47 results about "Physical verification" patented technology

The invention discloses an electric power system transient stability evaluation sample enhancement method, system and device based on a timing constraint generative adversarial network and a medium, and belongs to the technical field of electric power system safety analysis, and the method comprises the steps: constructing a sample enhancement model, generating transient time sequence data based on random noise and system feature tags by a generator, the discriminator outputs a sample authenticity score and a time sequence consistency score through a time sequence neural network, the physical constraint module calculates physical constraint loss of the generated data, the model is alternately trained in combination with multi-dimensional loss, the trained generator is utilized to synthesize samples, and qualified samples are screened through physical verification. According to the invention, by introducing the LSTM time sequence constraint, the WGAN-GP stable training mechanism and the multi-dimensional physical consistency constraint, three core problems of poor time sequence coherence, modal collapse and physical law violation in the existing sample enhancement method are cooperatively solved, and high-quality transient scarce samples can be generated.

The invention relates to the technical field of integrated circuits and provides a physical IP verification device and method, computer equipment and a medium. The physical IP verification device comprises a first reusable multimode test sequence generator, a verification component physical interface, a second reusable multimode test sequence generator and a verification component serial interface. Therefore, different simulation requirements and scenes such as accelerated simulation efficiency and integrated verification can be considered, protocol consistency verification, functional verification completeness of a physical layer subsystem level and standardized protocol verification are supported, and abundant test vector sets are provided; according to the method, the requirements of butt joint test scenes and completeness verification of different levels such as a transaction layer, a data link layer and a physical layer can be met, debugging interaction interfaces and debugging means with rich levels are supported, different physical interface versions and interface data bus bit widths are supported, and hierarchical and fine-granularity low-power-consumption management is also supported.

The invention provides a data center dynamic environment decision-making method and system, which can be applied to the technical field of data center intelligent dynamic environment operation and maintenance. The data center dynamic environment decision-making method comprises the following steps: collecting dynamic environment multi-modal data of a data center in real time; performing time sequence feature extraction processing on the moving ring multi-modal data to obtain moving ring time sequence features, and constructing unified physical state representation by using a clustering analysis result of the historical fault information and the moving ring time sequence features; executing a physical rule embedding operation on the unified physical state representation to obtain a physical constraint result, and executing a simulation deduction operation based on a world simulation engine on the unified physical state representation to obtain a simulation deduction result; executing a decision generation operation based on a large language model by using the physical constraint result and the simulation deduction result to obtain an initial decision scheme, and executing a multi-dimensional evaluation operation and a scheme optimization operation based on physical verification on the initial decision scheme to obtain a decision scheme; and interactively displaying the decision scheme to the user.

The invention relates to the field of aviation electrical engineering and real-time simulation testing, and provides a multi-level collaborative verification method and platform for an aircraft power generation system control strategy and a storage medium, and the method comprises the steps: an offline simulation stage: carrying out the preliminary design and verification of the control strategy; in the real-time simulation stage, closed-loop real-time verification and parameter optimization are carried out on the control strategy; in the rapid prototyping stage, optimized control strategy codes are deployed to a rapid prototyping controller and are connected with real or high-precision simulated power generation system hardware, and hardware-in-loop-entity hybrid verification is carried out; wherein a unified performance reference and error feedback chain penetrating three stages of off-line simulation, real-time simulation and rapid prototyping is established, a verification result of each stage is used as an expected reference of the next stage, and error monitoring and backtracking correction are carried out. According to the method, through offline-real-time-prototype three-layer progressive verification and a model precision progressive calibration mechanism, the confidence coefficient and the one-time success rate of final physical verification are greatly improved.

The present application relates to the technical field of log analysis, and particularly relates to a kind of audit system operation and maintenance log automatic generation method and equipment.The method parses log stream to distinguish business log entries from unassociated abnormal entries, constructs thread execution sequence and calculates the idle time slice between adjacent business log entries in thread execution sequence;Load the resource constraint mapping table defining hardware resource type and minimum duration;Get the candidate business entries of unassociated abnormal entries, and perform mutual exclusivity and capacity physical verification using the resource constraint mapping table to filter out effective candidate business entries;According to the time difference between unassociated abnormal entries and its effective candidate business entries, filter out the best matching business entries, and then backtrack the business context, inject the exception stack and correct the state to generate structured audit records.The present application realizes non-invasive and high-precision exception attribution based on the rules of runtime resource constraints, and improves the integrity and accuracy of audit data.

The invention discloses a digital back-end netlist conversion and physical verification method and system, a computer and a medium, and the method comprises the steps: exporting a GDS file after layout and wiring from a digital back-end, and completing layout information by fusing standard unit data in a process design suite; exporting a Verilog netlist file from a digital back end; the Verilog netlist file is subjected to netlist format conversion, and a CDL file is obtained; manually calibrating the CDL file, and establishing electrical equivalence of the module-level power supply network and the standard power supply network; and configuring an LVS verification rule, using the calibrated CDL file as a schematic diagram netlist, using an SP netlist generated by the GDS as a layout netlist, explicitly setting a power supply network name, and finally executing LVS verification. According to the method, the electrical connection consistency of the CDL file and the GDS layout can be realized through a standardized power supply network naming mapping mechanism, the LVS verification passing rate is improved, and the manual debugging cost is reduced.

The invention discloses a generator partial discharge sample generation method based on physical constraint and reinforcement learning, and the method comprises the steps: collecting a generator typical defect partial discharge PRPD sample, extracting phase distribution, amplitude asymmetry and discharge repetition rate polarity ratio features, and constructing a multi-dimensional physical feature constraint space; constructing a generative adversarial network comprising a generator, a discriminator and a physical verification module; in the training process, the generator generates a simulated PRPD sample, the discriminator outputs the authenticity probability, and the physical verification module calculates the physical feature deviation of the simulated PRPD sample in the multi-dimensional physical feature constraint space; carrying out weighted fusion on the authenticity probability and the physical characteristic deviation to construct a comprehensive reward function of reinforcement learning; and using a strategy gradient algorithm to update generator parameters according to the comprehensive reward function until convergence, and using a convergence generator to generate a simulated PRPD sample. According to the method, the problems of scarcity and uneven distribution of generator stator insulation fault samples are effectively solved, and a high-quality data basis is provided for improving the generalization ability and accuracy of a diagnosis model.

The application discloses a double-gate reconfigurable field effect transistor process design kit construction method, and belongs to the field of integrated circuit process design kit expansion, reconfigurable device modeling and physical verification. In view of the fact that existing open source PDK mainly faces traditional CMOS devices and is difficult to support circuit design, layout drawing and post-layout verification of double-gate RFET, the application provides a process design kit construction method for double-gate RFET. The method comprises the following steps: constructing a four-terminal RFET compact model and packaging the four-terminal RFET compact model into a SPICE subcircuit; establishing a schematic symbol, a layout unit and parameter configuration; extending LVS device identification rules to identify four-port RFET devices containing a source, a drain, a control gate and a polarity gate; constructing a parasitic parameter extraction file and integrating the parasitic parameter extraction file into a layout verification process; and finally, performing post-layout simulation verification on an RFET inverter and reconfigurable NAND and NOR logic. The application realizes a complete design closed loop of double-gate RFET from a model, a schematic, a layout, DRC / LVS, PEX and reverse label simulation.

The invention relates to the technical field of aviation electrical system design and verification, and provides an aircraft power distribution system controller rapid prototype design method and system based on multi-level hardware-in-loop verification, and the method comprises the steps: S1, an architectural offline simulation stage: carrying out the preliminary function verification and parameter setting of a control logic through a unified simulation model; s2, in a distributed real-time simulation and code generation stage, real-time closed-loop verification and iterative optimization are carried out on control logic; and S3, a hardware replacement type rapid prototype verification stage: performing performance verification and final setting on the control strategy under a highly approximate real working condition. The method provided by the invention not only can greatly reduce the safety risk in the physical test, but also has the remarkable advantages of short development period, low verification cost and support of multi-level integrated verification, thereby providing reliable experimental data support for the subsequent physical verification of the aircraft power distribution system control strategy.

The invention relates to the technical field of intelligent education, in particular to an artificial intelligence general identification education method and system based on bimodal closed-loop feedback. The method comprises the steps that a project task is acquired, students are guided to acquire situational data through an entity AI teaching aid, and a terminal provides real-time feedback for the acquisition process; entity verification is carried out on an entity AI teaching aid in a real environment, if a task is judged to be failed, the intelligent routing unit classifies problems based on multi-dimensional classification, and a feedback mode is dynamically selected; if the rule feedback mode is selected, matching a predefined rule base to generate a structured instruction, pushing the structured instruction to the terminal, guiding the student to take additional data and performing incremental training; if an Agent collaboration mode is selected, calling a cloud large model API to generate a Scotch bottom type guide dialogue, guiding students to analyze problems and select solutions, and performing entity verification again after data supplementary shooting and incremental training are completed; according to the invention, the practice efficiency and thinking cultivation depth of K12 artificial intelligence education are improved.

An electronic design automation (EDA) tool and system for physical verification of workflow for semiconductor circuit designs, and methods of using the same is described. Generally, the method includes (i) automatic splitting an integrated circuit (IC) layout into a number of windows for parallel processing using a plurality of central processing cores; (ii) extracting parasitic capacitance structures from the IC layout; (iii) generating fill elements for masks to fabricate an IC having the IC layout using a metadata matrix to minimize volume of information and resources needed; and (iv) extraction of parasitic resistance structures from IC layout. In some embodiments, the IC layout is additionally or alternatively split into groups of rules for processing. Other embodiments are also described.

This application relates to the field of integrated circuit technology and provides a physical IP verification device, verification method, computer equipment, and medium. The physical IP verification device includes: a first reusable multi-mode test sequence generator, a verification component physical interface, a second reusable multi-mode test sequence generator, and a verification component serial interface. This allows for the consideration of different simulation needs and scenarios, such as accelerating simulation efficiency and integrating verification. It supports protocol consistency verification, physical layer subsystem-level functional verification completeness, and standardized protocol verification. It provides a rich set of test vectors to meet the interfacing test scenarios and completeness verification needs of different layers, including the transaction layer, data link layer, and physical layer. It supports richly layered debugging interfaces and debugging methods, different physical interface versions and interface data bus widths, and also supports hierarchical and fine-grained low-power management.

The embodiment of the invention relates to the technical field of robots, in particular to a hand-object interaction data quality verification system. The system comprises a data preprocessing module which is configured to process collected dynamic interaction data into target interaction data when an operator wears a data glove to grab an object; the physical scene construction module is configured to construct an interaction scene of the hand model and the object model by using the target interaction data based on the simulation engine; the simulation replay module is configured to control the hand model and the object model to perform simulation replay on the target interaction data to obtain physical verification information; and the quality verification module is configured to verify the physical verification information based on multiple verification rules and determine abnormal interaction data. According to the embodiment of the invention, the interaction process is reproduced in the simulation environment, so that the physical anomaly which is difficult to perceive by naked eyes or cannot be judged by a traditional algorithm can be detected, the physical rationality of interaction data is ensured, and the reliability of related data research and application results is improved.

The application discloses a ground physical verification device and method of a space flexible capturing system, relates to the field of ground test verification of space robots, and comprises an outer frame, a target driving mechanism, a flexible capturing system, a soft arm driving mechanism, a mounting plate and a soft arm. The target driving mechanism comprises a rotating driving device for driving the target to rotate in a direction perpendicular to the ground, a vertical driving device for driving the target and the rotating driving device to move along a direction perpendicular to the ground, and a first pull wire for connecting the target to the rotating driving device. The flexible capturing system comprises the soft arm, the mounting plate, the soft arm driving mechanism, the mounting plate connected to the outer frame, one end of the soft arm fixedly connected to the mounting plate, the other end of the soft arm connected to the soft arm driving system through a second pull wire, and the soft arm driving mechanism for controlling the position and the angle of the second pull wire to pull the soft arm so that the soft arm captures the target. The ground physical verification device and method of the space flexible capturing system can realize test verification in a simulated space microgravity environment on the ground.

The invention relates to the technical field of log analysis, in particular to a method and equipment for automatically generating an operation and maintenance log of an auditing system. The method comprises the following steps: analyzing a log stream to distinguish business log entries from unassociated abnormal entries, constructing a thread execution sequence, and calculating idle time slices between adjacent business log entries in the thread execution sequence; loading a resource constraint mapping table defining a hardware resource type and a minimum duration; obtaining candidate service entries which are not associated with the abnormal entries, executing physical verification of mutual exclusiveness and capacity by utilizing the resource constraint mapping table, and screening out effective candidate service entries; and according to the time difference between the unassociated abnormal entries and the effective candidate service entries thereof, screening the best matched service entry, then backtracking the service context, injecting the abnormal stack and correcting the state, and generating a structured audit record. According to the method, non-intrusive and high-precision anomaly attribution is realized on the basis of a resource constraint rule during operation, and the integrity and accuracy of audit data are improved.

The invention relates to the technical field of die design, in particular to a design method and system of a combined die for hot extrusion of a cylindrical gear and the die. Design parameters including the outer diameter, the pattern draft and the sectioning strategy are obtained according to gear geometric parameters and technological requirements, and a three-dimensional model is constructed; after heat-force coupling simulation verification is carried out on the model, 3D printing is carried out according to a preset scaling ratio to prepare a scaling solid model, then the matching relation and the mold opening smoothness of all assemblies are obtained and corrected through material object assembling and demolding testing, finally, final parameters are determined, and a production mold is manufactured; optimization is advanced to a design stage through three-dimensional simulation and 3D printing scaling verification, so that the number of trial-manufacture times is greatly reduced, the research and development period is shortened by more than 30%, and the cost is reduced by more than 60%; the structural performance and demolding behavior of the mold under extreme working conditions are comprehensively evaluated through materialized verification, and the success rate and reliability of large gear hot extrusion forming are remarkably improved.

Aspects described herein relate to physical verification of a design of an integrated circuit to be fabricated on a semiconductor die. One example method involves inserting a dummy partition cell into a parent cell of a layout of the design of the integrated circuit (54). Sub-cells of the parent cell have a first portion that overlaps the dummy partition cell and a second portion that is outside the dummy partition cell (54-1). The method also includes creating, by one or more processors, a cell hierarchy having the sub-cells and the dummy partition cell descended from the parent cell, where the sub-cells have multiple instances in the hierarchy of cells (54-2), and performing a design rule check run set on the parent cell based on the hierarchy (56).

The invention discloses a deep learning fault diagnosis interpretability enhancement method based on a physical verification sandbox, and relates to the field of fault diagnosis, and the method comprises the following steps: collecting equipment monitoring data, and inputting the equipment monitoring data into a diagnosis channel and a verification sandbox channel at the same time; processing the equipment monitoring data by adopting an attention mechanism deep network and outputting a preliminary diagnosis result; constructing a rule engine based on an equipment physical model, and processing equipment monitoring data by adopting a three-level verification mechanism; processing the preliminary diagnosis result and the physical verification result by adopting a feature-physical parameter dynamic mapping mechanism to obtain a mapped result; and carrying out interpretability enhancement output processing on the mapped result to generate a diagnosis report containing physical significance. According to the method, it is ensured that the diagnosis result conforms to the physical law, model stiffness is avoided, the fundamental contradiction between physical constraints and model flexibility is solved, and the diagnosis stability under variable working conditions is remarkably improved.

The invention discloses a flow automation hardware self-calibration control method fusing current and vision, and belongs to the technical field of flow automation, the flow automation hardware self-calibration control method fusing current and vision comprises the following steps: sending an operation instruction to a target host through a USB HID simulation module; and the current sensing feedback module is connected in series on a power supply path of the USB HID simulation module. Through current and vision dual-channel physical verification, the limitation that traditional process automation depends on software for indirect inference is overcome, whether physical operation is actually executed or not can be directly verified, misjudgment caused by system blockage or signal loss is effectively avoided, verification delay is remarkably shortened through millisecond-level current feature detection, and the verification efficiency is improved. Compared with a traditional visual scheme, the order of magnitude is improved. And in combination with dual-channel time sequence alignment analysis, the misjudgment rate caused by environmental interference is greatly reduced.

The invention discloses a steering engine forward design and verification method and system, and the method comprises the following steps: demonstrating the technical requirements of a steering engine, and confirming the overall design technical route of the steering engine; technical requirements of the steering engine are demonstrated, and an overall design technical route of the steering engine is confirmed; virtual verification is carried out, and multidisciplinary simulation analysis and electrical mechanical interface suitability analysis are completed; trial-producing a sample machine, and carrying out real object test verification and virtual-real combination verification; and completing iterative optimization, and outputting digital prototype model data such as a steering engine analysis model and a description model. The system comprises software modules and hardware equipment such as a process interactive design platform, a technical requirement library module, a product library module, a technical index decomposition module, a key parameter detailed design module, a three-dimensional design module, a virtual simulation verification module, a virtual-real combination verification module and a digital prototype model library module. By applying the method, the forward design efficiency and precision of the steering engine can be greatly improved, and the real object verification cost is saved.

This invention discloses an embedded microkernel iterative generation and graph rewriting method and system based on physical constraint feedback. The method establishes a reverse feedback loop from a deterministic backend to the LLM (Limited Language Management Module): First, the deterministic backend is used as a "physical verifier" to tentatively synthesize the initial task graph; when physical violations such as register overflow or volume exceeding limits are detected, a physical diagnostic report containing bottleneck node information is generated; then, the diagnostic report is converted into natural language prompts using feedback encoding technology; finally, the LLM is driven to execute graph rewriting strategies such as node splitting and input serialization to correct the task graph topology. This invention achieves a closed-loop iteration of "physical problem, semantic solution." Experiments show that this method can increase the generation success rate of complex embedded tasks on extremely constrained hardware from 32% to 94%, significantly enhancing the robustness and adaptability of the system.

This invention discloses a method for discovering the core structure of high-entropy alloys based on multi-view characterization, belonging to the field of high-entropy alloy material design and characterization technology. The method includes data alignment enhancement; collaborative candidate mining; joint optimization discovery; physical verification and refinement; and iterative solidification output. This invention collects and preprocesses multi-modal data on the chemical composition, microstructure, crystal structure, and process parameters of high-entropy alloys. It utilizes anchoring processing to establish a unified cross-modal representation, achieving efficient fusion and structured encoding of multi-view data. This enables the construction of a performance prediction model, significantly improving the accuracy of predictions for mechanical properties and other indicators, while reducing data noise and feature redundancy. This method is applicable to different high-entropy alloy systems and multi-modal data types, providing a scalable and practical technical means for the intelligent design and optimization of high-entropy alloys. It has significant scientific research value and promising industrial application prospects.

The invention discloses an operation process control method and system based on a multi-level state machine and dynamic physical characteristic closed-loop verification, and relates to the technical field of industrial internet and safety production management. The method comprises the steps that a server constructs a hierarchical association finite state machine (FSM) of a master control data object and a subtask data object; in response to the physical verification rule, receiving field verification data containing a space-time tag; calculating a feature matching confidence coefficient of verification data, and driving a subtask state to change forward; particularly, in the operation process, a dynamic monitoring thread is started, timeliness parameters or environment sensing data are monitored in real time, once a preset rollback triggering condition (such as overtime or environment abnormity) is met, a subtask state machine is forcibly driven to reversely roll back to a to-be-implemented state, and a main control process is locked in a linkage mode. According to the method, the data state model is compared with the physical characteristics, the timeliness constraint is logically coupled, and hardware interlocking control is introduced, so that automatic closed-loop control and dynamic safety protection of the operation permission process are realized.

The invention belongs to the field of computer vision, and particularly relates to an expressway agglomerate fog detection method based on improved YOLO11n, which comprises the following steps of: 1, collecting agglomerate fog images generated on an expressway, establishing an agglomerate fog data set, preprocessing the agglomerate fog data set, and then dividing the agglomerate fog data set into a training set, a verification set and a test set; step 2, constructing an agglomerate fog detection MGP-YOLO network model based on the improved YOLO11n, wherein the MGP-YOLO network model comprises an improved Backbone layer, an improved Neck layer and a physical verification layer connected with a Head layer; 3, putting the training set into an MGP-YOLO network model for training, and then putting the verification set into the trained model for testing to obtain an optimal agglomerate fog detection model; and step 4, putting the test set into the optimal agglomerate fog detection model for test evaluation, and obtaining a target position and a target category in the image, namely obtaining a final detection result. According to the invention, accurate detection of agglomerate fog is realized based on the improved YOLO11n.

The application discloses a kind of multilevel collaborative prototyping design method, system and readable storage medium of aircraft energy management strategy, belong to avionics electrical design field.The method includes S1 offline simulation modeling and preliminary verification, and establishes and verifies the initial simulation model including multiple systems and energy management strategy;S2 model segmentation and real-time closed-loop verification, the initial model is segmented into controlled object model and control strategy model, and is deployed to different real-time simulation target mechanism to build the first closed-loop verification environment for testing and cross-level result comparison;S3 strategy optimization and hardware-in-the-loop verification, the optimized strategy code is deployed as prototype controller, and the second closed-loop verification environment is built for final verification with real or high-fidelity simulation physical aircraft system.The application realizes the efficient and reliable iteration of control strategy from virtual design to physical integration through hierarchical progressive verification process connected by data link, significantly reduces physical verification risk and cost, shortens development cycle and improves confidence.

The invention discloses a double-layer coordinated power system recovery method and system based on multiple flexible resources. The method comprises the following steps: acquiring basic parameters of a target power system and setting a line recovery rate; solving the upper-layer topology reconstruction model to obtain a generator starting sequence and a skeleton network reconstruction scheme containing a bus connection state; solving the lower-layer flexible resource scheduling model to obtain a load recovery amount and flexible resource scheduling power controlled by a corresponding bus connection state; performing joint solution on the double-layer model by combining a global active power balance equation to obtain a preliminary recovery scheme; and performing physical security verification on the preliminary scheme, and if the verification is not passed, constructing an integer cutting constraint and feeding back the integer cutting constraint to the joint solution for iteration until a final recovery scheme is output. According to the method, strong coupling cooperative scheduling of grid reconstruction and multi-type flexible resources is realized, and the feasibility of global optimization and real power grid landing under extreme disasters is ensured through physical verification and a mutual exclusion constraint iteration mechanism.

The application discloses a kind of object-oriented integrated circuit physical verification rule checking method and system, the physical verification rule checking system includes: the layout file to be verified, layout file parser, rule file, rule parser and physical verification engine, to the geometry definition basic geometry processing object of integrated circuit physical verification, provide a kind of method of accessing the common attribute and / or unique attribute of basic geometry processing object;By establishing the hierarchical mapping relationship of the layout file of integrated circuit, and according to this object-oriented method, the rule statement is programmed, to form a rule description file;Rule parser is responsible for the syntax and lexical analysis of this rule description file;Rule verification engine forms specific physical verification rule checking task according to the rule statement after rule parser analysis.The application makes the programming of rule and the algorithm of physical verification rule checking more easily realized, and later maintenance is more friendly.

The application relates to the field of integrated circuit design, and discloses a physical design method suitable for a high-performance atomic-level computing chip. The application firstly analyzes RTL code, carries out module division, and generates required memories; then carries out logic synthesis, sets up different path groups for the memory-to-register path, and gives different weights; in the layout and wiring stage, according to the algorithm function and data flow direction of each module, top layout planning, module layout planning, power supply and ground planning, layout, clock tree synthesis, wiring and design rule checking are realized; then physical verification, timing analysis, power consumption and voltage drop analysis are carried out, and through sufficient iteration optimization, it is ensured that the final design meets the timing, power consumption and voltage drop requirements. The application focuses on the physical design of the high-performance atomic-level computing chip, effectively deals with the challenges of high computing intensity, high design complexity, large chip scale and high power consumption, and improves the reliability of the chip on the basis of ensuring high performance.

The invention relates to the technical field of artificial intelligence, and discloses a flowmeter predictive maintenance method and system based on artificial intelligence, and the method comprises the steps: firstly carrying out the learning of multi-dimensional operation parameters through an artificial intelligence model, and preliminarily predicting the type of an electrode fault; and then, introducing a physical verification link based on equivalent capacitance, comparing an AI prediction result with an ideal capacitance value determined by a fault type so as to verify and correct the preliminary diagnosis, and finally outputting an accurate target fault type and confidence. Then, fault evolution prediction is carried out based on the target fault type and the corresponding target confidence coefficient, and fault remaining maintenance time is calculated; and finally, generating a personalized maintenance strategy according to the residual maintenance time of the fault and the target fault type. Therefore, different fault types of the electrode can be predicted and identified in advance, and a targeted maintenance strategy is provided.

The invention discloses a substation power supply partitioning method, device and equipment and a storage medium, and the method comprises the steps: carrying out the data processing of collected multi-source substation data, and obtaining a multi-source data set; based on a logic-space-physics verification mechanism, sequentially performing logic association check, geographic space check and electrical physical verification operation on the multi-source data set to obtain a verification data set; constructing a real-time power grid topology connection model based on an incremental updating correction mechanism according to the verification data set to obtain an incremental connected graph model; carrying out load node search analysis in the incremental connected graph model by adopting a breadth-first search algorithm to obtain a node tracing result; and traversing all load nodes of the system according to a node tracing result, and aggregating a plurality of power supply partitions. The technical problem that the power supply partition deviating from the reality is generated due to the fact that the prior art depends on static data partition and is difficult to deal with error information generated by sudden abnormity of the system can be solved.