the feature point cloud as a control point, constructing a three-level B-spline surface model, and adjusting the corresponding spatial distribution density; a weighted complete graph is formed through a key feature point set, a non-planar area is identified and processed through a Kurtowski theorem, a QEM algorithm is applied to carry out lightweight processing on a three-dimensional model, screening and optimization are carried out through automatically extracting key feature points of building components, and a concise and accurate lightweight model is constructed based on feature point topological optimization and a graph theory algorithm. The automation degree and efficiency of modeling are improved, and the contradiction between model lightweight and precision is effectively solved.

The invention provides a software supply chain risk analysis method. A data acquisition and preprocessing module acquires component information from a plurality of software warehouses and performs format unified processing; the components are modeled as nodes through a hypergraph construction module, the dependency relationship is modeled as hyperedges, and a hypergraph structure is dynamically constructed and updated so as to express many-to-many dependency relationship more accurately; performing representation learning on the hypergraph structure through a hypergraph neural network, generating embedded vectors of the components, and fusing context features of the components; based on an embedded vector, risk scoring, anomaly detection and classification are carried out by adopting multi-task learning and a graph attention mechanism, so that the generalization ability of the model and the risk identification precision are improved; online incremental updating of a hypergraph structure and model parameters is achieved through a dynamic updating and feedback mechanism, and the real-time performance and stability of the model are ensured. According to the method, the data transmission security, the transmission efficiency and the compatibility between devices are improved, and the method has higher risk analysis capability and system adaptability.

The invention relates to a visual component management method and system based on support of multi-user collaboration, and belongs to the technical field of computer software collaborative design. Wherein multi-party editing requests are received and verified through a cooperative access mechanism, structured component data are constructed by using a component modeling model, concurrent control and a difference buffer are adopted to coordinate parallel modification, write conflicts are identified and processed based on a conflict detection algorithm, and traceable management of component versions is realized through a snapshot generation model. According to the method, efficient, consistent and conflict-controllable unified management of the visual components in a multi-person online cooperation scene is realized, and the cooperation efficiency of component development and the system reliability are effectively improved.

The invention belongs to the technical field of building management, and discloses a BIM-based building engineering reverse construction disassembly distribution system and method, and the system comprises a building component modeling module which is used for collecting building site multi-modal sensing data, and generating a reverse BIM model of a building component; converting a structural process experienced by each building component in the reverse BIM model into a life path vector, and generating a building component attribute set according to the life path vector; the dynamic disassembly planning module is used for receiving the building component attribute set, constructing a dynamic constraint disassembly tree by combining structural mechanical simulation analysis, and generating a feasible disassembly path set meeting building structure safety constraints based on a greedy strategy and a Monte Carlo tree search algorithm; the safety, automation and controllability of the reverse dismantling process are improved, manpower dependence is reduced, and mistaken dismantling and resource waste are reduced.

The invention relates to the technical field of prefabricated part modeling, in particular to an interaction system for prefabricated part steel bar parameter driving design and a modularization implementation method. Incrementally updating the engine; the model application module is used for acting the change patch sequence on the three-dimensional reinforcement model in a transaction mode and driving display refreshing; the system further comprises a rule base module and an interpretable verification module. The rule base module stores a steel bar arrangement rule and / or a standard verification rule in a constraint declaration form; the interpretable verification module is used for performing compliance verification on the three-dimensional reinforcement model or the derived quantity thereof based on the evidence data field, and outputting a violation item list; the interactive interface comprises parameter panels and a violation interactive area, and the parameter panels are displayed in groups according to component type parameters, geometric parameters, steel bar parameters and specification options and support interactive modification. According to the method, the script dependency is reduced, the dependency graph increment patch is updated in real time, the automatic specification matching and positioning are realized, and the low-cost expansion is governed by the plug-in.

The invention belongs to the technical field of data processing, and discloses an active intelligent operation and maintenance monitoring method for a data center, which comprises the following steps: step 1, component modeling and topology configuration; 2, carrying out distributed health detection and data acquisition; 3, performing real-time health assessment and anomaly detection; 4, performing intelligent alarm and root cause analysis; 5, unified operation and maintenance and closed-loop control are carried out; and step 6, dynamically optimizing the intelligent operation and maintenance strategy. According to the method, a monitoring object and a dependency relationship are clarified through component modeling and topological configuration, and specific scenes, such as multi-mode acquisition, active detection, index pulling, log analysis, coverage message queue theme accumulation and database connection pool exhaustion, of distributed health detection are combined. The quantitative health score is calculated based on the preset scoring model, and by combining with the dynamic baseline learned by the ARIMA or LSTM algorithm, the module abnormity can be actively detected in different periods and weekly updating, and the problems of fault discovery lagging and incomplete monitoring coverage are solved.

A radar confrontation equipment modeling method based on a reconfigurable component technology adopts a modularization modeling mode to construct a radar confrontation equipment model framework required by an electronic confrontation simulation deduction system, and the main design idea is that modularization modeling is carried out on an equipment simulation model, reusable components are not repeatedly modeled any more, the development efficiency is improved, and the modeling cost is reduced. The model stability is improved. Based on the modularization modeling idea, splitting of common model components and fusion with an existing model are fully considered in the model design process, a complex equipment function model is split into independent function components, the modeling complexity of each component is reduced, the function components can be repeatedly used, the modeling workload is reduced, and meanwhile the modeling efficiency is improved. And the stability of the equipment model can be effectively improved.

The invention discloses an intelligent modeling and checking calculation method and system for a bridge component based on Dynamo, and belongs to the field of bridge engineering information modeling and structural performance visualization analysis, and the method comprises the steps: presetting a component family sketch and a parameter control rule in Revit; a three-dimensional modeling process based on geometric lofting is constructed in the Dynamo; bidirectional synchronization between parameters and geometry is realized by using a Python script; calling a bridge member standard database to carry out model configuration comparison and replacement; structuring the nested family parameters and outputting XML format information; docking a structure analysis platform through a model-checking calculation interface and automatically establishing a finite element model; executing multi-working-condition checking calculation, and returning a structural performance index; a visualization result is embedded in the Dynamo in a thermodynamic diagram mode; closed-loop feedback and real-time updating of structural design and checking calculation are achieved, and a full-process parameter-driven bridge component modeling and performance analysis integrated system is constructed. The method has the beneficial effects that the deep linkage between the BIM modeling platform Revit and the parameterized modeling platform Dynamo is realized.

The invention relates to an assembly type bridge modeling method based on a large model and an RAG technology. The method comprises the steps that a bridge standard component library is established based on an assembly type bridge standard image set; calling a large language model, and generating standardized knowledge statements based on the bridge standard component library; a word embedding method is adopted to convert the normalized knowledge statement into vectors, and the vectors are stored in a vector database; converting an input natural statement query into a vector by adopting a word embedding method, and retrieving in a vector database to obtain a normalized knowledge statement related to the query; performing parameter analysis and optimization on the retrieved knowledge statements based on a large language model by utilizing an RAG technology so as to generate component parameters; and calling a component modeling algorithm based on each component parameter to generate a component three-dimensional model, and assembling the component three-dimensional model to obtain a fabricated bridge model. According to the method, component parameter sorting, knowledge statement intelligent combination, efficient semantic retrieval, parameter optimization, three-dimensional model automatic generation and the like are organically integrated, and the modeling efficiency and quality are improved.

The invention discloses a software radio unified modeling method and system, and belongs to the field of software radio, and the method comprises the steps: determining modeling objects as platform modeling and waveform modeling; wherein during platform modeling, abstract modeling is performed on each calculation unit, and during waveform modeling, waveform component modeling and waveform application modeling are included; in the waveform component modeling, at least one modeled waveform component runs on a calculation unit, and a plurality of waveform components can be deployed on the calculation unit at the same time; the waveform application modeling comprises the following steps: establishing a connection relation between waveform components, and assembling into waveform application; then executing a modeling process of creating a platform model, creating a waveform model and establishing a platform and waveform connection relationship, and performing modeling detection; establishing a basic model set after modeling detection; the basic model set comprises a platform model subset and a waveform model subset. The modeling efficiency and the standardization degree are improved.

The embodiment of the invention discloses a cigarette packaging machine component modeling method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a label paper die-cut drawing corresponding to a cigarette packaging machine component of a target specification, and extracting a target die-cut drawing parameter associated with a special modeling parameter of the cigarette packaging machine component of the target specification from the label paper die-cut drawing, the special modeling parameter is any modeling parameter when modeling is carried out on each special part of the cigarette packaging machine component of the target specification; obtaining a function of a predetermined special modeling parameter about the target die-cut drawing parameter to obtain a first target function, and determining the special modeling parameter based on the target die-cut drawing parameter and the first target function; and based on the special modeling parameters, modeling is carried out on the cigarette packaging machine component of the target specification. According to the embodiment of the invention, the design efficiency of designing different specifications of cigarette packaging machine parts can be improved.

The invention relates to a model verification method suitable for RUCM4CPS, and belongs to the field of embedded system modeling. Comprising the following steps: extracting model components and attribute information of each component according to a model description file of RUCM4CPS to obtain a component attribute information mapping table; determining constraint conditions according to modeling requirements of the complex embedded system, and obtaining RUCM4CPS model verification rules based on the constraint conditions and attribute information of the components; according to the component modeling sequence, verifying all the components in sequence by using a verification rule; when each component is verified, a verification item corresponding to the component is obtained, attribute information corresponding to the component is obtained from the component attribute information mapping table, whether the attribute information meets the verification item or not is judged, and if the attribute information does not meet the verification item, a prompt is given. According to the method, the attribute of each component is verified according to the modeling sequence of the complex embedded system, and the problems that the current model verification is incomplete, the orderliness is poor, and the verification result lacks logicality are solved.

The present invention relates to a method and device for modeling a vehicle component. To this end, a group (111) of first vehicles and a group (112) of second vehicles are selected. Representative first data of first speed profiles are obtained from the first vehicles of group (111), and representative second data of second speed profiles are obtained from the second vehicles of group (112). One or more processing steps are applied to the first and second data to obtain speed profiles, the data from which are used for component modeling. Figure for the abstract: Figure 1

The invention relates to the technical field of medicinal liquor component detection, and discloses an accurate detection system for medicinal liquor components. The system comprises a multi-source spectrum acquisition module, a dynamic component modeling module, a multi-mode difference fusion module, an abnormal component positioning module and a detection strategy optimization module. The multi-source spectrum acquisition module synchronously captures near-infrared absorption spectrum, Raman scattering spectrum and liquid chromatogram-mass spectrum combined data, and generates a standardized spectrum data matrix through adaptive filtering; the dynamic component modeling module constructs a feature extraction network based on a historical spectrum library, and outputs a theoretical component vector containing a target active component concentration interval; the multi-mode difference fusion module generates a multi-dimensional difference tensor through multi-mode difference analysis; the abnormal component positioning module generates an abnormal component distribution probability thermodynamic diagram in combination with the medicinal material association topology network; and the detection strategy optimization module dynamically configures detection parameters according to the thermodynamic diagram. According to the system, accurate detection and abnormal positioning of medicinal liquor components are realized, and the comprehensiveness and intelligent level of detection are improved.

The application discloses a rock component modeling method based on image recognition and belongs to the technical field of numerical simulation tests, and comprises the following steps: S1, image gray processing and coordinate mapping; S2, gray statistics and threshold backstepping; S3, data import and model correspondence; and S4, mineral grouping and attribute assignment steps. The application can accurately acquire the mineral composition information of granite by fusing XRD test results and digital image processing technology, and can construct a modeling system in accordance with the actual rock microcrystal grain morphology and distribution characteristics in the discrete element software, so that the accuracy and the calculation efficiency of the numerical model can be effectively improved, and the visualization capability of the rock crack propagation process can be enhanced.

The application provides a compiling method and device of a programmable logic control system and electronic equipment, wherein the method comprises the following steps: determining configuration setting information, communication data content format information and IO variable logic variable management information of a target programmable logic control system; determining program organization unit source files supporting the target programmable logic control system, and forming program organization unit source files of corresponding target versions; and generating a download file of the target programmable logic control system based on all program organization unit source files of the target versions, so as to control the target programmable logic control system to run. Through the mapping of logic variables and IO variables, the component modeling and management method of the logic program set is established, the componentized splicing type logic adaptation and differential logic incremental content compilation for different wind power equipment configuration scenes are realized, the artificial burden is reduced, and the compiling efficiency is improved.

The invention belongs to the field of gas turbine modeling, and particularly relates to a simplified gas turbine modeling method for impact load analysis, which comprises the following steps of: performing sensitivity analysis on a simplified gas turbine model to obtain a sensitivity expression based on a feature vector; estimating the correction parameter of the sensitivity expression through a target function to obtain an estimated correction parameter of next iteration; and correcting the simplified gas turbine model through the correction parameter of the next iteration. Through geometric model preparation, component modeling and correction and connection modeling and correction of a complex connection form and a complex structure of the gas turbine, a complete machine model capable of being used for impact resistance simulation analysis is obtained, so that the scale of the model is greatly reduced, and the construction efficiency is improved. And the condition that the modal frequency difference between the 500Hz modal frequency and the vibration mode before the reference model and the simplified model is less than 5% and the MAC value is more than 0.9 after the corresponding modal vibration mode is matched is met, so that the simulation precision of the whole machine model can be ensured, and a technical foundation is laid for the subsequent whole machine modeling deepening research.

The invention discloses a multi-channel software radio platform modeling method, device, medium and system, and belongs to the technical field of software radio, and the method comprises the following steps: S1, equipment component modeling: defining inherited equipment components, input and output ports and equipment attributes; s2, packaging the equipment component: constructing a container code and a function code, nesting the function code in the container code, and compiling the container code and the function code of the equipment component together to generate an executable code; and S3, communication between the waveform components and the equipment component: when waveforms are deployed in multiple channels at the same time, the waveform components are connected with the equipment component, and the equipment component receives data of the first waveform component through a port and then sends the data to the second waveform component through a bottom layer driver. According to the method, complete decoupling of waveform modeling and platform modeling is supported, and the workload of waveform modeling in the waveform development process can be reduced.

This invention discloses a multi-channel software-defined radio platform modeling method, apparatus, medium, and system, belonging to the field of software-defined radio technology. The method includes the following steps: S1, device component modeling: defining inherited device components, input / output ports, and device attributes; S2, device component encapsulation: constructing container code and functional code, with the functional code nested within the container code, and compiling the device component container code and functional code together to generate executable code; S3, waveform component and device component communication: when multiple channels are deployed simultaneously with waveforms, the waveform component is connected to the device component. The device component receives data from the first waveform component through its port and then sends the data to the second waveform component through the underlying driver. This invention supports complete decoupling of waveform modeling and platform modeling, which can reduce the workload of waveform modeling during waveform development.

This application provides a distributed server rendering method, system, and medium. The method includes: component-based modeling and metadata definition of the rendered page using a component modeling module to obtain a component dependency model graph; acquiring user rendering request information; analyzing this information using a caching decision module to obtain a caching decision strategy; identifying independent rendering fragments using a fragmented rendering module based on the component dependency model graph; performing server-side fragmented rendering to obtain rendering fragment content packages; and performing multi-channel parallel transmission using a collaborative transmission module. Upon receiving the data, the client interaction module performs DOM rendering and data association binding to restore page interactivity. This application achieves distributed server rendering by constructing a component dependency model graph and defining metadata, making dynamic caching decisions based on real-time context and a preset component caching benefit prediction model, and combining fragmented rendering and multi-channel collaborative transmission with progressive data association and interaction recovery.

The invention belongs to the field of structural strength analysis, and particularly relates to a mechanism motion fatigue reliability platform construction method. The method comprises the following steps: S1, constructing a database; s2, constructing a key part and failure mode module based on the database; s3, constructing a moving part modeling module based on the database; s4, constructing a moving part stress total spectrum module according to a simulation analysis result of the moving part modeling module; s5, constructing a sensitivity analysis module according to the total stress spectrum of the moving part; s6, constructing a fatigue test evaluation module based on the database; s7, constructing a fatigue life analysis module based on the database and the total stress spectrum of the moving part; and S8, constructing a life evaluation module based on a fatigue test evaluation result and a fatigue life analysis result. According to the mechanism motion fatigue reliability platform construction method, an integrated design analysis framework is provided, and a method and means are provided for durability design of aircraft motion parts and construction of an analysis platform.

The application discloses a bridge component intelligent modeling and checking method and system based on Dynamo, belongs to the field of bridge engineering information modeling and structural performance visual analysis, and comprises the following steps: presetting component family sketches and parameter control rules in Revit; constructing a three-dimensional modeling process based on geometric lofting in Dynamo; realizing two-way synchronization between parameters and geometry by using a Python script; calling a bridge component standard database to compare and replace model configurations; structuring nested family parameters and outputting XML format information; connecting a structural analysis platform through a model-checking interface and automatically establishing a finite element model; executing multi-working-condition checking and returning structural performance indexes; embedding visual results in the form of a heat map in Dynamo; realizing closed-loop feedback and real-time updating of structural design and checking; and constructing a whole-process parameter-driven bridge component modeling and performance analysis integrated system.

The invention relates to the technical field of computer software, and provides a rule engine rapid construction method based on liteflow. The liteflow-based rule engine rapid construction method comprises the following steps: S1, a state adaptive component modeling step: defining a logic component comprising at least two operation states; according to the liteflow-based rule engine rapid construction method provided by the invention, an environment monitoring agent can actively sense a thought of link quality reduction or computing resource shortage in real time, and then a core scheduler can intelligently switch an execution path to a standby degradation link within a millisecond level according to a preset graph in a rule storage library, so that the execution efficiency is improved. According to the technical scheme of the invention, the state self-adaptive component is used as a control component, and the degradation logic of the state self-adaptive component is called, so that life-critical core services such as anti-collision early warning and traffic signal lamp control can be ensured to obtain the most basic continuous guarantee under the worst condition, and the safety redundancy, reliability and deployment feasibility of the system in various marginal environments are greatly improved.

This invention provides a method, device, and equipment for optimizing the reliability of distribution networks based on full-component modeling, relating to the field of smart distribution technology. This invention addresses the assessment bias caused by incomplete consideration of fault sources by acquiring basic data of distribution network nodes and full parameters of reliability and cost for all components. It accurately characterizes the correlation between faults and power outages by analyzing the impact of single and multi-fault coupling on load nodes and constructing a fault correlation matrix for all components, reducing computational bias caused by multi-fault coupling. It replaces traditional massive sampling simulation methods with an explicit analytical calculation model based on matrix algebra operations, solving the problems of computational explosion and low efficiency in optimization iteration. Finally, by constructing a dual-objective optimization model and combining iterative solutions with the analytical model, it achieves coordinated optimization of distribution network reliability and economy, solving the problems of large bias and low efficiency in existing distribution network reliability calculation and optimization methods.

The invention discloses a CAD vector data-based engineering quantity calculation method and terminal, and the method comprises the steps: obtaining and analyzing geometric data and attribute data in a target CAD drawing, and generating a vector object set; constructing a global topological structure according to the incidence relation of each object in the vector object set; on the basis of the global topological structure and a preset geometric constraint, performing aggregation in the vector object set to generate candidate component instances comprising structured features; taking the structured feature of each candidate component instance as the input of a neural network model, and outputting parameterized modeling information of the corresponding candidate component instance by using the neural network model; and generating a component model based on the parametric modeling information, performing engineering quantity calculation according to a preset engineering quantity rule based on the component model, and outputting a calculation result. According to the method, the output result of the neural network is directly linked with the component modeling and engineering quantity calculation process, so that the automation and large-scale application of the engineering quantity calculation process can be realized.

The invention discloses an industrial equipment time series data prediction method and system based on multi-frequency component modeling, and the method comprises the following steps: carrying out the multi-layer wavelet decomposition and reconstruction of the obtained time series data of industrial equipment; obtaining multiple layers of low-frequency trend signals for representing long-term stable change of equipment operation data and high-frequency detail signals which are complementary with the low-frequency trend signals and are used for capturing short-term fluctuation; performing interactive modeling on the low-frequency trend signal and the high-frequency detail signal through a feature fusion mechanism to generate an updated low-frequency trend signal; constructing a low-frequency prediction model according to the updated low-frequency trend signal, and generating a low-frequency prediction result for describing the overall operation trend and long-term change of the system; constructing a high-frequency prediction model according to the high-frequency detail signal, and generating a high-frequency prediction result used for supplementing low-frequency prediction result detail information; and fusing the low-frequency prediction result and the high-frequency prediction result of each level, integrating prediction information of different frequency bands, and generating time domain prediction output.

The embodiment of the invention provides a part modeling method and system for radiation emission simulation of an electric drive system, and the method comprises the steps: distinguishing an active element and a passive element in the electric drive system, and building a test platform for radiation emission of the electric drive system; passive elements are independently measured through the test platform, and a passive S parameter matrix is generated; measuring the electric drive system through a test platform, generating an S parameter matrix, separating a passive S parameter matrix from the S parameter matrix, and generating an active S parameter matrix; and converting the passive S-parameter matrix and the active S-parameter matrix into a Z-parameter matrix, selecting a corresponding equivalent circuit topological structure based on the Z-parameter matrix, and fitting the model in combination with a preset algorithm.

The invention discloses a ship motion online identification modeling method based on an incremental Gaussian mixture model. The method comprises the following steps: collecting ship motion state data and motion force and moment; determining input and output in the incremental Gaussian mixture model; collecting data of an off-line ship test, and obtaining global optimal hyper-parameters of the incremental Gaussian mixture model based on the off-line data by using a particle swarm optimization algorithm; sub-models are constructed, whether the sub-models meet conditions for constructing new sub-models or not and whether each sub-model meets conditions for removing or not are judged by using global optimal hyper-parameters and ship motion state data, and the reserved sub-models are combined to obtain an incremental Gaussian mixture model; inputting the motion state data of the ship into a model to predict the motion force and moment borne by the ship at the next moment, and then obtaining the motion state data of the ship at the next moment to realize the dynamic simulation of the motion of the ship; according to the method, multi-modal Gaussian component modeling and conditional regression prediction are combined, and the prediction effect in the test is remarkably improved.

The invention provides a modeling and simulation method for a compressed air energy storage system based on a Modelica language. The modeling and simulation method comprises the following steps: firstly, determining the composition of the compressed air energy storage system to be modeled and simulated; then the compressed air energy storage system to be modeled and simulated is split into all assemblies, a medium model is built based on the Modelica language, and all the assemblies are modeled; on the basis of a Modelica language, connecting models after modeling of all the components, and establishing a compressed air energy storage system simulation model; finally, an equation in the compressed air energy storage system simulation model is solved, parameter values of an inlet and an outlet of each assembly are obtained and can be used for simulation analysis of the energy storage process and the energy release process of the compressed air energy storage system, and guidance is provided for design and efficient operation of the compressed air energy storage system.

The invention discloses an automatic production line three-dimensional simulation debugging and monitoring method, and relates to the technical field of industrial simulation, and the method comprises the steps: carrying out the modularization modeling, motion and sensing configuration and process sequence arrangement of a production line assembly on a three-dimensional simulation platform, and obtaining a simulation engineering package, a process sequence table and a port dictionary; mapping the port dictionary into an object, a variable and an event node of a unified architecture address space, and solidifying a namespace version to generate a binding table; and controlling engineering variable unification according to the port dictionary drive, performing unified architecture subscription release configuration according to the binding table, executing virtual joint debugging, and collecting address space variable change records and event node trigger records to form an event mirror image volume and three-party version fingerprints. According to the method, the event mirror image volume, the namespace version, the virtual controller project version and the simulation project package version form a three-party version fingerprint, and fixed-point correction and namespace version incremental of the control project and the simulation project are achieved.