26 results about "Constraint matrix" patented technology

The application provides a personalized glasses frame design method and system based on 3D facial features. The method obtains facial 3D geometric data through a scanning device; extracts key feature points using an improved HRNet architecture; inputs the feature points into a multi-layer perception machine model to generate an initial frame parameter set containing 32 core parameters of four parts, i.e., frame geometry, nose bridge, temple, and overall design; constructs a multi-dimensional constraint matrix composed of five sub-matrices, i.e., geometry, style, manufacturing, comfort, and medical; establishes a constraint optimization objective function, taking the initial parameter set as the decision variable and the multi-dimensional constraint matrix as the constraint condition, and iteratively solves the optimal frame parameter set with the least constraint condition violation degree through a sequential quadratic programming algorithm; and finally generates a 3D model of the personalized frame. The application realizes full-process automatic design, ensures high adaptation of the frame to the patient's face, and is especially suitable for medical rehabilitation scenarios such as facial asymmetry or postoperative repair.

This application provides a fault propagation prediction method, apparatus, and related equipment, belonging to the field of information technology. An embodiment of this application provides a fault propagation prediction method, comprising: acquiring real-time operation and maintenance data of multiple nodes and historical operation and maintenance data within a preset first time range; constructing a service causal graph based on the historical operation and maintenance data and a preset topology constraint matrix, wherein the topology constraint matrix is ​​used to determine potential causal relationships between the multiple nodes; adjusting the edge weights of the causal edges of the faulty nodes according to the real-time operation and maintenance data to obtain an updated service causal graph, wherein the faulty nodes are one or more nodes among the multiple nodes that have experienced a fault; and predicting the fault propagation probability of the fault among the multiple nodes based on the updated service causal graph. This fault propagation prediction method can improve the accuracy of fault propagation prediction.

This invention relates to the field of digital twin technology, specifically to a method and system for monitoring the operating status of an electric arc furnace based on digital twins. The method includes: collecting multi-dimensional operating parameters and obtaining historical time series and historical normal time series; obtaining abnormal indicator sequences; constructing an initial digital twin model and obtaining a trained random forest model using first and second sample sets; statistically analyzing the sets of correct and incorrect classification trees corresponding to the triggers to obtain a feature importance weight matrix; obtaining a constraint matrix using the recognition accuracy; calibrating the initial digital twin model using the constraint matrix; inputting the abnormal indicator sequences into the random forest model to determine candidate triggers; inputting the initial operating conditions into the calibrated digital twin model to obtain simulation prediction parameter values ​​for the candidate triggers; and comparing the simulation prediction parameter values ​​with the multi-dimensional operating parameters to determine the core influencing factors. This invention can accurately determine the core influencing factors of the current state of an electric arc furnace.

The invention discloses a virtual power plant demand response clearing method and system based on a ciphertext grading constraint, and relates to the technical field of virtual power plant demand response clearing, and the method comprises the steps: carrying out the ciphertext packaging of a distributed resource node scheduling related parameter of a virtual power plant, and obtaining a node scheduling ciphertext parameter; scheduling control factors are obtained according to the node scheduling ciphertext parameters and the current demand gap parameters of the power grid, node priorities are determined and layered based on the scheduling control factors, and a ciphertext grading constraint matrix is constructed; according to the ciphertext grading constraint matrix and the demand response instruction, outputting an encrypted clearing result according to a power distribution objective function; and according to the ciphertext grading constraint matrix, a dynamic threshold reconstruction set is output according to a preset key reconstruction safety threshold, key reconstruction is completed based on the dynamic threshold reconstruction set, the encrypted clearing result is decrypted through the reconstructed key, and a scheduling instruction is generated. The method has the beneficial effects that the safety and the flexibility of the clearing calculation process are considered.

The application discloses a method for optimizing infrastructure network game strategy based on linear constraint, which comprises the following steps: obtaining the topology structure of the infrastructure network, determining the strategy set of the attack side and the defense side, and constructing a basic model of complex network game; determining an index representing network connectivity, calculating the income of the attack side and the defense side under various strategy profiles in the complex network game model, and thus obtaining an income matrix; adding a restriction condition to the strategy selection of the attack side and the defense side, and thus obtaining the strategy constraint set of the attack side and the defense side; converting the solution of the basic model of complex network game into the solution of a linear programming problem, obtaining a mixed Nash equilibrium solution, and thus obtaining the strategy optimization result of the attack side and the defense side. The method can greatly widen the application of complex network game research in practice by introducing the constraint matrix countermeasure into the infrastructure complex network game.

The present application relates to the technical field of steel structure test, and discloses a kind of steel structure veranda health monitoring method and system, comprising: in veranda layout sensing unit and establish finite element model;Analytic node connection relationship generates static topological constraint matrix;According to environmental real-time temperature data, solve thermal deformation response using constraint matrix, and deduct thermal deformation response from total response data to obtain nonlinear residual signal;Based on sensitivity jacobian matrix, residual signal is projected to structure physical parameter space to generate response deviation vector;According to deviation distribution, determine damage location and correct model local grid density and element stiffness, the present application establishes physical mapping path by introducing geometric topological constraint, eliminates the pseudo-mapping noise generated by environmental disturbance, improves the physical authenticity of structure damage identification under complex temperature difference working condition.

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 application relates to a distributed fusion estimation method with sensor saturation and multiplicative noise, and relates to the technical field of sensor network information fusion estimation. A dynamic model of a multi-sensor linear random system with sensor saturation and multiplicative noise is established; state estimation is performed on the dynamic model; a prediction intermediate matrix of a local estimator of each node at a time t is calculated; correction parameters of each node in a sensor network at the time t are calculated; a local estimator of the node at the time t is obtained; whether a total time length is reached is judged; if yes, the process is ended; otherwise, the next step is executed; an estimation error constraint matrix of each node at the time t is calculated; and fusion estimation and fusion estimation error covariance of the sensor network at the time t are calculated. The influence of the sensor saturation and the multiplicative noise on the fusion estimation performance is considered simultaneously, the method is easy to realize on line, and the fusion estimation precision is high.

This invention provides an intelligent detection method for continuous violations in hydropower plants based on multi-view fusion and cross-view re-identification. The method includes acquiring multi-view video streams synchronously collected from multiple monitoring nodes with overlapping spatial views; performing optical enhancement preprocessing based on a light reflection model and extracting trajectory coordinates using a target detection network; extracting 3D re-identification features and performing hard filtering with a time window using a pre-constructed spatiotemporal topological constraint matrix to eliminate false matching pairs that violate physical motion limits and generate a primary associated trajectory; when trajectory observation is interrupted, extracting the terminal momentum vector to perform virtual occupancy prediction within the blind zone, and performing spatial residual elimination when the target reappears to stitch together a globally spatiotemporally continuous trajectory; extracting microscopic skeletal spatiotemporal map features based on the global trajectory, and using a spatiotemporal map convolutional neural network to determine the violation and encapsulate an electronic evidence chain. This invention overcomes the problems of tracking disconnection and false alarms caused by homogeneous personnel clothing, strong metal reflection, and long-term occlusion in industrial scenarios through coupled verification of visual features and physical kinematic laws, thus improving the robustness and credibility of violation evidence collection.

This invention discloses a safety assessment method for inverting the internal force state of anti-slide piles based on corrected inclinometer data. Inclinometer data is collected along the depth direction of the anti-slide pile using an inclinometer, and the data is preprocessed. A polynomial model is established to fit the pile deflection. Then, a constraint matrix and constraint vector are constructed, and the constraints are solved using regularization. The distribution of internal forces in the pile is calculated using derivatives. The quiet zone at the bottom of the anti-slide pile is identified, and the foundation coefficient at each measuring point is inverted. The distribution of landslide thrust and thrust characteristic parameters are analyzed. The safety factor is calculated using the extreme values ​​of thrust internal forces, and a safety assessment and early warning are provided for the project. This application intelligently integrates the measured displacement of the pile top dial gauge with the relative displacement data of the inclinometer tube, solving the system deviation problem caused by initial readings and zero-point drift. It can accurately reflect the actual stress and deformation characteristics of the pile body. A high-order polynomial continuous fitting model for the entire pile achieves a precise description from discrete measuring points to continuous deformation.

This invention provides a quantum-classical feature fusion and recognition method and system for high-altitude operation safety monitoring, relating to the fields of quantum computing and computer vision. The method includes extracting the spatial coordinates and local image features of multiple safety nodes; normalizing and encoding the local image features into initial qubits; constructing a spatial constraint matrix based on the distance between spatial coordinates to sparsify the dynamic entanglement parameters; inputting the initial qubits and constrained entanglement parameters into a quantum circuit; using the spatial constraint matrix to control the entanglement gate to generate a quantum final state; measuring the quantum final state to obtain a quantum feature vector; and generating a drift signal based on the difference between adjacent time points; adaptively fusing the quantum feature vector with the local image features; and inputting the fusion, along with the drift signal, into an evaluation network to output a risk probability. This invention uses physical constraints to drive the isomorphic evolution of the quantum entanglement structure, mitigating gradient vanishing and improving early warning capabilities under occlusion conditions.

The present application provides a kind of multi-well sedimentary cycle statistics and waveform embedding learning seismic inversion method, it is related to seismic inversion technical field, including: collection lithology parameter and depth parameter, identifies lithology conversion interface and calculates cycle thickness sequence to obtain cycle distribution characteristics, constructs cross-well cycle correlation and is converted into spatial constraint matrix, with lithology parameter operation obtains sedimentary cycle control factor;Seismic waveform data is obtained, and amplitude sequence and phase sequence are extracted and mapped to uniform feature space to obtain waveform embedding vector, based on waveform embedding vector and sedimentary cycle control factor, cross-well waveform similarity is calculated to generate horizon correlation diagram;Horizon correlation diagram topological traversal is identified connected domain, and the center embedding vector in connected domain and sedimentary cycle control factor are cooperatively decoded to obtain horizon physical property prediction value, and inversion result is generated after cross-well consistency correction.

The application discloses a resource space optimization configuration method and system for land planning, and relates to the technical field of land planning and resource space configuration; the application collects and pre-processes space data of a planning area, constructs complete topological adjacency relations, establishes a neighborhood correlation constraint matrix and a constraint processing priority sequence, filters candidate land use types through priority, completes initial configuration based on comprehensive configuration scores, detects and resolves neighborhood conflicts, adjusts land use structure deviation, and outputs a configuration scheme after constraint compliance verification, effectively solving the problem that neighborhood correlation constraints are difficult to be effectively coupled and processed in the optimization solving process, significantly improving the scientificity and rationality of land resource space configuration, and improving the constraint compliance rate of the configuration scheme and resource utilization efficiency.

This paper relates to an intelligent packing method, device, and system for heterogeneous items considering segmentation constraints. First, it obtains the item dimensions, box dimensions, and a segmentation constraint matrix defining item conflict relationships. Then, it constructs a hybrid integer programming model that simultaneously incorporates geometric and segmentation logic constraints. A hybrid branch-and-price algorithm is used to solve the model. This algorithm iteratively optimizes through a column generation framework, where the pricing subproblem integrates particle swarm optimization and spatial heuristic decoding to efficiently generate new single-box loading patterns. Finally, a branch-and-bound strategy is combined to obtain the integer optimal solution. The system includes modules for data acquisition, optimization calculation, and solution output, achieving a closed loop from perception and decision-making to execution. This invention solves the problem that existing technologies cannot collaboratively optimize space utilization and complex business rule constraints. It can minimize the number of packaging boxes used and improve the feasibility and execution efficiency of packing schemes while strictly meeting segmentation requirements such as the isolation of fragile items.

The application discloses a MIMO-SAR robust beam forming echo separation method based on LASSO regression, which comprises the following steps: S1, a MIMO-SAR transmitting waveform is designed, and a pitch multi-channel system is used to collect echo signals; S2, a pitch dimension space snapshot is constructed, and a sample covariance matrix is estimated; S3, a space domain search is performed based on a LASSO regression model, and the angle of arrival of each signal component is roughly estimated; S4, the width of a beam main lobe and a null is set, and a constraint matrix is designed according to the estimated angle of arrival information of the expected and interference signals; S5, a LASSO regression model is constructed based on the constraint matrix, and an optimal weight vector is solved; and S6, the space snapshot in the step S2 is processed by using the optimal weight vector, the interference signals in the echo are suppressed, and the final echo separation is realized. The method can still apply a non-distortion response to the expected signal direction under the condition of terrain undulation, can sufficiently suppress the interference components, and has high robustness and wide application prospect.

The application discloses a dynamic threshold leakage identification method based on hierarchical time series prediction, and relates to the field of leakage detection of water supply systems. By obtaining water quantity or water meter data of different levels with hour granularity, standard time series data sets are obtained through format conversion, time series completion and data merging processing. The top, middle and bottom sequences are identified. For water types lacking direct monitoring data, a virtual sequence is constructed by using hierarchical aggregation constraint coupled moving average filtering to complete the aggregation constraint matrix. A time series prediction model with hour granularity is constructed based on a hierarchical hybrid network to determine the prediction performance with coefficient of determination and root mean square error. The upper limit of the interval is used as the normal water consumption boundary by using the prediction interval of different confidence levels output by the model. The optimal dynamic threshold proportion is determined by traversing the threshold candidate range. When the actual water quantity exceeds the proportion, it is determined as potential leakage. The accuracy, precision and recall rate are used as evaluation criteria to maximize the recall rate and reduce the missed detection loss.

This invention provides a method for detecting conflicts in the construction layout of microgrid power-grid-load-storage equipment based on 3D vision and graph optimization algorithms, belonging to the interdisciplinary field of swarm intelligence and computer vision. The method involves collecting 3D point clouds from the construction site and preprocessing them to obtain registered point clouds, simultaneously extracting equipment and structural component data, and retrieving electrical safety distance and maintenance access specification data. A 3D semantic model is constructed and bounding boxes are generated. A physical constraint graph is built using the bounding boxes as nodes and safety distances as edge weights, and input into an improved graph convolutional network to complete layout conflict detection. Access widths are obtained, and maintenance accessibility evaluation indicators are calculated based on specifications. A spatial constraint matrix is ​​established based on safety distances, with maintenance accessibility as a hard constraint. The goal is to reduce layout conflicts and improve space utilization. Heuristic search iterative optimization is used to output the optimal equipment layout scheme. This solution can provide intelligent decision support for the construction layout of microgrid power-grid-load-storage equipment.

The application discloses a kind of based on minimum operating gene unit and digital twin dining operating real-time deduction and closed-loop control method and system. Including: the dining operating entity is disassembled into minimum operating gene unit represented with characteristic vector;Correlation constraint matrix is constructed, and its triplet definition space mutual exclusion time sequence dependence and resource binding relationship and priority;With gene unit as node, construct digital twin, and gene state is synchronized in real time through multi-source heterogeneous data stream;In response to trigger event, the multi-branch discrete event simulation of gene state combination snapshot is carried out, and gene state transition is simulated in parallel based on constraint matrix and priority sorting algorithm, and gene state evolution function is formalized description and coefficient is dynamically optimized by machine learning;According to multi-objective weighted evaluation function, select optimal deduction branch, convert into instruction set by mapping rule, and execute through API to physical terminal. Realize perception-decision-execution closed loop, decision second level, error <5%, utilization rate is improved by 15%-25%.

The present application relates to a kind of logistics network dynamic optimization method and system based on digital twinning, comprising the following steps, obtaining the real-time state of transport node and mapping to digital twinning model, construct logistics twin network model;The scene is analyzed to obtain multi-objective constraint matrix;Accordingly, path combination optimization is carried out, and multiple candidate scheduling schemes are generated;Quantitative calculation each scheme scheduling index obtains score, and according to score, selected target scheduling scheme, realize the precise scheduling of logistics under complex constraints, solve the technical problems that traditional scheme often cannot respond to the instantaneous change of transport node state in real time according to static model and periodic updating technical scheme, leading to significant time lag and deviation between the scheduling scheme generated and actual operation scene.

The present application relates to the technical field of geophysical exploration, in particular to a borehole-ground electromagnetic inversion method, device and storage medium. The method comprises: setting prior information; calculating borehole-ground electromagnetic response; calculating model data fitting term; calculating model regularization term containing constraint matrix based on minimum support gradient; solving gradient and Hessian matrix of objective function; iteratively solving to obtain model increment; determining update step length to obtain updated model; using the updated model to obtain borehole-ground electromagnetic response and calculate data fitting difference; judging whether the data fitting difference meets the convergence condition and whether the iteration number k meets the convergence condition; if one of them meets the condition, the iteration is exited and the model is output. The present application enhances the ability of borehole-ground electromagnetic to depict deep formation interface, improves the precision of borehole-ground electromagnetic inversion of deep formation interface, and can more intuitively and clearly invert the interface between formations at different depths.

This invention relates to the field of automated training technology and discloses an intelligent teaching and training service system, including a host computer terminal, an industrial control terminal, a hardware-in-the-loop fieldbus gateway, and physical actuators. The host computer terminal generates a mapping dictionary and sends it to the hardware-in-the-loop fieldbus gateway. The gateway extracts uplink messages, calculates the system energy integral value, corrects the basic safety constraint matrix, and generates a dynamic constraint matrix. The gateway intercepts downlink messages, predicts the physical state vector, and overwrites the message when it exceeds the safety range, sending it to the physical actuator. It also sends an anomaly tracing feedback message in conjunction with the mapping dictionary. This invention can intercept abnormal control commands at the underlying hardware level to prevent physical equipment from being damaged by collisions, dynamically shrink the safety boundary based on the real-time energy state of the equipment, and accurately trace underlying control anomalies to training code statements, effectively improving the efficiency of debugging training code and ensuring the safety of the training system.

The application discloses a track allocation method based on pseudo Boolean optimization local search in wiring, and steps of the method comprise: generating a topological model containing hierarchical track, wire net and obstacle information according to topological information of hierarchical panel data structure of a large-scale integrated circuit to be analyzed; generating a multi-dimensional overlapping cost quantization model based on an overlapping area calculation rule and the topological model; constructing a decision variable matrix, and converting the decision variable matrix into a pseudo Boolean optimization constraint matrix by setting a constraint condition; generating a global approximate optimal solution sequence based on an initial solution of the pseudo Boolean optimization constraint matrix and the multi-dimensional overlapping cost quantization model; and generating a track layout scheme of the large-scale integrated circuit to be analyzed according to an optimal solution in the global approximate optimal solution sequence to perform track layout. The optimization process of the application can dynamically respond to design rule requirements of different process nodes, and effectively reduces the rule violation risk in the manufacturing stage.

This invention relates to the field of cloud-edge collaborative control technology. It discloses a cloud-edge collaborative system and method for optimizing the energy efficiency of air compressor stations. The system includes a cloud platform that uses historical gas consumption data and external environmental information to determine gas consumption disturbance factors, corrects a preset load baseline curve to generate a gas consumption load prediction curve, acquires real-time operating data of the air compressor, extracts unit performance drift characteristics, dynamically updates a preset air compressor power consumption model to form a real-time power consumption characteristic space, constructs an initial constraint matrix for the unit's start-up and shutdown states based on these data, and solves it using mixed-integer nonlinear programming to obtain a preliminary start-up and shutdown combination strategy. This strategy is mapped to an initial particle state space of a particle swarm. The system iteratively updates the initial particle state space to determine a globally optimized start-up and shutdown combination strategy for the unit. This globally optimized start-up and shutdown combination strategy is then sent to the edge controller, enabling start-up and shutdown to adapt to fluctuations and drifts in load, reducing surge response, and improving operational stability.

This invention provides a transmission precoding design method and apparatus integrating communication and sensing, relating to the field of communication technology. The method includes: modeling user channel vectors based on the Ricean channel model; constructing a communication signal model by combining the configuration parameters with the transmission precoding matrix to be optimized; discretizing the user's uncertain angle interval into multiple angle sampling points based on the communication signal model and calculating the received signal to construct a target echo signal model; deriving sensing performance indicators based on the target echo signal model and the mean square error of the multiple signal classification algorithm, and constructing a non-convex constraint optimization model; performing semi-definite relaxation on the non-convex constraint optimization model and transforming it for solution to obtain a semi-definite constraint matrix; performing eigenvalue decomposition on the semi-definite constraint matrix, and obtaining the optimized transmission precoding matrix by verifying the largest eigenvalue. This invention solves the problems of inaccurate known user angles and degraded target angle estimation accuracy.

This application relates to the field of industrial automation control technology and discloses an intelligent program factory system for wastewater reuse. The system includes a syntax tree generation module, a constraint matrix construction module, a violation early warning module, an algorithm injection module, and a code compilation module. This system transforms discrete control logic into an initial abstract syntax tree and injects metadata semantic tags; it constructs a multi-physics coupling constraint matrix to set a lower bound threshold for the biochemical reaction residence time; it extracts extreme parameters and maps them to extreme transient flow rates; when the extreme biochemical reaction residence time is less than the lower bound threshold, it outputs a violation early warning object; driven by the early warning object, it locates nodes in the initial abstract syntax tree and superimposes control subtrees to generate a target abstract syntax tree; finally, it performs verification and compiles the code into a source file for output. This invention identifies the risk of biochemical residence time escape before program compilation and dynamically injects a compensation algorithm, reducing the risk of substandard water quality and improving the reliability of the underlying control logic.

This invention discloses a method for modeling and topology verification of power compartment disassembly and assembly processes based on a multi-source constraint matrix, relating to the field of special vehicle maintenance and assembly process modeling technology. The method includes: constructing a component connection graph model based on graph theory to describe the assembly structure of the power compartment system; extracting multi-source constraint information from the component connection graph model and fusing it into a multi-source process constraint matrix; generating a candidate set of disassembly and assembly sequences containing multiple potential candidate sequences by initially sorting the disassembly and assembly order of each component in the power compartment system; performing recursive topology verification and closed-loop constraint deadlock detection on the candidate set of disassembly and assembly sequences; and selecting the optimal candidate disassembly and assembly sequence from the detected candidate set. This invention solves the problems in existing technologies regarding the reliance on manual experience for disassembly and assembly sequence planning, lack of unified modeling of structural and spatial constraints, and insufficient handling of closed-loop dependencies and symmetrical components in power compartment disassembly and assembly operations.