29 results about "Line model" patented technology

This invention discloses a production line modeling method based on a multi-layered logical model. The method comprises three levels: equipment-level, unit-level, and production line-level modeling. First, equipment is abstracted as a logical chain of "input-processing-output," describing its geometric, physical, behavioral, and rule information through quadruples. Second, multiple equipment logical models are combined into storage, production, and detection units, with internal collaboration driven by state and event, and inter-unit interaction through standardized interfaces. Finally, a production line-level logical model is constructed through a unified interface, achieving seamless integration and simulation expansion of the multi-layered logical models. This method, combined with a production process simulation module, enables the standardization, modularization, and rapid construction of production line models, improving production line design efficiency and operational flexibility.

The present application relates to a kind of event-oriented power grid-life line-user disaster influence whole chain joint simulation method, to solve the problem that existing technology cannot cover composite extreme event, coupling modeling is not accurate, lack of unified whole chain simulation framework.The method generates extreme event scene such as natural disaster, network attack, constructs multi-granularity life line model, carries out joint simulation in two stages (two-way coupling system iterative simulation, one-way influence system section simulation), to combine time-event double-driven interaction, synchronously model 8 kinds of important users.Can accurately simulate whole chain failure process, output power grid fault evolution, life line function loss and user service availability, provide support for city life line resilience assessment and emergency decision-making.

The application relates to a behavior intention prediction method and system for a moving target and a readable storage medium. The method comprises the following steps: inputting multi-modal to-be-predicted data into a trained multi-line model to obtain a behavior intention prediction result; a training process of the multi-line model comprises the following steps: constructing a target loss function according to a first loss function of a primary task, a second loss function of a secondary task and a preset alignment loss function between single-line models in an initial multi-line model; the primary task is direction-level intention prediction, and the secondary task is behavior-level intention prediction; and the trained multi-line model is obtained based on multi-modal training data and the target loss function, thereby solving the problem of poor behavior intention prediction performance of single-modal data, processing each modal data through the multi-line model, and strengthening the model performance through a multi-task and multi-modal alignment loss function in the training stage, so that the reliability and adaptability of the model are significantly improved.

The application provides a power distribution network anomaly prediction method, device, equipment, medium and program product. In the method, the line length, line model, power supply capacity and power consumption capacity corresponding to each line level in the target line from the transformer node to the to-be-installed power node are determined according to the acquired power node connection line diagram of the transformer area and the position of the to-be-installed power node. The grid-connected capacity is determined according to the installation purpose and installation capacity of the to-be-installed power node. Then, whether the power distribution network is abnormal is predicted in combination with the current capacity of the transformer and the node type of the to-be-installed power node. The line length, line model, power supply capacity and power consumption capacity corresponding to each line level in the target line determined, the position, installation capacity, node type and installation purpose of the to-be-installed power node are used for power distribution network anomaly prediction, and the prediction accuracy is improved.

This invention provides a method and system for transmission line inspection and analysis based on digital twins. The method involves: using a digital twin object identifier as the core, uniformly solidifying the transmission line structure and constructing an initial static line structure model; based on continuously collecting multi-source sensing data and forming a time-series operational observation set, constructing a multi-physics coupled evolution model that simultaneously characterizes icing and melting, thermal equilibrium response, and mechanical evolution; identifying hidden risks by jointly discriminating the state evolution trajectory of key state variables and their historical reference distribution; and conducting parameterized perturbations and multi-scenario simulations to assess operational reliability risks. Finally, the risk development trend is reflected back into the spatial line model, generating forward-looking inspection and analysis results. This invention can perform line inspections on transmission lines that are under long-term alternating thermo-mechanical coupling conditions of icing and melting.

The application discloses a kind of general line shape calculation methods of railway line, it is related to railway design technical field, including the following steps: constructing line model management link table container;Through the curvature expression of constructing straight line, circular curve, easement curve, create general line shape data structure;Using curvature expression, combined with numerical integration and nonlinear equation solution, calculate line parameter;Interconversion is carried out to two kinds of data organization models of intersection method and unit method;Build mileage conversion system, carry out the conversion of line model mileage and broken chain;Through using model splitting, merging, editing means, realize the interactive modification of line model;According to the design specification and design speed used by line model, carry out line model compliance check;Line model coordinates, line spacing are calculated and output results;The calculation method is novel and unique, can greatly improve the precision and calculation efficiency of railway line line shape calculation, with strong versatility and expandability.

This invention discloses a method, apparatus, device, medium, and product for generating guide line effects. The method involves: determining the target axis scaling information of the guide line model; determining the final scaling information of the guide line model based on the target axis scaling information and a preset standard length for a single guide line effect; obtaining the tiled texture coordinates of the guide line model based on its base texture coordinates and the final scaling information; determining the scaled texture coordinates of the single guide line effect based on the tiled texture coordinates; determining the sequence frame texture coordinates based on the tiled texture coordinates and the scaled texture coordinates of the single guide line effect; and sampling the sequence frame texture map based on the sequence frame texture coordinates to generate the guide line effect. This invention enables consistent lengths of guide line effects across guide lines of varying lengths.

The embodiment of the application provides a project whole life cycle integrated management method and system based on a digital main line technology, relates to the technical field of project management, and first acquires an original project planning document set in a project starting stage, generates a project task decomposition structure tree according to this, then constructs a task time sequence dependent relationship network, clearly defines the logical relationship and an estimated duration parameter between task node units, then carries out resource demand matching processing to obtain a resource allocation quota set, and finally generates a project initial digital main line model by fusing the task time sequence dependent relationship network and the resource allocation quota set, so that the application realizes integrated management of project whole life cycle information, and improves the scientificity and accuracy of project management.

This application provides a telephone fraud risk assessment method based on the fusion of multi-agent and machine learning, belonging to the field of telecommunications fraud risk assessment technology. It involves collecting and processing historical call data, constructing a call behavior feature system based on the processed data, and training a machine learning model using this feature system. A fraud case knowledge base is constructed based on fraud case data. The method receives the number to be assessed and obtains its real-time call data. Using a multi-agent approach, the machine learning model and the fraud case knowledge base are used to perform risk analysis on the real-time call data, resulting in multiple independent sub-scores. These independent sub-scores are then adaptively weighted and fused to obtain a final risk score. The final risk score is then mapped to a risk level. Thus, through offline model training and case knowledge base construction, online multi-agent parallel analysis, and adaptive weighted fusion of multi-dimensional scores, a high-precision, interpretable, and real-time telephone fraud risk assessment is achieved.

The application relates to the technical field of prefabrication plants, and discloses a production optimization method based on a digital twin production line model, which comprises the following steps: establishing initial models of all processes, simulating the production line by adopting Monte Carlo sampling, discovering capacity and quality risks, putting forward production suggestions and management points, tracking worker and equipment production data in real time during the operation of the production process, updating model parameters, updating the model into a twin model, simulating by Monte Carlo sampling, predicting capacity and quality risks, putting forward a production optimization scheme, continuously updating model parameters and the twin model in the subsequent production process, and finally solidifying into a twin model highly matched with the existing production line. The existing production line twin technology focuses on data acquisition and display, a linear model is adopted for the prediction of capacity and quality, and the variation of samples is not considered enough. The application provides a nonlinear model and key parameters, and the matching of the production line is realized through dynamic updating, which is of great significance to actual production.

This invention proposes a method, system, electronic device, and storage medium for offline-real-time fusion feature prediction of big data based on parameter transfer. It belongs to the field of big data processing and artificial intelligence technology. The method includes: an offline model generating offline analysis results using historical data and extracting transfer parameters; transferring the transfer parameters to a real-time model; the real-time model using the transfer parameters to expand features of real-time data and make predictions; after the offline model completes its analysis of data from the same period, fusing the offline and real-time prediction results using a confidence model fusion method; and finally, the offline model updating the transfer parameters for use by the real-time model in the next period. This invention proposes a parameter transfer mechanism and "three principles," constructing an offline-real-time collaborative closed loop. Without compromising real-time performance, it utilizes the deep features of the offline model to improve the accuracy of real-time predictions, solving the problem of balancing timeliness and accuracy in big data analysis.

This invention discloses a human-machine collaborative method for balancing locally destructive dismantling lines. The method includes: dividing decommissioned electromechanical products into dismantling tasks; determining the dismantling priority relationship between tasks, as well as the dismantling profit, dismantling direction, selectable operators, and selectable dismantling modes for each task; determining the dismantling time and cost for each task by different operators under different dismantling modes; establishing a bilateral human-machine collaborative dismantling line model for locally destructive dismantling guided by workstations, smoothing indicators, robot numbers, and profit, and converting it into a mixed-integer linear programming model, while setting dismantling constraints; constructing an encoding / decoding strategy based on the dismantling constraints, and solving it using an improved multi-objective artificial bee colony algorithm based on reinforcement learning to obtain the dismantling scheme. This invention can obtain a dismantling line balancing scheme with superior overall performance in a short time, significantly improving dismantling efficiency and economic benefits, while reducing energy consumption and environmental impact.

This invention relates to a fault segment location method based on a linked list of fault characteristic coefficients. First, equipment is numbered and the network is partitioned according to the principle of linked lists. A distributed parameter line model is used for modeling. Inherent characteristic coefficients and actual characteristic coefficients are constructed by analyzing the positive-sequence steady-state response law. Based on this, fault characteristic coefficients are formed to determine the faulty line. Further analysis of measurement information within the faulty line is then required to further narrow down the fault segment. This invention uses a linked list algorithm for topological description of the distribution network, which can adapt to dynamic network changes, has high fault tolerance, low complexity, and higher location efficiency. The inherent characteristic coefficients depend only on the line parameters and length, serving as an important reference for whether the line is operating normally. Furthermore, the fault characteristic coefficients have good fault location effects under various fault conditions. This invention not only facilitates further determination of the fault segment but also reduces data processing pressure, promoting rapid fault location.

Provided are a shoe appearance inspection system, a shoe appearance inspection method, and a computer-readable storage medium that can improve inspection efficiency and inspection accuracy. In the shoe appearance inspection system, a virtual line extraction unit (128) extracts a plurality of virtual lines that respectively connect a reference point and a plurality of feature points from an image of a shoe as an inspection object. A model storage unit (136) stores a learning model generated by machine learning, and the machine learning uses the virtual lines and contours extracted from images of a plurality of shoes as qualified products as teacher data. A pass / fail determination unit (134) inputs the plurality of virtual lines and contours extracted from an image of a shoe as an inspection object into the learning model, thereby determining whether the shoe as an inspection object is a qualified product and outputting the result.

The application relates to a transformer continuous winding parameterized modeling method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: acquiring at least one double-line pie model, the double-line pie model acquisition step comprising the following steps: reading parameter data of a continuous winding and initializing the parameter data, constructing a positive pie model and a reverse pie model based on pie internal wire turn connection schemes and wire turn start and end coordinates determined according to the parameter data; correcting model coordinates according to the parameter data and confirming an inter-pie arc connection scheme; acquiring a first wire turn arc model to connect two models based on the corrected coordinates and the arc connection scheme, and obtaining a double-line pie model; acquiring at least one second wire turn arc model to connect at least one double-line pie model, and acquiring a single-coil model; and repeatedly executing the above steps to obtain at least one single-coil model, which is used to construct a transformer continuous winding model. The method can be used for parameterized modeling of a transformer continuous winding.

This invention relates to the field of 3D modeling technology for power lines, and discloses a method and apparatus for 3D reconstruction of missing power line point cloud data. The method involves acquiring 3D point cloud data of power lines, performing voxel sampling and ground point identification to obtain target points for the power line, fitting these points to generate a basic 3D catenary model, and supplementing these with interior points to obtain an initial 3D power line model. Multiple initial 3D power line models are obtained by repeating this process a set number of times, and the model with the most interior points is selected as the target power line model. All interior points of this target model are used as the overall feature vector for calculation; if a preset threshold is met, it is considered a valid power line model. The cross-sectional model of the power line is calculated and integrated with the target power line model to obtain a 3D catenary model. This invention achieves accurate segmentation and reconstruction of power line point cloud data, significantly improving the accuracy and efficiency of power line extraction, especially improving the accuracy of extracting and reconstructing broken power line point cloud data, and enhancing the realism of the modeling.

This invention discloses a self-testing method for Building Automation (BA) links with leakage detection and alarm delay drift, belonging to the field of communication monitoring technology for building automation systems. The method includes: injecting standardized self-test messages into the BA link under test during quiet periods and calculating a baseline delay sequence; filtering the baseline delay sequence to extract current statistical features and obtain historical baseline features; constructing a delay trend line model based on the filtered sequence and calculating its model evaluation parameters; calculating the link health degradation index and determining whether the link exhibits a performance degradation trend based on the historical trend of the link health degradation index and the statistical significance of the delay trend line model; if so, obtaining the predicted delay using the delay trend line model; comparing the predicted delay with a preset delay failure threshold and calculating the remaining safe time using the delay trend line model; and generating a performance degradation warning signal when preset conditions are met. This method achieves proactive prediction and early warning of BA link delay performance degradation.

The application belongs to the field of electric power, and discloses a simulation test system and method for self-healing function of a power distribution master station, which comprises a double-power hand-in-hand overhead feeder line automatic line model, a fault library and a communication configuration unit. The system can simulate current and voltage signals, switch actions and various abnormal states occurring in the self-healing process of each type of fault state under each type of feeder automation mode on the double-power hand-in-hand overhead feeder line automatic line model through the fault library by setting the double-power hand-in-hand overhead feeder line automatic line model and the fault library. The system can simulate the fault handling process of each type of fault and fault interval of various modes of feeder automation, such as centralized feeder automation, on-site reclosing feeder automation, intelligent distributed feeder automation and differential protection mode feeder automation, and can test the self-healing function and fault tolerance of the power distribution master station under different feeder automation modes. The system has multiple test samples, wide scenes and high efficiency.

The application relates to the technical field of space optimization management, and discloses a land space precise management method based on key driving factor thresholds, which adopts technical coupling and comparison of the leading ESs supply-demand types identified by SOM and the key driving factor thresholds extracted by constraint lines. The method solves the technical problem that the data collection, model analysis and policy making links are disconnected in the existing land space evaluation and monitoring, resulting in the difficulty in converting the evaluation results into specific instructions, realizes the full-chain technical closed loop from data input to evaluation suggestion output, ensures the systematicness and integrity of the evaluation and monitoring method, adopts the XGBoost model to process the complex interaction between variables, and innovatively adopts the constraint line model to analyze the constraint boundary of data distribution, so that the technical problem that the traditional evaluation method relies on a linear model and is difficult to capture nonlinear relationships and the evaluation suggestions are mostly qualitative descriptions is solved.

This disclosure provides a rendering method, apparatus, electronic device, and storage medium for model decoration lines. The method includes: determining a target model and its model outline; setting a three-dimensional line model at at least one outline position of the model outline according to the model characteristics of the target model, and configuring the attachment relationship between the three-dimensional line model and the target model; obtaining a target texture map set for the three-dimensional line model; performing normal baking on at least some lines in the three-dimensional line model based on the normals of the target model to obtain target normal information of the three-dimensional line model; adjusting the material of at least some lines in the three-dimensional line model to obtain target material information of the three-dimensional line model; and rendering the three-dimensional line model based on the target texture map, target normal information, and target material information when rendering the target model, so that the target model presents the corresponding line decoration effect. This disclosure can improve the dynamism of model decoration lines.

This invention relates to the field of end-of-life electric vehicle recycling and dismantling, and discloses a dismantling sequence planning method and system based on an improved ant colony algorithm. The method includes: using the improved ant colony algorithm to iteratively solve a U-shaped dismantling line model; in the initial iteration, generating several U-shaped coded initial feasible sequences containing all dismantled parts; performing local optimization operations using adaptive roulette wheel selection and optimization operators on each U-shaped coded initial feasible sequence; selecting the maximum value from all fitness values ​​as the local optimum solution for this iteration, and simultaneously using the feasible sequence corresponding to the maximum value as the local optimum dismantling sequence for this iteration; comparing the local optimum solution for this iteration with the historical global optimum solution, and updating the global optimum solution and global pheromone; and outputting the final solution after completing the global pheromone update for the current iteration. This invention effectively perturbs the search path through the synergistic effect of multiple operators, significantly enhancing the algorithm's ability to escape local optima.

The application provides a kind of same-tower double-circuit line optimization design method and system considering system zero sequence current constraint: generating full coupling impedance matrix and admittance matrix representing the coupling relationship of six-phase conductor, and integrating the line model with the system model containing the neutral point grounding branch of main transformer, to build a system-line coupling simulation model;With phase sequence arrangement and transposition strategy as design variables, the phase sequence arrangement and transposition strategy are screened and selected to generate a set of candidate design schemes;Batch simulation is carried out on the candidate design scheme set, the three-phase current data of the high-voltage side of the main transformer is extracted, and the neutral point zero sequence current evaluation value of the main transformer corresponding to each scheme is calculated by using the symmetrical component method;With the minimum zero sequence current evaluation value and construction cost as double objectives, and the zero sequence current safety limit and voltage unbalance limit as constraints, a multi-objective optimization algorithm is used to solve the Pareto optimal solution set, and a recommended design scheme is output.

This invention discloses a fault diagnosis method for a water electrolysis hydrogen production system based on a reinforcement learning model, belonging to the field of water electrolysis hydrogen production fault diagnosis technology. The method includes: Step 1: By mining textual knowledge in the field of water electrolysis hydrogen production, a quantitative fault knowledge graph and a RL prior constraint rule base are constructed; an equivalent test platform for fault units is built based on the quantitative fault knowledge graph; single or coupled faults of the test platform are triggered in a gradient manner according to the RL prior constraint rule base; the collected numerical values ​​and visual multimodal fault features of single or coupled faults are collected simultaneously to generate a fault sample set; Step 2: By performing Min-Max normalization and feature fusion on the fault sample set, and performing cross-scale domain alignment through a domain adversarial neural network, domain-invariant features are extracted to obtain a multimodal fusion feature vector; Step 3: An adaptive three-fusion RL algorithm is used to construct an offline fault model based on the multimodal fusion feature vector.

This disclosure provides a performance analysis method, an electronic device, and a storage medium. The method includes: obtaining the number of operations of instructions supported by the graphics processing unit (GPU), as well as the runtime data and duration during the execution of a target function. Based on the runtime, runtime data, and the number of operations of instructions executed during the execution of the target function (obtained using the number of operations and the types of instructions executed), the processing speed of the GPU and the computational intensity for multiple memory regions are determined. The processing speed and multiple computational intensities are combined separately as performance indicators of the amount of data read and written to multiple memory regions during the execution of the target function by the GPU. If the bottleneck type of the target function is determined to be a computational bottleneck or a bandwidth bottleneck based on the positional relationship of the performance indicator relative to the roofline model, the performance of the target function is analyzed according to the bottleneck type. This method improves the accuracy of performance analysis of target functions running on a GPU.

This invention provides a method for building an electromagnetic transient simulation model of a 35kV complex wiring collector line, belonging to the field of power system simulation technology. The technical solution of this invention is a method for building an electromagnetic transient simulation model of a 35kV complex wiring collector line, comprising the following steps: S1, collecting and processing data on the topology of the 35kV collector line, overhead lines and cable bodies, frequency domain, insulation status, etc.; S2, constructing a clear line topology model and appropriately simplifying it; S3, building the collector line model; S4, simulating the model; S5, adjusting the model and parameters based on the simulation results. The beneficial effects of this invention are: performing time-domain equivalence and aging prediction on cables and overhead lines can more accurately simulate the changes in line parameters, improving the accuracy of modeling; using an elite-preserving genetic algorithm to simplify the topology model can reduce model complexity and lower the difficulty of modeling while ensuring modeling accuracy.