42 results about "Constraint analysis" patented technology

The invention relates to the technical field of equipment management, in particular to an equipment full-life-cycle digital twinborn decision-making system enabling a large model. Comprising a digital twin modeling unit; a large model enabling analysis unit, wherein the large model enabling analysis unit adopts a hydroelectric equipment multi-modal causal constraint analysis model; a whole-process closed-loop management and control unit; and an intelligent decision output unit. According to the method, the multi-modal causal constraint analysis model adaptive to the working condition of the hydroelectric equipment is constructed, and a causal chain verification backtracking mechanism is introduced, so that the problem that the reasoning result lacks logic verification is effectively solved, the logic consistency of a fault reasoning conclusion is guaranteed, and the reliability of decision output is improved; through a scene adaptation mode of'pre-training + fine tuning 'of a large model, multi-modal feature fusion processing and deep linkage of a workflow engine and a digital twinborn body, full-life-cycle management requirements of equipment are fully covered, and the refinement and intelligence level of hydroelectric equipment management is further improved.

The invention relates to an electric power customer service task processing method and device based on multilevel decomposition and iterative enhancement and a storage medium. The method comprises the following steps: executing intention analysis processing and constraint analysis processing on first user request information to obtain target task structured description information; determining a target subtask sequence according to the target task structured description information; and determining at least one abnormal sub-task in the execution process of the target sub-task, and adjusting and executing the target sub-task sequence according to the at least one abnormal sub-task. According to the method, through organic integration of semantic analysis, task decomposition, dynamic planning and iterative optimization, the problems of semantic understanding deviation, low decomposition accuracy and execution disjunction of complex task processing in electric power customer service are solved, and the task processing success rate and the user experience are remarkably improved.

The invention discloses a method for analyzing the testability of a marine launched rocket by light thunder equipment, which comprehensively considers factors such as radar performance indexes, tracking target characteristics and the like through radar tracking capability calculation, tracking angle calculation, visibility constraint analysis, testability constraint analysis and testability time determination. And a quantitative analysis result is provided for the testability of the sea-based light thunder equipment of the rocket launched on the sea, and the accuracy of a calculation result is high. The application of the method provided by the invention can assist the analysis of measurement and control support conditions during maritime emission, especially the development of maritime optical and radar equipment station distribution design and the verification of the rationality of a maritime station distribution method, and also facilitates the optimization of a scheme which meets the key measurement and control requirements and has a better overall measurement effect through the testability analysis of different station distribution schemes.

The invention discloses a lossless evaluation method and device for the repair completion degree of a lining void disease of a hydraulic tunnel. The method comprises the following steps: acquiring a void geometric boundary, and constructing a corrected slurry time-varying electrical constitutive model based on fusion of laboratory test and field embedded sensing data; collecting a ground penetrating radar response sequence in a plurality of curing ages after grouting; performing constraint analysis on the ground penetrating radar sequence by using a multi-physical field coupling model or a physical constraint machine learning model containing slurry seepage, solidification dynamics and electromagnetic wave propagation, and reconstructing a slurry space filling state field; and inferring a receiving state of a far-end node in combination with the void-fracture network topology model, generating a residual void risk quantitative index, and generating a refilling decision. According to the method, through an observation-estimation-prediction-control closed loop mechanism, the problems of model parameter distortion and uncontrollability of a far-end blind area in a traditional method are solved, and accurate quantitative evaluation of the repair quality is realized.

The invention relates to the technical field of structure assembly, and discloses an ancient building digital building block education system, method and device, and the system comprises an operation interaction module which is used for receiving operation instructions of a user about the selection, assembly sequence and node connection mode of ancient building components, and converting the operation instructions into assembly action data recognized by the system; the modeling and constraint analysis module is used for constructing a three-dimensional configuration model of the components in a high-dimensional configuration space according to the received splicing action data, extracting tenon-and-mortise node information between the components, and establishing node constraint conditions for a contact position relationship and a rotation direction relationship between nodes; and the stability verification module is used for constructing a mechanical verification model based on the three-dimensional configuration model and node constraint conditions. Through mechanical verification modeling and a visual feedback mechanism, accurate stability evaluation and real-time operation guidance in the splicing process are realized, and teaching interactivity and splicing precision are improved.

The invention discloses an article grabbing and positioning method, system and device and a medium, and relates to the technical field of visual recognition. The method comprises the steps that a two-dimensional image, collected through a monocular camera, of an object to be grabbed is acquired; the types and the number of the to-be-grabbed articles in the two-dimensional image are recognized, and standard physical sizes corresponding to the types are determined; if the object is a single object, the object serves as a target to-be-grabbed object, the top face corner pixel coordinates of the object are detected, and the three-dimensional pose is solved through the PnP algorithm by combining the physical size and the internal reference of the monocular camera; if the number of the objects is multiple, all candidate corner points are detected, quadrilateral corner point sets of all the objects are screened out through clustering and geometric constraint analysis, then candidate three-dimensional poses of all candidate objects to be grabbed are calculated through a PnP algorithm, and then a target object to be grabbed is selected according to the candidate three-dimensional poses; and finally outputting the three-dimensional pose information of the target to-be-grabbed object. According to the invention, accurate positioning of a single article and three-dimensional pose recognition in a multi-article stacking scene are realized only by means of the monocular camera.

The invention provides a manufacturing decision system-oriented modular functional architecture and a collaborative mechanism thereof, and the structural organization and reusable collaboration of a manufacturing decision process are realized by constructing a multi-layer capability system, a functional module system and a standardized behavior interface. The architecture comprises a data interface module, a decision-making target module, a disturbance response module and a fusion decision-making module, and defines a data flow, a control flow and a trigger relationship among the modules. The system completes target expression, constraint analysis, disturbance identification and collaborative decision generation through standardized access of multi-source data such as orders, productivity, materials and processes, and forms an interpretable and executable decision link. According to the invention, modularization, interpretability and intelligent cooperation of the manufacturing decision-making system are realized, and multi-scene and multi-industry manufacturing decision-making application is supported.

The invention discloses a hydrogen-lithium hybrid aircraft weight estimation method, and relates to the field of overall design of hydrogen energy aircrafts and hybrid aircrafts, and the method comprises the following steps: carrying out constraint analysis according to aircraft task requirements and existing database information, and obtaining a power-to-weight ratio and a wing load; performing performance analysis on the basis of the power-to-weight ratio, the wing load, the aircraft weight initial value and the flight mission profile to obtain an aircraft power demand and an energy demand; calculating the weight of each part of the airplane based on the airplane power demand, the energy demand, the power mixing degree and the energy mixing degree; and obtaining the total weight of the aircraft based on the weight of each part of the aircraft, judging whether the total weight of the aircraft converges or not, if so, outputting the total weight of the aircraft, and completing the weight estimation of the hydrogen-lithium hybrid aircraft. The method solves the problem that an existing method lacks aircraft weight research on different proportions under the condition that energy is supplied to the lithium hydrogen battery at the same time.

The invention discloses a multi-agent system adaptive target tracking formation control method based on reinforcement learning, and relates to the field of multi-agent system target tracking formation control, and the method comprises the following steps: 1, designing a scene, and making a decision in real time; 2, constructing a constraint analysis model, and constructing a target function and a constraint condition; step 3, designing an intelligent agent strategy; designing an observation space, an action space and a reward function; step 4, experiment design; step 5, intelligent agent training; a two-stage training process is adopted; 6, designing a self-adaptive target tracking formation control framework; an ATTFCF framework is provided. According to the method, target tracking and formation control problems are fused, the MPR-DDPG algorithm is adopted for solving, the problems that multi-agent cooperative target tracking and formation control is low in precision and poor in strategy safety are solved, and the method can be suitable for cooperative target tracking tasks of different numbers of agents.

The application relates to the technical field of intelligent vehicle management, and discloses a vehicle state monitoring method and system based on deep learning, wherein the vehicle state monitoring method based on deep learning comprises the following steps: based on structural mechanics, constraint analysis, vibration anomaly detection, loose positioning and fatigue evaluation monitoring task physical dependency relationship, a task dependency directed graph is generated; a multi-modal monitoring data matrix is input into a shared encoder of a multi-task learning network to generate a unified representation vector; the unified representation vector is respectively input into a vibration anomaly detection decoder, a loose positioning decoder and a fatigue evaluation decoder to output initial prediction results of each task; a conditional probability model between task outputs is established based on a constraint relationship defined by the task dependency directed graph, and a consistent diagnosis result meeting physical constraints is generated through maximum posterior estimation. The application solves the technical problems of one-sided diagnosis results, mutual contradictions and low calculation efficiency.

The invention relates to the technical field of electric power Internet of Things communication, and discloses a multi-party computing driven electric power Internet of Things and computing network fusion secure communication method, which comprises the following steps of: firstly, acquiring a node state and a link communication parameter, and constructing a real-time computing network state matrix in combination with topology; performing security-time delay double-constraint analysis on the service request based on the matrix to generate a constraint set; thirdly, determining an optimal strategy through joint optimization of a multi-dimensional path and a threshold strategy; and finally, performing elastic fragmentation and multi-path parallel transmission on the original data. Through global perception and cooperative scheduling of computing network resources, dynamic adjustment of security policies is realized, the problem of uncontrollable time delay caused by resource limitation or network fluctuation in the power Internet of Things is effectively solved, and the real-time performance and robustness of communication are remarkably improved while data privacy security is guaranteed.

This application relates to the field of energy and carbon optimization technology, and provides a method and related equipment for coordinated energy and carbon optimization. The method includes: acquiring energy and carbon state data for each system node in a target energy system; identifying the equipment response characteristics of each system node based on all energy and carbon state data; generating a scheduling strategy parameter matrix and a control strategy switching mechanism for the target energy system through constraint analysis based on all equipment response characteristics; and performing coordinated energy and carbon optimization on the target energy system according to the scheduling strategy parameter matrix and the control strategy switching mechanism. This method can improve the accuracy of coordinated energy and carbon optimization.

This invention relates to the field of knowledge graph technology, and discloses an automated entity relation extraction method and system for knowledge graph construction. The method includes: deep cleaning of heterogeneous data to obtain target text data; contextual structure parsing of the target text data to identify core entities and inter-entity event descriptions; latent constraint analysis of the core entities to obtain a set of deep relations; logical conflict determination between the explicit relation statement set and the deep relation set of the target text data to obtain a set of non-contradictory relations; semantic connection completion of the set of non-contradictory relations to construct a fused relation network; and association reinforcement reconstruction of the fused relation network to confirm the final entity relation set of the target text data. This invention can improve the efficiency of automated entity relation extraction in knowledge graph construction.

The invention relates to the technical field of additive manufacturing and intelligent material design, and discloses an AI coordinated regulation elastic resin DLP forming analysis method and system.The method comprises the steps that firstly, a physical constraint analysis model is constructed and trained, and the physical constraint analysis model comprises a polymerization activity analysis model and a DLP printability analysis model; then, constructing a multi-target generative AI model based on the physical constraint analysis model, and operating the model to generate a candidate molecular structure; and performing dual physical constraint analysis on candidate molecular structures by using the physical constraint analysis model, and filtering to obtain an effective molecular structure set. Then, AI collaborative regulation and control are executed, a material process parameter mapping model is established, and initial DLP forming process parameters are determined for the effective molecular structure set; according to the method, the problems that the material design and the forming process are separated, and the experiment trial and error cost is high are solved, and collaborative design and efficient closed-loop optimization of the material and the process are achieved.

The application discloses a supply chain transaction link intelligent generation method, system, device and storage medium. The scheme receives natural language instructions, business events and external data, assembles context information to generate a task object relying on a PCM service bus; an intent, an entity and constraint analysis are completed through a large model, and a standardized task plan is output. A business topology is built relying on a knowledge base and a knowledge graph, an evaluation function is constructed combining semantic weights, rules and constraints to screen candidate links; a plurality of business systems are linked to check conditions such as resources, budgets and permissions and to prune invalid paths; a plurality of intelligent agent tasks are split to drive a heterogeneous system to complete document landing; after a closed loop, experience, cases, vector and graph data are stratified and deposited. The application realizes the conversion of supply chain transaction links from a fixed process to an intent-driven intelligent generation iteration.

This invention relates to the field of geological exploration technology. It discloses a method, apparatus, equipment, and storage medium for geological exploration path planning. The method includes acquiring basic data of the area to be explored and extracting topological features from the basic data to obtain a regional topology map; performing constraint analysis based on the regional topology map to obtain a constraint quantification lookup table; constructing a node connectivity network based on the constraint quantification lookup table; using the node connectivity network as a search vehicle, performing a multi-objective path search for the exploration target to obtain a set of multi-objective candidate paths; resolving conflicts in the multi-objective candidate path set to obtain a set of compliant paths; scoring all paths in the compliant path set based on preset evaluation criteria, and determining the path with the highest score as the optimal geological exploration path. This invention performs path planning based on regional topology analysis and constraint quantification, generating an optimal geological exploration path that balances target coverage integrity and path compliance.

The application relates to the technical field of aero-engines and discloses an AI-physical model coupling driven engine demand analysis method and system, which fuses natural language demand and industry standards by using RAG (retrieval-augmented generation) technology and a large language model, intelligently analyzes multi-dimensional demand including point performance constraints, physical boundary constraints and task target demand through deep coupling of AI semantic analysis and a physical model, checks the feasibility of a design space based on double physical model verification of constraint analysis and task analysis, ensures that the point performance constraints and the task target demand meet the requirements, and realizes intelligent closed loop from fuzzy text to accurate demand specification book design.

The application provides a dynamic data packet scheduling method and system, and belongs to the field of data processing. The application introduces wireless state perception, real-time flow perception and TSN time constraint analysis mechanism on the DS-TT side, and forms a closed-loop control through dynamic scheduling decision and scheduling execution feedback, so as to realize time perception collaborative scheduling of cross 5G network and time sensitive network TSN. The application can reduce the influence of wireless fluctuation on the time delay of high priority data packet, reduce scheduling conflict and improve resource utilization efficiency, guarantee that the key time sensitive network TSN service is completed within the specified time window, and is suitable for deterministic communication scenes such as intelligent manufacturing, rail transit and power automation.

The invention provides a dynamic data packet scheduling method and system, and belongs to the field of data processing. Wireless state sensing, real-time flow sensing and TSN time constraint analysis mechanisms are introduced to the DS-TT side, closed-loop control is formed through dynamic scheduling decision and scheduling execution feedback, and time sensing cooperative scheduling of the TSN across the 5G network and the time sensitive network is achieved. According to the method, the influence of wireless fluctuation on high-priority data packet time delay can be reduced, scheduling conflicts are reduced, the resource utilization efficiency is improved, it is guaranteed that a key time sensitive network TSN service is forwarded in a specified time window, and the method is suitable for deterministic communication scenes such as intelligent manufacturing, rail transit and electric power automation.

The application discloses a stage lighting and lifting equipment linkage control method based on timing constraint analysis, comprising the following steps: constructing a layered timing constraint matrix of lighting actions, lifting actions and safety checking actions, integrating action start-stop relationship, occupation relationship and interlocking relationship into a unified constraint expression, solving the problems of dispersed cross-equipment action relationship and unclear conflict boundary in the existing linkage control; extracting the precedence edge, parallel edge, mutual exclusion edge and recovery edge, generating an action index sequence and a candidate linkage sequence, improving the sequence and continuity of linkage arrangement; determining the to-be-executed linkage segment according to the link state and forming a linkage control sequence according to the difference priority, reducing the influence of communication fluctuation on key lifting actions; and finally, blocking or rearranging the conflict actions through index backtracking, improving the safety, stability and execution consistency of the linkage control.

The invention provides a time sequence driven chip design cross-stage acceleration system and method, and the system comprises a time sequence prediction module which is used for executing time sequence prediction and evaluation operation on received chip design related input data at the pre-layout stage and / or the pre-wiring stage of chip design; the constraint analysis module is used for analyzing the reasonability of the time sequence constraint by adopting a constraint search method according to the time sequence prediction and evaluation result of the time sequence prediction module and generating the optimal clock period constraint; and the integrated optimization module is used for integrating the optimal clock period constraint to a layout stage and / or wiring stage chip design process, interacting with an electronic design automation tool to complete chip design iteration, and evaluating a design acceleration effect. According to the invention, acceleration of chip design optimization and improvement of design efficiency are realized.

The present application belongs to the technical field of data processing, and particularly relates to an FTO risk analysis method and system based on a feature map. The method comprises: obtaining patent files and to-be-implemented scheme materials; performing constraint analysis on the claim text in the patent files to obtain constraint units with necessity levels; collecting associated evidence according to the constraint units to obtain a candidate evidence set comprising identification candidates and evidence source chains; determining feature influence values according to the uncertainty and necessity levels of the identification candidates; constructing a claim feature map based on the constraint units and the candidate evidence set, and constructing a to-be-implemented feature map based on the to-be-implemented scheme materials; performing constraint satisfaction calculation and consistency correction according to the evidence source chains to obtain a corrected satisfaction degree; and generating an FTO risk analysis result according to the corrected satisfaction degree and the feature influence values. The present application can reduce the misjudgment caused by local similarity and evidence splicing, and improve the explainability and traceability of the risk result.

The invention discloses a near-earth orbit spacecraft implementation layer task planning method and equipment, and belongs to the technical field of spaceflight. The method comprises a core planning process, a constraint processing process, a cooperative work process and a staged iteration process. The core planning process comprises demand submission, event layer planning, instruction layer planning and result confirmation; the constraint processing flow comprises constraint carding, initial arrangement, conflict detection, conflict resolution and planning result implementation; the cooperative workflow comprises resource constraint release, demand submission, plan generation, feedback adjustment, countersigning confirmation and operation control implementation; the staged iteration process comprises pre-planning, monthly planning, weekly planning and real-time re-planning. According to the method, a two-layer planning, multi-party cooperation and staged iteration mode is adopted, complex tasks are adapted, resource configuration is optimized, and cooperation efficiency and real-time response capability are improved.

The invention relates to the technical field of spacecraft design, in particular to a rapid scheme demonstration system for an aircraft. Comprising a task analysis module, a constraint analysis module, a function demand analysis module, a special design module, a design integration module, a demonstration analysis evaluation module, a system modeling simulation module, a model data management module, a demonstration management module, a collaborative demonstration support module and an aircraft multi-field unified model library. According to the method, decomposition, transmission and structured association of different levels from tasks to functions, from functions to indexes and the like are achieved through all the modules, rapid aircraft scheme argumentation from top to bottom is achieved through simulation analysis and rechecking, the complexity and cost of scheme argumentation are reduced, and the design efficiency is improved.

The application discloses a kind of power line loss analysis system and method based on big data, it is related to power line loss analysis technical field, including real-time acquisition power grid equipment operating state and environmental parameter, constructs power line loss dataset;Each power line loss data and line loss rate's rank correlation coefficient is calculated, and strong correlation factor of line loss is output to be weighted, and the real-time data of each line's strong correlation factor of line loss is analyzed by first line loss constraint, whether to meet constraint is judged, and second line loss constraint analysis command is sent out;The strong correlation factor of line loss of each line is analyzed by exponential smoothing residual error method, and second constraint analysis result is obtained, the first constraint analysis result and the second constraint analysis result are comprehensively, and third constraint analysis result is obtained, to third constraint analysis result is rendered line loss rate distribution in real time.Further analysis residual error, capture line aging, nonlinear factors such as load mutation superimposed influence on line loss, combined with multi-stage constraint analysis improves decision robustness.

The application discloses an Excel data knowledge question and answer method based on table structure semantic cooperation, and belongs to the technical field of intelligent question and answer, and comprises the following steps: defining the hierarchical semantic structure, metadata glossary and task category of a cell, and processing an Excel file into a two-dimensional table; generating a cooperative knowledge body for each cell in the two-dimensional table to construct a composite knowledge base; performing multi-constraint analysis on a user question; generating an evidence set based on constraint-driven hierarchical mixed retrieval; guiding a large language model to generate an answer by using a structured prompt; and checking the answer. The application cooperatively models the semantic and structural relationship of table text to improve the expression capability of the real semantics of Excel data, drives hierarchical mixed retrieval through multi-constraint analysis, improves the retrieval accuracy and integrity under complex problems, introduces an explicit executable reasoning mechanism, improves the accuracy and stability of numerical question and answer, constructs an evidence closed-loop checking and self-correction mechanism, and improves the credibility of the answer.

The application discloses a kind of control system and method of ecological discharge flow intelligent gate of hydropower station, it is related to the technical field of hydropower station intelligent control, including, real-time acquisition ecological hydraulic operation data, pre-processing is carried out, and using LSTM model predicts downstream ecological water demand prediction curve;Ecological water demand prediction curve and the ecological hydraulic operation data after pre-processing are combined, and the rule reasoning of fuzzy PD+I control algorithm is carried out to obtain the preliminary control parameter set of gate;By comparing the safety operation constraint condition of gate through numerical constraint analysis method, boundary mapping and smooth adjustment are carried out, and the constraint compliance gate control parameter set is obtained;Based on constraint compliance gate control parameter set and ecological water demand prediction curve, through digital twinborn model, rapid simulation verification is carried out, and the gate control parameter set that is verified is passed;The application is based on the fusion of prediction curve and real-time data by fuzzy PD+I control algorithm, realizes the efficient unity of ecological protection target and gate operation safety.

The application discloses an artificial intelligence technology development auxiliary system and relates to the field of artificial intelligence technology.The system comprises the following components: a multi-modal data acquisition and receiving module, a cross-modal constraint analysis module, an architecture data comparison module, a conflict identification module and an adaptive scheme generation module.Through multi-modal collaborative design, the application can comprehensively and accurately capture architecture requirements, is compatible with various data channels and formats, ensures that there is no omission of requirements, provides high-quality data for architecture comparison, relies on quantitative comparison and hierarchical adaptation mechanism, accurately identifies and resolves architecture conflicts, clearly defines conflict levels and types, generates customized adaptive schemes, adapts to mainstream development tools and realizes efficient optimization of architecture design.

The invention is suitable for the technical field of industrial environment control, and provides a multi-air-duct valve self-adaptive control method and system oriented to temperature and humidity uniformity, and the method comprises the steps: carrying out the dynamic characteristic modeling and constraint analysis of a tail end air valve during the shutdown period of the system, obtaining an opening mapping model and response time of each air valve, and carrying out the dynamic characteristic modeling and constraint analysis of the tail end air valve; determining a global adjustment period and set value compensation; calculating an environment uniformity index, and judging environment stabilization time; generating a control scheme based on the hybrid strategy; establishing a control scheme scoring model, scoring the generated control scheme, and predicting a control effect; the control scheme with the highest score in the fourth step is received, the control scheme is written into the OPC according to the minimum time interval and the air valve mapping relation, and the air valve is controlled. Batch control can be achieved, efficiency is improved, the labor burden is relieved, intelligent decision making based on a model is achieved, dependence on artificial experience is eliminated, self-optimization design is achieved, and the adaptability and robustness of the system are enhanced.