40 results about "Model synchronization" patented technology

The invention discloses a model optimization method, electronic equipment, a storage medium and a program product, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining input information, inputting the input information to a preset main model, and obtaining first answer information; inputting the input information into a preset shadow model to obtain second answer information; under the condition that an intervention behavior aiming at the first answer information is detected, performing reverse optimization on the shadow model according to the intervention behavior and the second answer information to obtain an optimized shadow model; performing performance evaluation on the optimized shadow model and the main model to obtain performance evaluation results; and determining the model with the optimal evaluation result in the performance evaluation results as a main model, and determining the model with the suboptimal evaluation result in the performance evaluation results as a shadow model. According to the method, the shadow model synchronously running with the main model is deployed, and self-improvement is continuously performed according to the user intervention behavior, so that efficient and continuous model optimization is realized.

The invention discloses a complex man-machine cooperation station operation compliance sequential logic verification method and system based on a multi-modal video, and the method comprises the steps: obtaining a standard operation instruction (SOP), analyzing the SOP, and converting the SOP into a formal model with sequential logic constraints; synchronously acquiring a video data stream, an audio data stream and an equipment data stream of the station; performing real-time analysis on the video data stream by using a human-object interaction (HOI) deep learning model to generate structured visual event metadata; taking the visual event metadata as input, and driving the formalized model to carry out state evolution so as to judge the compliance of an operation process; and performing fusion cross validation on the audio data stream and the equipment data stream at a preset key verification node by taking the time window of the occurrence of the visual event as a reference. By fusing fine-grained visual interaction recognition, strict sequential logical reasoning and multi-modal cross validation, high-reliability closed-loop verification can be carried out on operational process compliance and physical result authenticity.

The application discloses a data synchronization method and system with full-link back pressure characteristics, comprising: configuring metadata of a synchronization task; starting incremental synchronization of a binlog log, and selectively performing full synchronization; routing generated add, delete, modify and query events to a distributed parallel Stream pipeline; and distributing the events to an Actor entity in an Actor model shard cluster according to dimension fields configured for each table in an asynchronous request response mode; performing event persistence and state updating, and complex conversion logic based on the current state, and returning the result to the Stream pipeline; performing message batching, sorting and deduplication processing on Response events by the Stream pipeline; writing the result to a Sink data source, and performing an asynchronous ACK mechanism to ensure reliable synchronization. The application can quickly realize complex model synchronization conversion between heterogeneous data sources through highly configurable synchronization tasks, and has the characteristics of short link, few components and efficient synchronization.

The invention discloses a photovoltaic flexible direct current grid-connected system simulation method and device and a storage medium, and relates to the technical field of power system simulation, and the method comprises the steps: building a photovoltaic module, an alternating current system module and a direct current line module on a simulation platform, so as to construct a simulation model; deploying the photovoltaic module on a first device, deploying the AC system module and the DC line module on a second device, and setting each simulation step length; after environment parameters and faults are set, the first device and the second device are operated at the same time based on the simulation step lengths, and data interaction between the first device and the second device is achieved through a data synchronization interface according to a preset data interaction period till a simulation result is output. Compared with the prior art, the method has the advantages that synchronous calculation of the multi-time-scale model can be realized, so that the problems of module calculation failure and simulation result distortion in the prior art are solved.

The invention discloses a software testing method and system based on a data analysis platform, and particularly relates to the technical field of software testing, and the method comprises the following steps: tracking business semantic change by constructing a semantic evolution perception map, and establishing a semantic-driven data label linkage mechanism to maintain the consistency of training samples of a defect recognition model; semantic consistency drifting is monitored, model output is controlled, a map-enhanced test case generation mechanism is introduced to achieve semantic synchronous generation, meanwhile, a semantic regression verification process is set to ensure alignment of a test case and evolution semantics, and a closed-loop test process covering a full path is formed; according to the method, semantic-driven label linkage and model synchronous updating are realized by constructing the semantic evolution perception map, and a map-enhanced test case generation and regression verification process is introduced, so that the test process is ensured to be consistent with the service semantic dynamic state, the defect identification accuracy and the test coverage integrity are improved, and the test efficiency is improved. The method is suitable for software quality guarantee in a continuous delivery environment.

The present application relates to VR auxiliary debugging and bearing fault positioning technical field, specifically, the present application relates to VR auxiliary debugging and fault positioning method for equipment maintenance, aiming at solving the problem that traditional bearing fault detection adopts visual and static detection, and cannot collect full angle torque dynamic characteristics and large fault positioning error, in the bearing press fitting link, the dynamic torque sensor integrated with the angle encoder is used to collect the instantaneous torque of the full angle, the torque curve of the rotation angle is generated and is associated with the coding storage, when the fault occurs, the measured curve and the standard curve of the same type are called, and are bound to the double virtual bearing model of the VR scene, the virtual driving model is synchronously rotated, the signal module generates the resistance signal according to the torque to control the force feedback data glove, the real rotation feeling is restored by superimposing the viscous damping, the comparison module compares the resistance difference point by point and in the sliding window, if the threshold value is exceeded, the abnormal rotation angle interval is locked, the effective fault area is verified and confirmed through the original point, and the positioning result is output, and the fault positioning precision is improved.

This invention discloses a rapid interactive and verification method for mold structures based on wireframe preview, applied to a computer-aided design system. The method includes: receiving and loading a parametric 3D structural model of the target mold; parsing the 3D structural model, extracting and registering the driving design parameters, and generating a parameter registry; constructing and displaying a lightweight wireframe preview model representing the structural outline based on the parameter values ​​in the parameter registry; adjusting the design parameters, updating the parameter values ​​in the parameter registry in real time, and driving the wireframe preview model to update synchronously; after confirming that the updated wireframe preview model meets the design intent, driving the computer-aided design system to generate the final 3D solid structure based on the final parameter registry. This invention significantly improves the efficiency of mold structure design by providing real-time preview and rapid adjustment interaction during the design process.

The invention provides a cooperative control method and device for a driving motor, a vehicle-mounted terminal and a storage medium, and the method comprises the steps: directly mapping a multi-dimensional input signal, a current instruction and target heating power through a target neural network model, on one hand, the current instruction outputted by the model can be accurately converted into a target torque, and on the other hand, the target heating power is outputted; on the one hand, torque requests of a driver or a whole vehicle are strictly responded, timeliness and stability of power output are ensured, on the other hand, the model synchronously outputs target heating power, and it is ensured that the heating power is consistent with a request value; the cooperative control of the two can execute the driving torque required by a driver or the whole vehicle and ensure the dynamic property; and the requested heating power can be accurately generated, and efficient collaboration and decoupling of the two can be realized.

The application discloses a land use type prediction method and system based on multi-source data fusion, and the method comprises the following steps: acquiring historical land use and multi-source driving factor grid data of a target region; generating a shape self-adaptive conversion probability through a neural network coupled with deformable convolution; determining future land demand based on scenario and policy coupling; iteratively simulating by using a dynamic double feedback cellular automaton model, the model synchronously adjusts the competition inertia coefficient and the spatial neighborhood weight, and dynamically integrates spatial constraints such as ecological protection red lines in a three-dimensional lookup table; finally, the prediction result is converted into standardized land cover data through a probabilistic multi-level classification mapping engine, and a spatial uncertainty distribution map and an area confidence interval are synchronously generated. The method realizes the deep internalization of regulatory rules, provides complete decision support information containing uncertainty quantification, and provides a scientific and reliable technical tool for land space planning and management.

This invention belongs to the field of axial flow pump control technology, specifically relating to an intelligent optimization control method and system for axial flow pump operation. The method includes: constructing and fusing a Gaussian process regression surrogate model corresponding to the physical mechanism and operating data; the model synchronously outputting performance prediction values ​​and prediction uncertainties; calculating the state entropy corresponding to the current operating condition based on the surrogate model; performing heuristic pruning by using the surrogate model to estimate the change in state entropy; the system selecting a subset of candidate rules and calling the surrogate model to infer and calculate the comprehensive gain value; the inference depth decreasing as the prediction uncertainty increases; establishing a penalty mechanism that applies penalties to the gain value based on historical failure probabilities and the current state entropy value; and the system determining the optimal control rule and issuing commands based on the adjusted gain value. This invention can reduce the underlying computing power consumption, prevent long-term error accumulation, prevent repeated equipment oscillations, and ensure the long-term efficient operation of the axial flow pump.

This invention relates to the field of software development technology, specifically providing a method and system for code generation and isolated execution based on a multi-level model. The method includes: acquiring business domain data containing business objects, field attributes, object relationships, and semantic metadata, and constructing a business ontology model; generating code based on the model, dividing the code into a model layer, a read-only logic layer, and a data operation layer, and configuring differentiated code regeneration rules; embedding the business domain data into the model layer code in a structured manner, enabling direct runtime access; performing layer validity verification at runtime through an import interception mechanism, prohibiting the import of read-only logic layer code into data operation layer code; repeating the aforementioned operations when the model changes, and ensuring idempotency of the code generation process according to the differentiated rules. This invention can standardize the code layering architecture, achieve mandatory runtime call isolation, balance model synchronization and custom logic retention, and adapt to automated development and deployment processes.

The invention belongs to the technical field of model teaching, and particularly discloses a digital twin-driven multi-model synchronous teaching method and system, a terminal and a medium. Comprising the steps that modeling information of target equipment is acquired, and a three-dimensional geometric model behavior model and a signal model are constructed based on the modeling information; establishing a mapping relationship between corresponding parts in the behavior model and the three-dimensional geometric model, and establishing an association relationship between the signal model and the behavior model; in the teaching process, driving the behavior model to change the state according to an instruction, and synchronously triggering the state updating of the three-dimensional geometric model and the signal model; and determining a signal flow path in the current working state, and mapping the signal flow path to a part position corresponding to the three-dimensional geometric model to realize collaborative teaching output of the equipment. The behavior state serves as a unified control core, and synchronous updating and consistent operation of multiple models in the same working state are achieved. Therefore, the structural form, the working logic and the signal processing process of the equipment can be kept consistent and corresponding in any working state.

This invention provides a lightweight digital twin migration method and system for vehicle-to-everything (V2X) scenarios, relating to the field of urban V2X digital twins. The invention first constructs a V2X digital twin system, including a communication model, a synchronization delay model, a caching model, and a migration model. Based on the migration model, a digital twin migration utility function is defined. Based on the digital twin migration utility function, the communication model, the synchronization delay model, and the caching model, an optimization problem and its constraints for the V2X digital twin system are established. The optimization problem of the V2X digital twin system is solved to obtain the caching server and the optimal migration strategy. The digital twin is then migrated according to the optimal migration strategy, achieving digital twin migration. This invention utilizes a caching mechanism to effectively address the lag in vehicle twin migration and improve migration flexibility. Simultaneously, the use of Tiny MLP ensures effective feature representation capabilities while adapting to resource-constrained or low-latency scenarios, completing the transformation from environmental observation to action decision-making, and achieving digital twin migration while reducing migration time and energy consumption.

This invention discloses an automated model management method suitable for a 3D collaborative design platform, belonging to the fields of architectural design and software development. The 3D design platform includes a web interface, a Windows application interface, and a Revit interface. The method includes: managing and maintaining a professional template library; project planning and MBS (Model-Based Structure) decomposition; the platform, based on a PDCA (Plan-Do-Check-Act) design task engine, categorizing platform users according to project roles; allowing users to jump to the Revit interface for collaborative model design by clicking on a design task in the Windows application interface; using an automated model management method to compare historical versions of submitted model files, enabling the submitting professional designers to quickly see the differences in modifications and model updates between versions; the platform synchronously uploads submitted models to the server, and after lightweighting the 3D model, it attaches it to the MBS decomposed model structure. This efficiently completes design task allocation and collaborative design work, improving design efficiency and quality.

This invention belongs to the field of intelligent logistics and industrial digital twin technology, specifically disclosing an AGV / AMR digital twin operation and maintenance system that integrates dynamic modeling. The system includes a physical entity perception unit, a visual semantic parsing unit, a multibody dynamics solution unit, a twin model synchronization unit, and a parameter evolution control unit. It uses visual semantic parsing to inversely solve for load distribution and structural deformation as dynamic boundary conditions, and combines this with a recursive Newton-Euler algorithm to calculate forces and deformations in real time, driving the synchronous update of the twin's geometric mesh. Simultaneously, it identifies and corrects mass, friction, and stiffness parameters online based on multi-source observation data, and introduces an aging factor to simulate long-term degradation behavior. Through the above technical solutions, this invention achieves high-fidelity, adaptive, and full-lifecycle digital twin construction, improving predictive control accuracy and operational reliability.

The invention relates to an object model dynamic combination method and system based on capability componentization, and belongs to the technical field of the Internet of Things. Equipment functions are disassembled into independent reusable capability units through a capability componentization mechanism, when equipment is online, only a capability list needs to be declarated, and the capability units can be reused; and the system automatically obtains units from the capability warehouse and dynamically combines the units to generate a target object model. Dependence check and conflict detection are introduced in the combination process to ensure that the model is complete and consistent. And meanwhile, versioning management and gray scale upgrading of the capability units and automatic generation of Mock test codes are supported, so that the test efficiency is improved. The system is deployed at the cloud end, the edge end and the equipment end in a distributed mode, and model synchronization consistency is guaranteed through a consensus protocol. According to the method, the object model coupling degree is remarkably reduced, plug-and-play access is achieved, the method is suitable for complex scenes such as the power internet of things, and the equipment management flexibility and the system reliability are improved.

The application provides a double closed loop collaborative evolution control method, device and medium for full heterogeneous subjects, aiming at the calculation asynchrony and model synchronization error problem of full heterogeneous subjects in a dynamic environment, an asynchronous interaction "execution-evolution" double closed loop architecture is constructed: the subject side uses a time sequence belief network to execute local control flow and realizes asynchronous calculation and synchronization reporting of experience trajectory; the collaborative controller uses a global feature cross attention mechanism to execute strategy evolution flow and triggers a global model synchronization instruction when monitoring an environmental performance deficit. The core innovation is: the evolution timing is triggered accurately by actively determining the environmental drift, and a time and space semantic review mechanism is introduced to forcibly verify the semantic coherence of the parameters issued before the subject hot update and the current physical characteristics. The application solves the timing logic conflict and semantic mismatch risk in asynchronous evolution of large-scale heterogeneous systems, and realizes dynamic calculation synchronization and stable model synchronization among full heterogeneous subjects.

This invention discloses a method and system for locating single-ended traveling wave faults in distribution networks based on the PINN-Transformer model. The method includes: real-time acquisition of transient time-frequency diagrams of fault voltage and inputting them into a trained PINN-Transformer model, and synchronously outputting the fault feeder results and precise location distance. This invention combines the advantages of deep learning in fault time-frequency feature extraction with the mechanistic constraints of physical information neural networks. By constructing differentiable physical residual terms, it ensures that the location results meet physical consistency requirements, thereby improving the ranging accuracy under complex operating conditions to a certain extent.

The application discloses a method and device for modifying appearance attributes of a virtual equipment model and a storage medium. The method comprises the following steps: obtaining a first equipment appearance signal, wherein the first equipment appearance signal is triggered to be generated by a first part of a virtual role model wearing a corresponding first virtual equipment model, and the first equipment appearance signal is used to indicate that a second virtual equipment model corresponding to a second part of the virtual role model is modified in appearance synchronously with the first virtual equipment model; and modifying appearance attributes of the second virtual equipment model according to a signal type and signal content of the first equipment appearance signal to obtain a modification result, wherein the signal type is used to match a signal receiving object, and the signal content is used to determine an appearance attribute modification manner. The application solves the technical problem of high cost and poor flexibility of a method for realizing appearance linkage of a virtual equipment model by using an appearance attribute data label in the related art.

The invention discloses an industrial automation AI hierarchical optimization architecture and method based on edge cloud collaboration, and the architecture comprises a cloud platform which is used for carrying out global data aggregation, digital twin simulation, AI model training and global optimization decision; the at least one edge AI gateway is deployed in an industrial field, is in communication connection with the cloud platform and is used for executing local AI reasoning and performing real-time control on field equipment; and the collaborative manager is used for dynamically distributing AI tasks according to the network state, the calculation load and the service priority and managing data interaction and model synchronization between the cloud platform and the edge AI gateway. According to the invention, organic unification of real-time response and global optimization of the industrial automation system is realized through an innovative layered architecture and a collaborative mechanism, the architecture enables time-sensitive and high-frequency decision-making tasks to be executed on the edge side, the millisecond-level response speed of an industrial control loop is ensured, and the hard real-time requirement of a production process is met.

The invention relates to the technical field of intelligent control, in particular to an intelligent control method and system for polyurethane production based on digital twinning. The method comprises the following steps: constructing a digital twin simulation model corresponding to a polyurethane production whole process flow, and synchronously accessing a real-time sensor data flow corresponding to a production line; performing dynamic assignment based on the real-time sensor data stream to generate a digital twinborn model instance; performing prospective process simulation operation based on the digital twinborn model instance to generate multi-physics field prediction data; a prediction time sequence curve set of the key process state parameters is extracted from the multi-physical field prediction data, high-frequency dynamic comparison is carried out, and a deviation attribution analysis report is generated; and generating a real-time optimization control instruction set based on the deviation attribution analysis report, and obtaining the actual response data of the production line after execution as a new round of real-time sensor data flow execution feedback, thereby forming a closed-loop intelligent control loop. According to the invention, the production regulation efficiency of polyurethane can be comprehensively improved.

This disclosure proposes a method and system for BIM model full lifecycle decomposition and cross-model synchronization. The method includes: encoding BIM model components based on full lifecycle coding rules, binding private attributes of each engineering stage with the component codes of that stage, storing them in the component extended attributes, and generating a BIM master model containing multi-stage attribute information; setting BIM model decomposition rules based on a rule engine; parsing the code of each component in the BIM model, comparing the code with the filtering conditions in the decomposition rules according to hierarchy, packaging the component data corresponding to the successfully matching codes, and saving them as sub-models; establishing association mappings between models; when the source model is modified, the synchronization engine executes the synchronous update of the target model according to the association mapping between the source model and its associated target model, thereby improving the efficiency of cross-stage multi-participant collaboration and providing solid technical support for the digital transformation of the construction industry.

The application discloses a power grid geographic data and device topology model synchronization method and device based on geographic information atlas integration, provides an embedded GIS map model engine to a power grid control system based on a power grid geographic information system, keeps synchronization between the power grid geographic information system and the embedded GIS map model engine, and pushes real-time change data to the embedded GIS map model engine in combination with a self-positioning function of the power grid control system; and the power grid geographic information system updates change conditions of a power distribution network device topology model to the power grid control system in an incremental mode, so that real-time display and application of a power grid geographic information map are realized.

The invention relates to the technical field of semiconductor manufacturing and intelligent chips, and discloses an intelligent sealing test method and system for a wafer in a chip. The method comprises the following steps: acquiring original characteristics and material parameters of a wafer; collecting production line multi-source real-time state data; based on the multi-physics field coupling simulation model, virtual sealing test deduction is carried out; calculating a deviation vector through error back propagation; and generating a modified process parameter instruction set by utilizing a reinforcement learning engine, issuing and executing, and synchronously updating the digital twinborn body. The system comprises a wafer feature acquisition unit, a production line state sensing unit, a digital twinning deduction unit, a deviation analysis unit, a parameter optimization decision unit and an instruction execution and model synchronization unit. According to the method, a'sensing-deduction-decision-execution 'closed loop is constructed, millisecond-level self-adaptive regulation and control of sealing and testing parameters are realized, and the yield and the process stability are remarkably improved.

The application relates to the technical field of enterprise intelligent information management, and discloses a material application automatic filling and auditing method and system based on multi-agent cooperation, which comprises the following steps: a user submits a material application request through text, voice or a Web form; a system generates a structured intention according to the material application request and automatically generates a material application form by calling a retrieval enhancement RAG model; then, a comprehensive verification result is obtained through four-dimensional parallel verification of format, inventory, budget and policy; a rule-machine learning dual-track auditing model is used for synchronous scoring; when conflicts occur, a three-level risk decision is started, including low-risk automatic single passing, medium-risk limited-time sampling and high-risk forced manual review; the review result is used for incremental updating of a model and a rule base online; finally, an approval report is generated and written into a blockchain. Through the RAG enhancement technology and the multi-agent cooperation mechanism, the application realizes full-process, dynamic and intelligent management and control effects from intention understanding to final auditing of the material application.

This invention discloses a method and device for constructing a cross-island heterogeneous federated learning system based on homomorphic encryption. After local training on the client, the local model is packaged and sparsified at the packet granularity. The sparsed packet data is homomorphically encrypted, and the ciphertext and mask are sent to a parameter server. The parameter server aggregates the data according to the client's ciphertext weights and sends the aggregated ciphertext global model and mask to the client. The client decrypts the global ciphertext and unpacks it to obtain the global model, and updates its local model. The client calculates and returns a sketch of its local model. By clustering the sketch, the fastest client in each cluster is selected as a participant in the next round of training, and the contribution is calculated based on the sketch to obtain the aggregation weights for the next round. The trained local model is then applied to the cross-island heterogeneous federated learning system. This invention can improve the efficiency of homomorphic encryption while protecting privacy, and simultaneously resist the negative impact of lagging on model synchronization.

The present disclosure provides a model synchronization method and apparatus, a device and a storage medium. The method includes that a first device determines a model adjustment moment, and adjusts a first AI model to a second AI model according to the model adjustment moment. Multiple devices using the same AI model can adjust the model simultaneously, so that the AI model used at the same moment by the multiple devices using the same AI model is completely matched.

The invention discloses an intelligent power distribution network fault self-recovery system and method based on digital twinning and artificial intelligence, and belongs to the technical field of power system automation. The system comprises a physical entity layer, a data perception and interaction layer, a digital twin engine layer, an AI intelligent center layer and an application and display layer. The method comprises the following steps: constructing a digital twinborn model synchronous with a physical power grid; millisecond-level accurate positioning of the fault is realized by using a deep learning model; a digital twinning environment is used as a simulation sand table, and an optimal self-healing strategy is generated through online optimization of a reinforcement learning agent; the strategy is issued and executed after being subjected to security verification; and model self-evolution is realized based on feedback data. According to the method, model synchronization is realized through a Kalman filtering algorithm, fault diagnosis is carried out by adopting a hybrid model comprising 1D-CNN and LSTM, and a recovery strategy is optimized by utilizing a multi-target reward function, so that the problems of poor flexibility and non-optimal decision in the prior art are solved, and rapid, safe and intelligent self-healing of the power distribution network fault is realized.

The present application relates to VR auxiliary debugging and bearing fault positioning technical field, specifically, the present application relates to VR auxiliary debugging and fault positioning method for equipment maintenance, aiming at solving the problem that traditional bearing fault detection adopts visual and static detection, and cannot collect full angle torque dynamic characteristics and large fault positioning error, in the bearing press fitting link, the dynamic torque sensor integrated with the angle encoder is used to collect the instantaneous torque of the full angle, the torque curve of the rotation angle is generated and is associated with the coding storage, when the fault occurs, the measured curve and the standard curve of the same type are called, and are bound to the double virtual bearing model of the VR scene, the virtual driving model is synchronously rotated, the signal module generates the resistance signal according to the torque to control the force feedback data glove, the real rotation feeling is restored by superimposing the viscous damping, the comparison module compares the resistance difference point by point and in the sliding window, if the threshold value is exceeded, the abnormal rotation angle interval is locked, the effective fault area is verified and confirmed through the original point, and the positioning result is output, and the fault positioning precision is improved.

The application provides a tripping line type millimeter wave radar identification terminal and a cloud end object model synchronization system, relates to the Internet of Things sensing technical field, and the identification terminal comprises: a millimeter wave radar module which is arranged at the entrance and exit of a to-be-identified area to generate bidirectional flow statistical data in real time; and an edge computing device which is connected with the millimeter wave radar module and is used for performing bidirectional independent incremental analysis processing according to the bidirectional flow statistical data to calculate the number of target objects in the to-be-identified area in real time. The application analyzes the tripping line radar flow statistical frame through the edge computing device, maintains the in-door estimation, the in-door entrance and exit cumulative counts and the session by adopting a double-axis independent incremental algorithm, synchronizes the flow statistical attributes and the Internet of Things cloud platform object model by using the MQTT protocol, and can subscribe to the attribute under the optional linkage control, and is suitable for the non-contact flow statistical and occupancy management scene.