402 results about "System model" patented technology

The invention belongs to the technical field of Internet of Vehicles, and particularly provides a federated learning optimization system and method for an intelligent network connection automobile scene, which improves an asynchronous federated learning framework, divides a plurality of vehicles into different clusters due to the isomerism of computing power, and adopts a cloud-edge-end three-layer federated learning framework, so as to realize the optimization of the federated learning of the vehicles. An edge server is deployed on a roadside unit RSU, received model parameters are subjected to pseudo-asynchronous aggregation in a self-adaptive dynamic time window, the received model parameters are subjected to real-time aggregation at a cloud end, the system model training efficiency and quality are improved, meanwhile, the data security is ensured, the user privacy is protected, and the user experience is improved. And the efficiency of the federated learning optimization system and the quality of the global model in the intelligent network connection automobile scene are ensured.

The invention discloses a conversion method and system based on SysML and Modelica model semantic mapping. The method comprises the following steps that S1, a Modelica standard model library is imported into a SysML modeling tool; s2, completing the definition of behavior elements, and forming an SysML model instance; s3, exporting a Modelica model which can be executed by the Modelica simulator; s4, establishing a mapping relation table between SysML model elements and Modelica model elements; s5, when a change event occurs in the SysML model, updating the content of the corresponding Modelica model; s6, the Modelica model is imported into the SysML model, and a corresponding SysML model instance is generated; s7, simulation result mapping and behavior modeling generation are executed, a state transition diagram structure is formed, and structure updating of internal block diagrams in the system model is completed. According to the method, bidirectional conversion and joint simulation optimization between models are realized, and the method is suitable for cross-platform modeling, collaborative design and functional verification scenes of a complex system.

The invention relates to a quantitative evaluation method for robust stability of a hybrid multi-infeed system constructed with a network. The quantitative evaluation method comprises the following steps: S1, constructing a hybrid multi-infeed system model; s2, enabling the series-parallel multi-infeed system to be equivalent to an equivalent network construction subsystem and an equivalent network following subsystem, and respectively calculating a generalized short-circuit ratio as a power grid strength quantitative index; s3, selecting a nominal system model, and determining a critical value of small interference stability of a nominal system through the dominant feature root locus; s4, drawing a frequency domain characteristic curve of the uncertainty perturbation singular value, and determining an uncertainty perturbation upper bound; and S5, drawing a complementary sensitivity peak curve when the decoupled nominal system is connected to alternating current networks with different power grid intensities, and quantifying a critical value and a margin of robust stability under a power grid intensity perspective by combining an uncertainty perturbation upper bound. Compared with the prior art, the robust small-interference stability quantitative evaluation method is creatively provided, and technical support can be provided for coordinated optimization configuration and safe and stable operation of the high-proportion new energy grid-connected system.

The invention relates to the technical field of new energy power systems, and discloses a new energy consumption software model construction method based on a simulation platform, and the method comprises the steps: firstly dividing new energy consumption system units, determining the topological structure and operation parameters of the new energy consumption system units, and constructing a multi-physics field coupling simulation model; then, carrying out distributed parallel solution on the model, defining a global optimization target, constructing a joint optimization and network reconstruction model, respectively adopting a deep reinforcement learning algorithm and graph neural network optimization, and generating an optimization scheme through multi-agent collaboration; whether the optimization target converges is verified, if yes, control parameters are output, and if not, optimization variables are updated to continue optimization; and finally, the optimized parameters are imported into the digital twin platform calibration model integrated with the block chain technology, and hyper-parameters are adjusted. The method improves the accuracy of a new energy consumption system model, optimizes the system operation, enhances the cooperative stability, and promotes the efficient utilization of new energy and the sustainable development of a power system.

The invention relates to an unmanned aerial vehicle group-oriented sensing communication integrated network multi-resource joint scheduling method, and belongs to the technical field of wireless communication, and the method comprises the steps: building a system model of multiple UAV-ISAC tasks, and defining a joint optimization problem; extracting spatio-temporal features from the dynamic heterogeneous graph in which the unmanned aerial vehicle, the user and the sensing target are abstracted as nodes and the relationship is abstracted as edges; taking the features as input, and adopting a layered multi-agent reinforcement learning architecture to solve the joint optimization problem on line; in the architecture, resource allocation and trajectory planning actions are generated through cooperation of a central Actor and all unmanned aerial vehicle Actors, and system performance is evaluated by a central Critic; constructing a multi-target weighted reward function, stabilizing a training process by combining experience playback and a Mini-batch sampling mechanism, and updating network parameters in parallel; and obtaining an optimal resource allocation and unmanned aerial vehicle trajectory strategy through training. The sensing performance is improved, the communication quality is guaranteed, and the defects in the aspect of dynamic resource scheduling in the prior art are overcome.

The invention provides a fault diagnosis method and system for a spindle box of a high-speed gear milling machine based on fault mechanism simulation and data fusion. The method mainly comprises the following steps: S1, calculating a tooth profile wear curve of a gear based on an Archard wear principle; s2, three-dimensional modeling software is used for building system models in different wear states, and simulation data sets under different wear degrees are obtained with the help of dynamics simulation software; s3, establishing a data acquisition system to obtain an experimental vibration data set under the actual working condition of the spindle box; s4, constructing a spindle box fault diagnosis model by using the analogue simulation data set obtained in the step S2; and S5, performing fault diagnosis on the experimental vibration data set obtained in the step S3 by using the spindle box fault diagnosis model constructed in the step S4, and identifying the health condition of the spindle box system. Important data support is provided for a main axle box fault diagnosis and health management system, and the diagnosis accuracy and reliability are improved.

The invention discloses a hemispherical resonator gyroscope attitude drift error compensation method, and relates to the technical field of resonator gyroscopes, and the method comprises the following steps: S1, system modeling: firstly, establishing a mathematical model of a hemispherical resonator gyroscope, including dynamic characteristics and a noise model, for designing a PID controller; s2, a PID controller is designed, the proportion P, integral I and differential D parameters of the PID controller are designed according to the system model, and the parameters determine the response speed and stability of the controller to error signals; s3, error signal calculation: calculating an error signal between the actual output and the expected output of the system in real time, and taking the error signal as the input of a PID (Proportion Integration Differentiation) controller; by comprehensively applying the steps, the robustness of the HRG can be remarkably enhanced, the HRG can still keep high precision and stability when facing environment change, system aging or non-ideal working conditions, and a closed-loop control mechanism is combined to ensure that the system can maintain good performance under various conditions.

The invention discloses an MBSE-based aircraft undercarriage system model integration method, and belongs to the technical field of system engineering. The method comprises the following steps: constructing an aircraft undercarriage system architecture, a classification mapping of simulation design information and a GOPPRR-E element model, and a meta-model library; constructing an architecture model according to a demand-function-logic-physical process, and generating a Simulink simulation model according to the architecture; a simulation model semantic mapping rule is constructed according to an OSLC specification, and design information is analyzed to establish an integrated data model; and a Simulink simulation tool integration adapter is constructed, and a tool interoperation service based on Web is provided. According to the method, a multidisciplinary model can be accurately constructed, uniform expression of architecture and simulation models and semantic consistency of heterogeneous models are realized, two-way transmission of cross-domain information and interoperation between tools are supported, the problem of interoperation between architecture modeling and simulation modeling tools in aircraft undercarriage system design is effectively solved, and the design efficiency is improved.

The invention relates to the technical field of satellite internet, and discloses a low-orbit satellite phased array multi-beam interference modeling and suppression method and system, and the method comprises the steps: selecting a Kaiser window as a core filtering method, and achieving the optimization of beam characteristics through the dynamic adjustment of a shape parameter beta; generating an initial beam directional diagram based on a digital phase matching method, and multiplying the Kaiser window function coefficient by the excitation weight of the 64-array-element linear array element by element to realize spatial domain weighted filtering; the method comprises the following steps: constructing a training data set containing multi-scene interference characteristics, calculating a corresponding covariance matrix and an accurate inverse matrix thereof to form a sample pair, designing a deep neural network architecture, inputting a flattened covariance matrix vector, and learning a complex nonlinear mapping relation from the covariance matrix to the inverse matrix through a multi-layer full-connection structure; a mean square error is used as a loss function to constrain network output precision, and a multi-beam interference system model is constructed; according to the invention, stable and efficient communication of the low-orbit satellite system in a complex electromagnetic environment and under rapid channel change is ensured.

A method and system for power grid optimization control based on a linear time-varying model is provided. The system model is first estimated offline using historical data combined with a piecewise linear regression method that supports a vector regression model. For online applications, a time-varying linear model prediction control framework based on a piecewise linear model coordinates the optimization control of both fast and slow regulating devices in the power grid. This approach does not require precise system model parameters, instead learning the power grid model from historical data. The method optimizes voltage distribution, reduces operating costs, and addresses issues like bad data and collinearity in the historical data, improving the voltage quality and enabling optimal operation even with incomplete models.

The invention relates to the technical field of servo driving, and discloses a closed-loop control method and system for a servo driving system, and the method comprises the steps: carrying out the mathematical modeling of the servo driving system, and building an initialization system model containing a motor equation and a load kinetic equation; collecting a current signal and a position signal of the initialization system model to obtain system operation characteristic data; performing feature extraction on the system operation feature data to obtain system modeling features; constructing a three-ring nested controller according to the system modeling features, and calculating a first system control parameter; performing operation test and time-frequency analysis on the servo driving system after the first system control parameter modulation to obtain system operation state data; and performing particle swarm optimization calculation on the first system control parameter based on the system operation state data to obtain a second system control parameter. According to the method, self-adaptive adjustment of the servo driving system is achieved, and the adaptive capacity and the control precision of the servo driving system under different working conditions are improved.

The invention discloses a strip steel hot continuous rolling loop system modeling and fault detection method and system, and relates to the technical field of industrial steel rolling process modeling and fault detection, and the method comprises the steps: building a state space model of a strip steel hot continuous rolling loop system at a plurality of stable working points based on least square identification; fuzzifying the state space model based on a preset fuzzy rule to obtain a T-S fuzzy model of the strip steel hot continuous rolling loop system; optimizing the T-S fuzzy model based on a neural network, and establishing a target system model in which the neural network and fuzzy kernel representation are combined; and performing fault detection on the strip steel hot continuous rolling loop system based on the sum of residual signals between the model output of the target system model in the preset time period and the real output of the strip steel hot continuous rolling loop system. The technical problems that in the prior art, an accurate mathematical model of a loop is difficult to establish in a model-based fault detection method, and a data-driven fault detection method is low in accuracy and difficult in fault interpretation are solved.

The invention belongs to the technical field of mass concrete construction, and discloses a temperature control system model, a construction method and application. A water cooling technology is mostly adopted in traditional mass concrete construction, but water is difficult to take in special construction sites, a large number of water resources need to be wasted, temperature control measures of the traditional water cooling technology are lagged, and the crack probability is remarkably increased. According to the temperature control system model, the construction method and the application, a second-order response surface is used for fitting a multi-parameter temperature control system model, and the temperature control system model is corrected and optimized according to measured data acquired by a temperature control acquisition unit, so that a closed-loop control system is formed. The concrete grid units and the corresponding air guide pipes serve as minimum temperature control units, construction, temperature control and management are carried out, the management and control granularity is finer and more accurate, and a new research and development direction is provided for the temperature control technology of mass concrete construction.

The invention belongs to the technical field of system simulation, and relates to a joint simulation model integration method and tool and a medium. The method comprises the following steps: firstly, analyzing semantics of a model, including meta-model data analysis, conceptual model description analysis, static semantic analysis and dynamic semantic analysis; then performing interface function event association mapping to obtain a mapping relationship between a model interface and a standard interface; next, configuring a model integration environment, including a running environment, model assembly and scheduling parameters, a generation directory file, an agent model / model scheduling file and the like; and finally, integrating and packaging the packaged proxy model / model scheduling file and the like, and sending the packaged file to a model resource library. According to the method, automatic integration of most types of models (including components, entities, semi-physical models and systems) in the technical field of system simulation can be realized, the integrated polymorphic models can be expanded and reused, the simulation efficiency is greatly improved, and various existing model resources are fully utilized to shorten the integration period.

The invention discloses a profile optimization design method in a positioning system based on an RIS, and the method comprises the steps: building a system model, determining the system composition elements, namely an access point (AP), the RIS, UE and the position relation of the AP, the RIS and the UE, and building a signal model and a measurement model. Fisher information analysis is carried out, a correlation matrix and parameters are calculated, and a position error boundary expression is deduced. And then an optimal RIS profile design strategy is provided, an optimization problem is constructed, and an optimal covariance matrix and RIS profile design are obtained through matrix analysis and derivation. Meanwhile, hardware limitation is considered, constrained RIS profile design is proposed, an optimization problem with constraints is constructed, and an RIS profile meeting actual hardware constraints is obtained through solving by an alternating minimization technology. The present invention improves the positioning accuracy of user equipment (UE).

The invention discloses an edge computing network task unloading and resource allocation method based on optimal service quality, which comprises the following steps of: constructing a system architecture comprising a cloud server, a plurality of edge servers and mobile equipment, and establishing a multi-dimensional system model covering task characteristics, service cache, communication transmission, computing resources, service cost and service quality; constructing an optimization problem aiming at maximizing the long-term service quality of all mobile equipment, and forming a mixed integer nonlinear programming model under the constraints of mobile equipment cost constraint, storage capacity limitation, bandwidth, computing resources and the like; a double-time-slot hierarchical decision-making mechanism is designed, and multi-dimensional joint optimization of service caching, task unloading and resource allocation is realized through a collaborative mechanism that short-term resource allocation is constrained through a long-term caching decision and short-term performance feedback optimizes long-term caching. According to the method, the overall quality of service (QoS) can be effectively improved and the task processing delay and energy consumption can be reduced under the condition that the cost of the mobile equipment and the system resource limitation are met.

The invention discloses an anti-robustness test method and system for an end-to-end automatic driving system, electronic equipment and a storage medium. The method comprises the following steps: acquiring image data of a surrounding environment in a driving process of an automatic driving vehicle; when the current frame is the first frame, the initial disturbance is random Gaussian noise; except the first frame, the initial disturbance of the subsequent frame is the weighted disturbance generated by the previous n frames; based on the image data, multi-view BEV semantic features are obtained, semantic perception consistency loss is constructed, and semantic feature disturbance is optimized through an optimizer; the semantic feature disturbance is used as an initial value, trajectory planning confrontation loss is constructed, and final planning-level confrontation disturbance is generated based on multi-step iteration of gradient symbols; and adding the final planning-level adversarial disturbance to the acquired image data for adversarial testing. According to the invention, the super-resolution effect of the video in the complex motion scene is improved, and the quality and visual effect of the video are enhanced. According to the method, the robustness of the automatic driving system model can be improved.

The invention relates to a semantic communication anti-interference method and system based on a multifunctional intelligent metasurface, and the method comprises a system model design part and a robust optimization algorithm part, and improves the degree of freedom of reconstructing an electromagnetic propagation environment through the flexible regulation and control capability of the multifunctional intelligent metasurface on the phase and amplitude of electromagnetic waves. And meanwhile, actual defects such as hardware power consumption are overcome through an energy collection function. On the basis of the proposed system model, a robust optimization problem with transmission and rate maximization is constructed. In order to solve the optimization problem, a global optimal algorithm based on fast convergence monotone optimization and decoupling second-order cone programming is provided, a global optimal solution can be obtained through fast convergence, and efficient intelligent metasurface semantic communication anti-interference capability obtaining is achieved.

An industrial integrated development environment (IDE) provides a development framework for designing, programming, and configuring multiple aspects of an industrial automation system using a common design environment and data model. Projects creating using embodiments of the IDE system can be built on an object-based model rather than, or in addition to, a tag-based architecture. To this end, the IDE system can support the use of automation objects that serve as building blocks for this object-based development structure. Project data models defining collections of automation objects and their functional relationships can be stored in a model library for selective inclusion in system projects.

The invention belongs to the technical field of power plant thermodynamic and control, and particularly relates to a fractional order model of an ultra-supercritical coal-fired unit coordination control system and an identification method. The fractional order model comprises a coal pulverizing system, a boiler steam-water system and a steam turbine power generation system; the modeling method comprises the following steps: S1, acquiring and storing data of an ultra-supercritical coal-fired unit coordinated control system DCS; s2, constructing a fractional order model of the coordination control system; and S3, fitting a to-be-solved function through acquired data, and identifying dynamic parameters of the fractional order model offline by adopting a segmented time-sharing adaptive particle swarm method. According to the method, fractional order modeling is carried out on the coordinated control system of the coal-fired unit, the dynamic parameters of the system are identified by adopting a segmented time-sharing adaptive particle swarm identification method, the optimal model parameters are obtained through iterative calculation, the precision of the unit coordinated control system model under the wide load is greatly improved, and the system performance is improved. And implementation of a control strategy based on a system model is facilitated.

The invention discloses a margin analysis method based on an MBSE spaceflight equipment model, and the method comprises the following steps: S1, building an MBSE model of spaceflight equipment, and converting design parameters, function demands and system constraints into a unified system model; s2, analyzing and determining coupling design parameters through a system model; s3, margin representation data are formed according to the coupling design parameters; s4, generating a margin distribution result based on the margin representation data; s5, based on the margin distribution result, generating a visual margin distribution result; s6, calculating a safety margin boundary based on a visual margin distribution result; s7, generating an over-limit alarm and verification report based on the safety margin boundary; and S8, monitoring the change of the design parameters in real time according to the over-limit alarm and verification report, and recording the over-limit condition of the design parameters. According to the method, the MBSE concept is introduced, and a more systematic and accurate view angle is provided for margin analysis by establishing a formalized model of the system.

The invention relates to a disturbance source positioning method based on dynamic mode decomposition, which belongs to the technical field of power system operation and analysis and comprises the following steps of: accurately extracting oscillation mode characteristics of a system by performing matrix decomposition on actually measured data; furthermore, a participation factor analysis model fusing time-space characteristics is constructed, and the spatial distribution characteristics and the time evolution characteristics of the modal are comprehensively considered, so that accurate positioning of the oscillation source is realized. Compared with a traditional method, the method has the advantages of no dependence on a detailed system model, high positioning precision and the like, is realized completely based on measurement data calculation, avoids complex system modeling, and has relatively high practical application value and popularization potential.

The invention relates to the technical field of building safety, and discloses a safety transformation monitoring system for building construction and a method thereof. The system comprises a data acquisition and standardization module, a dynamic security entity relationship map construction module, an organization capability and cognitive load modeling module, a hybrid risk identification and conduction calculation engine, a self-adaptive security transformation strategy generation engine and a closed-loop self-calibration module. According to the method, a dynamic security entity relation graph is constructed and updated in real time, the cognitive load of management personnel is quantified, and the cognitive load is used as a dynamic adjustment factor of the conduction probability of risks on the graph; when a safety transformation strategy is generated, comprehensively evaluating a risk reduction effect, resource cost and additional cognitive load cost to output an optimal adaptive strategy; and finally, performing closed-loop self-calibration on the system model by utilizing execution feedback. According to the method, dynamic prospective risk prediction, self-adaptive strategy generation and continuous self-optimization are realized.

The invention relates to the technical field of automatic control, in particular to a switching positive system identification method and system and a storage medium, and aims to solve the problems that in the prior art, a model violates non-negative physical constraints, hyper-parameter estimation is prone to local optimum, calculation efficiency is low, and switching path identification precision is insufficient. The method comprises the following steps: firstly, determining non-negative priori of a system model and pulse response truncated Gaussian distribution through a preparation module; constructing a Bayesian network, and iteratively optimizing a switching path by adopting Gibbs sampling; and finally, based on regularization optimization and Gibbs sampling in combination with Monte Carlo approximation, accurately estimating the pulse response of the subsystem. According to the method, the non-negative characteristics are embedded into the whole identification process, global parameter optimization is achieved, high-dimensional integral calculation is simplified, identification precision and stability are improved, and the method is suitable for multi-scene engineering application.

The invention discloses a ship pipeline system model generation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a pipeline schematic diagram and a specification configuration file after receiving a modeling instruction for a pipeline system, determining an element model of a part forming the pipeline system from a model library according to the pipeline schematic diagram, according to the pipeline schematic diagram and the specification configuration file, the primitive model is adopted to generate an initial pipeline system model, and the initial pipeline system model is adjusted to obtain a target pipeline system model when a model adjustment instruction is received. The initial pipeline system model is generated by triggering the modeling instruction, and the target pipeline system model is obtained by triggering the adjustment instruction to adjust the initial pipeline system model, so that a designer does not need to manually model and adjust the model for multiple times according to a pipeline schematic diagram, and the modeling efficiency of the pipeline system model is improved; the design progress of the pipeline system is accelerated; and the design quality is improved.

The invention relates to the field of intelligent water affairs, and discloses a precise flow control system for intelligent water affairs, which comprises the steps of collecting local water flow change data in real time, extracting flow velocity disturbance characteristics and pipe network transient pressure response, and judging whether unexpected disturbance trigger exists or not; constructing a local disturbance label library based on disturbance trigger source features and a historical operation model, and identifying disturbance sources and flow direction tendentiousness by using fuzzy discrimination and variable weight filtering algorithms; according to the pipe section hydraulic characteristics corresponding to the mismatching behavior, the flow of the target pipe section is corrected through a high-resolution electric proportional valve set and a two-way feedback control unit; constructing a cross-section response chain through the intelligent edge control node, and generating a multivariable adjustment gradient according to the multi-period callback simulation data; flow state data and peripheral environment variables before and after the current round of regulation and control intervention are collected, and system model parameters are dynamically corrected through the integrated evolutionary prediction network. The stability of the intelligent water affair system is improved.

The invention provides an automatic generation method supporting an MBSE system model and a design document. MBSE system model project information is read, and design document basic information is automatically generated; system design flow information of a methodological model constructed in an MBSE system model project is read, corresponding document chapters are generated according to flow design content C, the sequence of the document chapters is determined according to the design flow sequence A, and the outline level of each chapter in the design document is determined according to the hierarchical relation in the design flow hierarchy B; on the basis of the generated design document structure and the read design process corresponding model D, automatically filling each chapter with model content; and dynamically updating the content of the design document. The problems that in the prior art, a design document generation method based on templates and rules is poor in flexibility, and the document and the model are difficult to dynamically synchronize can be solved, and the consistency of the system model and the design document is guaranteed.

The model assembly room comprises a model assembly area, the side face of the model assembly area is communicated with a model preparation area, a model storage area and a control area, and a hoisting hole is formed in the top of the model assembly area; a model assembly upper supporting frame used for supporting the upper portion of the model assembly and a model assembly lower supporting steel column used for supporting the bottom of the model assembly are arranged in the model assembly area. The model assembly room is suitable for stably supporting a large model assembly, debugging and assembling the model assembly in the supporting process, and transferring the model assembly out of the model assembly room from the top of the model assembly room through the model hoisting device after assembly is completed; the technical blank of lack of a model assembly room suitable for stably supporting the large model assembly in the prior art is filled, so that a worker can complete efficient and safe assembly of the large model assembly without entering a test section, and the test efficiency and safety are improved.

The invention relates to the technical field of comprehensive energy systems, and particularly provides a low-carbon building-oriented electro-hydrogen-heat comprehensive energy system modeling method, which comprises the following steps of determining different physical fields involved in a low-carbon building-oriented electro-hydrogen-heat comprehensive energy system and mechanism models under each physical field, determining a model interface of each mechanism model; establishing a dynamic model of each component device according to each mechanism model; based on the dynamic model of each component device, establishing each subsystem model; and combining the sub-system models according to the model interfaces in the physical fields to obtain the low-carbon building-oriented electro-hydrogen-heat comprehensive energy system model. Therefore, on the basis of a modularized modeling thought, the modeling models are divided according to different fields, the coupling relation and the dynamic characteristics in the electro-hydrogen-heat comprehensive energy system can be accurately reflected, then the maintainability and the simulation efficiency of the models can be more effectively improved, and pre-judgment of dynamic changes of the system under different load conditions is helped.

An abstract system model comprising one or more model elements corresponding to one or more infrastructure elements of a deployed system infrastructure is generated. Each model element specifies one or more selectors, and for each model element, each selector includes an indication of at least one infrastructure element that is associated with the model element. An inventory of the one or more infrastructure elements is built. For at least one model element, at least one infrastructure element of the inventory associated with the at least one model element is identified as indicated by the respective one or more selectors of the at least one model element. A bound system model comprising one or more associations between the model elements of the abstract system model and the inventory of the infrastructure elements is generated.