641 results about "Topological optimization" patented technology

The invention provides a self-adaptive network topology dynamic reconstruction method and system based on deep reinforcement learning, and relates to the technical field of deep reinforcement learning, and the method comprises the steps: obtaining the topology state information, service flow distribution information and historical reconstruction records of a current network; extracting topological correlation characteristics among nodes through graph convolution operation, and generating fusion state representation in combination with service flow information; inputting the fusion state representation into a deep reinforcement learning model to identify bottleneck nodes and redundant links, and outputting a reconstruction action candidate set; searching and evaluating the long-term cumulative income of the candidate actions through a Monte Carlo tree, and screening an optimal reconstruction action sequence; a graph coloring algorithm is utilized to allocate time slots and process resource conflicts, and a resource-feasible topology adjustment scheme is generated; and extracting a network evolution rule through tensor decomposition, and constructing a topological optimization association mapping graph. According to the method, the network bottleneck can be intelligently identified, the network topology structure is dynamically optimized, and the network performance and the resource utilization rate are effectively improved.

The invention discloses an automatic river network grading and river topological relation identification method based on a graph theory, and relates to the technical field of hydrological geographic information. The method comprises the following steps: acquiring and cleaning a vector river network, a key point location and DEM data of a target drainage basin; constructing an initial river network graph model based on the line element connection relationship; integrating DEM topographic evidence and graph theory connection features, constructing and solving a global potential energy field equation containing topographic driving and boundary constraint, and calculating flow potential energy attributes of nodes of the whole network to determine a flow relationship; based on the flow direction relation, identifying topology abnormal structures such as strong connectivity components in the network, and performing ring breaking processing by using direction confidence to generate a ring-free directed network structure; and performing river grade division based on a topology transfer rule, and associating the key point location to a river network skeleton. According to the method, through global potential energy field solving and topological optimization, the problems that the flow direction of the plain micro-geomorphic area is difficult to recognize and complex loops cannot be graded are solved, and automatic construction of the river network topology is achieved.

The invention relates to a network topology dynamic optimization method and equipment for large-scale power supply and distribution equipment networking. The method comprises the following steps: step S101, real-time data acquisition and state sensing; step S102, carrying out network topology modeling and performance evaluation; step S103, dynamic risk assessment and optimization target generation; s104, carrying out topological optimization decision making based on a feasibility maintenance type genetic algorithm; step S105, carrying out optimal strategy verification and seamless switching; selecting an optimal network topology reconstruction scheme from the Pareto optimal solution set according to a preset decision strategy; and after the reconstruction scheme is verified on a control level, generating an equipment cascade and open circuit control instruction sequence, and guiding related nodes to complete undisturbed switching of the network topology in a preset time window through a distributed cooperative control mechanism. According to the method, generation of invalid solutions can be avoided, and the convergence efficiency of a large-scale network topology optimization algorithm is remarkably improved.

The invention belongs to the field of router protection, and particularly provides an energy router protection system and method based on deep reinforcement learning and virtual impedance collaboration, and the method comprises the steps that a high-speed sensing and monitoring unit collects and preprocesses the data of each power branch; the main control unit operates deep Q network fault reasoning, and a fault criterion threshold value is finely adjusted in combination with online Q-learning; calling a virtual impedance injection module, and superposing compensation voltage on the PWM reference signal to realize injection; a topology self-reconfiguration module is triggered synchronously, a fault branch is isolated, and a standby branch is switched to maintain power supply of a key load; the thermal management regulation and control module deploys load shedding through PID load shedding control and a temperature-current permission curve based on the thermal RC equivalent model and the real-time temperature; and synchronously issuing a related instruction by means of the CAN-FD bus. According to the method, the deep reinforcement learning algorithm and the virtual impedance technology are combined, so that adaptive protection and topological optimization of the energy router under complex working conditions are realized.

The invention discloses an automobile chassis lightweight structure design method based on topological optimization, and relates to the technical field of lightweight design. Constructing a macro-micro coupling model, and simulating and quantifying material parameter fluctuation by using Monte Carlo; establishing a rigid-flexible coupling multi-body dynamic model, simulating working conditions such as braking and turning, and generating a load spectrum by using a rain flow counting method; constructing a multi-objective function containing light weight, rigidity and modality, and solving manufacturing constraints such as pattern draft and the like by using an NSGA-II (Non-dominated Sorting Genetic Algorithm-II) algorithm; dividing steel, aluminum and carbon fiber material domains; and fusing bench test data to correct the model. According to the method, multi-scale collaborative optimization is realized, dynamic loads are accurately mapped, and light weight and performance are balanced; the connection reliability is improved through the multi-material gradient design; manufacturability is ensured through feature recognition and process verification; the batch consistency is guaranteed by digital twinning and robustness optimization; the chassis design efficiency and quality are integrally improved, and the service life is prolonged.

The invention relates to a radial frequency-doubled sound filtering metamaterial and a topological optimization design method thereof.The radial frequency-doubled sound filtering metamaterial comprises scatterers which are arranged on a base body and distributed in a concentric circle mode, and the topological optimization design method comprises the following steps that a two-dimensional axial symmetry model is established, the two-dimensional axisymmetric model corresponds to the cross section of the radial frequency-doubled sound filtering metamaterial in the radius direction and comprises periodically arranged unit structures, and each unit structure comprises a main board and a square design domain; a Floquet periodic boundary condition is applied to parallel boundaries of a unit structure in the radius direction, other boundaries are set as free boundaries, a genetic algorithm is adopted to carry out iterative optimization on the material distribution topology of a square design domain, the optimal material distribution topology of the square design domain is obtained, and then the final optimized shape of the radial double-frequency sound filtering metamaterial is obtained. Compared with the prior art, the invention has the advantages of capability of realizing omni-directional sound wave frequency doubling filtering, high design reliability and the like.

The invention discloses a graph mapping method based on precise synthesis, and the method comprises the steps: constructing a precise synthesis structure library based on NPN equivalence classes, and inputting the precise synthesis structure library into a Boolean network; k-Cut cutting enumeration is carried out on the input Boolean network, a truth table is calculated, cutting is matched with a structure in a precise comprehensive structure library through Boolean matching, and rapid search is realized in combination with NPN classification; the overlay network is generated through multi-round mapping optimization, logic sharing nodes are mined in combination with structural hash, and the multi-round mapping optimization comprises delay-oriented mapping, global area topological optimization and local accurate area optimization; and a new target network is generated based on the optimized overlay network, redundant nodes are removed, and final network construction is completed. According to the method, manual intervention is not needed through full-process automatic mapping and a redundancy removal mechanism, the labor cost of a technical mapping link in chip design is remarkably reduced, and the method is particularly suitable for efficient design of complex circuits and emerging majority of logic base technologies.

The invention provides an offshore wind plant current collection network topology optimization method based on an improved grey wolf optimization algorithm, and the method comprises the steps: S1, obtaining basic data of an offshore wind plant, initializing the grey wolf algorithm, and generating an initial solution set; s2, adopting polar coordinates and a minimum spanning tree to optimize and expand the initial solution set; s3, optimizing a connection mode in each group; s4, executing the optimal connection of each group of fan combination; s5, performing optimal solution set exploration on the grey wolf algorithm by adopting an operator; s6, repeatedly executing until a preset maximum number of iterations is reached, and generating a topology model of the current collection system of the offshore wind plant; the method can improve the initial solution quality and the convergence efficiency, gives consideration to the global search capability and the local optimization precision, and achieves the quick and effective processing of geometric constraints.

The invention discloses a contact force field-based topological optimization design method for a detachable steel structure beam-column joint reinforcing member, which comprises the following steps of: (a) establishing an integral joint finite element model, defining a frictional contact relationship and carrying out nonlinear static analysis; (b) extracting node counter-force components on all contact surfaces and taking the node counter-force components as equivalent loads acting on a reinforcing component; (c) establishing a reinforcing member independent optimization model, applying an equivalent load and defining an inertia release boundary; (d) setting a design variable, a constraint condition and a target function of topological optimization, and solving; and (e) carrying out geometric reconstruction and performance verification on an optimization result. According to the method, a complex contact nonlinear problem is converted into a determined load boundary condition, an inertia release method is utilized to deal with a constraint problem in optimization ingeniously, an optimal topology result of the detachable reinforcing component is obtained finally, and the problem of optimization result distortion caused by the uncertain boundary condition is effectively avoided.

The invention relates to the technical field of lattice structure topological optimization, and discloses a multi-scale hybrid lattice structure double-variable topological optimization method, which comprises the steps of defining double variables, including a first design variable as a scaling scale and a second design variable as a relative density; determining a basic unit cell of the hybrid lattice structure and obtaining a corresponding unit cell size, wherein the second design variable is determined based on the unit cell size; obtaining a first filling unit cell and a second filling unit cell; determining a design domain, and filling the first filling unit cells and the second filling unit cells into the design domain by taking the flexibility minimization of the hybrid lattice structure as a target and the volume fraction as a constraint; and optimizing the filling process based on a moving asymptote optimization algorithm so as to carry out topological optimization of the hybrid lattice structure based on double variables, and outputting an optimized multi-scale hybrid lattice structure. According to the industrial bearing structure, higher structural specific stiffness, specific strength and energy absorption efficiency are achieved, and the requirements for light weight, self-adaption and high performance in an existing industrial bearing structure can be met.

The invention discloses a cutterhead structure design method combining topological optimization and finite element analysis, and belongs to the technical field of aerospace high-performance cutting tool design and manufacturing. The technical problems that a traditional cutter head depends on experience design, and rigidity, chip removal and heat stability are difficult to balance are solved. According to the method, a parameterized model is established, multi-working-condition loads including cutting loads, dynamic excitation and thermal-mechanical coupling are defined, a topological optimization technology with multi-working-condition weighted flexibility minimization as a target and a material volume fraction as a constraint is adopted, and a material optimal distribution cloud picture is generated based on a variable density method; geometric reconstruction and engineering semantic interpretation are carried out on an optimization result, and a material enrichment region is converted into engineering characteristics such as an internal reinforcing rib and a variable spiral transition structure, so that a lightweight high-performance conceptual model is formed; finally, through multi-working-condition finite element verification and manufacturing manufacturability analysis, a final design scheme meeting the requirements for strength, rigidity, dynamic characteristics and thermal stability is obtained through iteration.

The invention belongs to the technical field of advanced manufacturing and intelligent design, and provides a topological optimization method and system for a liquid cooling plate of a lithium ion battery pack, and the method comprises the steps: building a parameterized simulation model of a battery pack liquid cooling system, constructing a multi-dimensional design variable space of the liquid cooling plate, and formally defining a multi-objective optimization problem; on the basis of the initial training data set, independently constructing a probabilistic agent model capable of predicting a target value and quantifying uncertainty for each optimization target function; performing quantum behavior enhanced multi-universe optimizer iterative optimization on the constructed agent model, selecting new sample points from a multi-dimensional design variable space of the liquid cooling plate according to a set criterion after a set number of iterations is completed, performing high-fidelity CFD simulation to obtain real data, supplementing the real data to a data set, and updating or reconstructing the agent model; and judging whether an iterative optimization condition is met or not, and if so, screening and outputting a final Pareto optimal solution set from all samples subjected to high-fidelity simulation verification. And efficient multi-objective optimal design of the liquid cooling plate is realized.

The invention relates to the technical field of building construction, in particular to a BIM (Building Information Modeling) forward design method based on full-process AI (Artificial Intelligence) driving, which comprises the following steps of: digitizing a demand, and extracting a quantitative design index through a multi-modal demand analysis module; parameter generation: generating and evaluating a first-order BIM seed model by using an AI parameter generation engine driven by a generative adversarial network; iterative optimization is carried out, and automatic form, performance and layout optimization is carried out on the model through topological optimization, energy consumption prediction and reinforcement learning; performing collaborative verification, and generating collaborative correction suggestions by adopting a conflict detection algorithm fusing a boundary box and a GJK algorithm; and result delivery: performing simulation verification through a digital twin engine and outputting a final result. According to the method, intelligence and automation of the whole process from demand to delivery are achieved, the problems that a traditional method depends on manpower, collaboration lags behind, performance analysis and design are disjointed and the like are solved, and the design efficiency, quality and scientificity are remarkably improved.

The invention discloses a low-altitude economic intelligent scheduling method based on multi-dimensional data fusion and dynamic topological optimization, and belongs to the technical field of aircraft air traffic control, and the method comprises the following steps: S1, collecting and fusing multi-dimensional data, including meteorological data, equipment data, airspace data, task data and historical data, S2, constructing a dynamic airspace topological network based on the fused data, the topology network comprises a vertex set and an edge set, vertexes represent unmanned aerial vehicles, and edges represent cooperative paths between the unmanned aerial vehicles, S3, generating a global optimal scheduling strategy through a multi-objective optimization algorithm according to the dynamic airspace topology network, S4, executing the global optimal scheduling strategy, updating historical data and model parameters after a task is completed, and S5, executing the global optimal scheduling strategy according to the updated historical data and model parameters. And closed-loop feedback is formed. Multi-target dynamic balance of unmanned aerial vehicle dispatching safety, efficiency and energy consumption is achieved through multi-dimensional data fusion and dynamic topological optimization, the system supports full-process closed-loop automation, and the accident rate and resource consumption are remarkably reduced.

The invention discloses a mining area information three-dimensional perspective model construction method and device, equipment, equipment and a medium, and relates to the technical field of modeling. The method comprises the steps of performing data fusion and voxel filling on multi-source mining area geological data, constructing an initial model according to the data fusion and voxel filling, and performing topological structure optimization; performing surface topology and texture mapping on the model based on a mining area remote sensing image to obtain mining area ground feature distribution transmission data and superposing the data into the model; performing density distribution and density mutation recognition on the model according to the gravity exploration data of the mining area to obtain density distribution transmission data of the mining area, and superposing the density distribution transmission data into the model; resource prediction is carried out based on mining area ground feature / density distribution transmission data; threshold screening is carried out on the topological optimization model based on the prediction result, and then the topological optimization model is superposed into the model; performing deep source focusing processing on the mining area resource area data to obtain deep source focusing area data, and superposing the deep source focusing area data into the model; and carrying out resource visualization on the model to obtain a mining area information three-dimensional perspective model. According to the invention, multi-dimensional fine expression of mining area information can be realized.

The invention relates to the technical field of battery thermal management, in particular to a topological optimization structure cold plate of a battery non-uniform heat source, a design method and a battery pack. The specific design method comprises the following steps: establishing a battery non-uniform heat source model and a cold plate structure two-dimensional model; taking heat exchange uniformity, heat exchange efficiency and flow energy dissipation as objective functions, carrying out flow channel topological optimization, and establishing a three-dimensional topological optimization flow channel model; establishing a battery pack packaging model; and carrying out CFD simulation calculation, and obtaining the topological optimization cold plate structure by adjusting the weight ratio of heat exchange uniformity, heat exchange efficiency and flow energy dissipation until the battery pack packaging model meets a preset condition. The method comprises the following steps: constructing a model of a non-uniform heat source of a battery fixed object; a topological optimization structure design method is used for designing a battery pack cold plate to constrain the highest temperature rise and the temperature difference; the problems that according to an existing cold plate design method, the battery temperature is inconsistent, and certain errors exist in the actual application process are solved.

The invention discloses a multi-machine multi-card distributed training optimization system and method oriented to a credential heterogeneous environment, and relates to the technical field of distributed training. In order to solve the defects existing in distributed training in a credential and credential heterogeneous environment, the system comprises an application layer for receiving a training task; the core system layer comprises a self-adaptive task scheduling module, a hybrid communication topological optimization module and a dynamic check point and elastic recovery control module, and the scheduling module generates a performance portrait and an optimal scheme based on a training task and adjusts the scheme according to a node fault; the optimization module executes the scheme, firstly detects node topology, constructs a hierarchical path, loads and initializes an optimal communication rear end for target equipment, and synchronizes the path to the target equipment; the control module periodically stores a complete training context and realizes reliable recovery of a training process; the credential hardware abstraction layer is used for providing a uniform interface for realizing underlying resource access and data acquisition; and the hardware resource layer comprises heterogeneous computing nodes and an RoCE network switch.

The invention discloses a topological network global optimization method based on graph reinforcement learning, and relates to the field of computational geometry and grid optimizing.The method comprises the steps that a topological optimization process is modeled into a Markov decision process, a topological network containing singular points and angular points is converted into heterogeneous graph representation, and a graph state is constructed; selecting a topology editing action by a reinforcement learning agent fused with the graph neural network based on the current graph state; after executing the action, updating a topological structure and a graph state, and calculating an instant reward based on the global grid quality index change; training intelligent agents in batches through experience playback and time sequence differential learning, so that the intelligent agents learn a mapping strategy from a graph state to an optimal action; and applying the trained policy network deployment to automatic optimization of the new topology. According to the method, full-process automation of topological optimization is achieved, non-local negative effects of local modification are effectively avoided, a global optimal optimization strategy is learned, the grid quality and optimization efficiency are remarkably improved, and the method is suitable for simulation grid generation of aircrafts.

The invention provides a liquid cooling plate flow channel design optimization method and device based on topological optimization and a liquid cooling plate, and relates to the technical field of thermal management, and the method comprises the steps: S1, determining the geometric parameters of the liquid cooling plate according to the size of a battery module, constructing a double-layer two-dimensional design domain, and setting material, heat source and boundary conditions; s2, a topological optimization algorithm is adopted, material distribution is represented with a relative density variable, a multi-objective function giving consideration to the maximum heat exchange amount and the minimum pressure drop is constructed, a clear fluid-solid interface is obtained through density filtering and a projection function, and a target double-layer two-dimensional flow channel contour is obtained through iterative solution under volume fraction constraint; and S3, taking the target double-layer two-dimensional flow channel contour as a cross section to carry out spatial stretching bending deformation, and generating a double-layer special-shaped flow channel structure with a diffusion layer and a collection layer. According to the method, global optimization of two-dimensional topological optimization and three-dimensional geometric reconstruction are fused, the contradiction between the heat dissipation performance and the flow resistance is effectively solved, and a high-performance heat dissipation solution is provided for battery thermal management.

The invention discloses a truss type load-bearing structure time domain dynamics topological optimization method and system based on an intrinsic orthogonal decomposition method, and relates to the technical field of truss type load-bearing structure topological optimization. The method is provided for solving the problems of high calculation power and the like caused by large-scale space-time response iteration of original transient problems and intensive calculation of dual problem sensitivity analysis in the prior art. According to the method, a local geometric control strategy for the cross interference problem of rod piece units is introduced, and a transient dynamics full-order topological optimization model of the truss structure is established through an equal geometric stiffness diffusion method. Based on an intrinsic orthogonal decomposition method, a transient dynamics reduced-order model of a truss structure is constructed, a reduced-order model base is updated in real time through an incremental singular value decomposition method, and then efficient solving of a transient dynamics equation and an adjoint equation in sensitivity analysis is achieved. And updating an iterative design variable by adopting a penalty function method, and seeking the optimal layout design of the truss structure. The invention provides a time-domain dynamics topological optimization method of the truss type load-bearing structure based on an intrinsic orthogonal decomposition method, and the method can be used for efficiently solving the dynamics layout optimization problem of the truss structure under the action of a transient load.

The invention belongs to the technical field of aero-engines, and particularly relates to a design method of an air inlet casing thin-wall reinforced structure based on rigidity requirements. The invention relates to a design method of a thin-wall reinforced structure of an air inlet casing based on a rigidity requirement. Comprising the following steps of model establishment, parameter setting, load and boundary determination, topological optimization mathematical model establishment, topological optimization calculation, model reconstruction, structural strength evaluation, manufacturability evaluation and preparation, and preparation of the air inlet casing by adopting a selective laser melting additive manufacturing technology. According to the design method for the thin-wall reinforced structure of the air inlet casing based on the rigidity requirement, the topological optimization structure design method and the additive manufacturing technology are combined, the material utilization rate and the specific rigidity of the air inlet casing are greatly improved, and the light weight level of the whole machine is remarkably improved.

The invention discloses a water supply pipe network dynamic pressure control method and system based on multi-parameter fusion, and relates to the technical field of water supply pipe network control, and the method comprises the steps: carrying out the standardization processing and topological optimization of pipe network geographic information system data, and constructing an urban pipe network topological graph; identifying a pressure sensitive node and a distance sensitive node based on a hydraulic calculation result of the mechanism calculation model; performing association coding on historical monitoring data of the key nodes and a topological connection relationship, and training a machine learning model fusing pipe network topological constraints; collecting real-time monitoring data, inputting the real-time monitoring data into the mechanism calculation model and the machine learning model, and respectively obtaining offline adjustment parameters and online adjustment parameters; and determining a final adjusting instruction through consistency verification to control water supply pump set equipment. According to the method, the calculation precision of the mechanism model and the response speed of the machine learning model are fused, organic unification of accuracy and real-time performance is achieved, and the control stability and reliability under the abnormal working condition are improved.

The invention discloses a BIM (Building Information Modeling)-based curtain wall standardized design method, and relates to the technical field of building curtain wall design, and the method comprises the following specific steps: realizing curtain wall intelligent design through five steps: S1, building an association constraint database and a dynamic matching module; s2, an algorithm is embedded, and a topological structure is generated; s3, reversely optimizing the process, and feeding back adjustment parameters; s4, intelligently arbitrating standard conflicts to ensure compliance; s5, constructing a digital twinborn body, collecting operation data to feed back the design, forming a full-life-cycle intelligent closed loop, and improving the design efficiency and quality; according to the method, precise adaptation of the curtain wall and the building main body is realized through main body constraint dynamic matching and AI topological optimization; the contradiction between design and construction is reduced through process reverse optimization, and the compliance is ensured through standard conflict arbitration; meanwhile, a digital twinborn feedback closed loop breaks through an information barrier, collects operation data in real time, optimizes a feedback design, and pushes curtain wall design to develop towards the intelligent direction of data driving and continuous iteration.

The invention belongs to the technical field related to structure optimization design, and discloses a topological optimization method and device for a metamaterial microstructure capable of bearing a band gap, and the method comprises the steps: (1) respectively defining an interpolation penalty coefficient of a Young modulus for the homogenization analysis of the microstructure and the band gap problem of an energy band structure according to the performance analysis of the microstructure, calculating an interpolation penalty coefficient of the mass density; (2) carrying out homogenization analysis of the microstructure based on dynamics to obtain equivalent physical property parameters and determine equivalent material modulus; (3) defining an irreducible first Brillouin region wave vector path of the microstructure based on the geometric symmetry constraint of the microstructure, and further calculating a band gap quality factor between adjacent energy band curves of the microstructure; and (4) establishing a topological optimization model which takes the equivalent modulus as a grading constraint and takes band gap quality factor maximization as a target, and performing iterative optimization based on the topological optimization model to obtain an optimal microstructure configuration. According to the invention, efficient and stable design of the microstructure is realized.

The invention discloses an aerated building block geometric dimension intelligent detection method based on three-dimensional point cloud reconstruction, and the method comprises the steps: collecting and processing multi-view point cloud data, and generating a complete point cloud data set covering six surfaces; executing self-reference calibration based on hexahedron features, and generating a standardized point cloud data set; inputting the multi-modal input into an improved SegFormer model, extracting geometric features and calculating a variance; executing weighted segmentation and topological optimization based on the geometric features, and outputting geometric parameter data; calculating the geometric dimension of the aerated building block, and combining the spatial covariance to generate a precision calibration result; and fusing variance information to establish a space-time coupling judgment mechanism, and outputting a detection report and a detection result. According to the method, through fusion of improved SegFormer dynamic geometric semantic modeling, geometric entropy driving topology correction and a space-time coupling tolerance judgment mechanism, high-precision three-dimensional point cloud reconstruction and intelligent geometric dimension detection of the complex surface of the aerated building block are realized.

The invention provides a construction method of an ultrahigh-field MRI local shim coil based on topological optimization, and relates to the field of magnetic resonance imaging. The construction method provided by the invention comprises the following steps: step 1) selecting a target area needing to be subjected to magnetic field compensation, and obtaining a target magnetic field required by compensation of the target area; 2) representing current distribution by adopting a flow function, and obtaining magnetic field distribution generated by the current distribution; 3) taking the target magnetic field as a target, continuously iteratively optimizing the magnetic field distribution to approach the target magnetic field, and obtaining optimized current magnetic field distribution; and 4) winding a coil on a current-carrying surface by taking a current function corresponding to the optimized current magnetic field distribution as a reference. On the basis of a target field point method, a preset magnetic field compensation target is taken as a starting point, continuity and physical consistency of current distribution are ensured through flow function constraint, and regional specificity shimming compensation is realized by adopting a multi-current-carrying-surface topological optimization strategy.

The invention discloses a manufacturing method for preventing a single-board guitar panel from recessing, and relates to the technical field of manufacturing for preventing the single-board guitar panel from recessing, and the method comprises the steps: carrying out the finite element stress simulation of a three-dimensional digital model of the single-board guitar panel, and determining a high-stress region in a stress state; according to the distribution characteristics of the high-stress area, generating a structure model of the bionic support network through topological optimization; preparing a lightweight support net with a bionic structure by adopting an additive manufacturing process based on the structure model; the method comprises the following steps: placing a to-be-processed veneer panel on a rigid mold with a preset curved surface, and carrying out plastic pre-deformation on the to-be-processed veneer panel under the action of vacuum negative pressure to obtain a pre-formed panel; a lightweight supporting net is fixed to a high-stress area on the inner side of the preformed panel; the modularized metal framework with preloaded stress is installed at a preset position in the guitar body to form a reverse acting force system which resists the downward sinking of the panel; and carrying out integral curing treatment on the guitar body provided with the supporting net and the metal framework to complete integrated manufacturing.

The invention discloses a wiring diagram recognition method and device based on deep learning and electronic equipment, and the method comprises the steps: carrying out the correction and mask processing of an initial wiring diagram, obtaining a first wiring diagram, and fusing mask parameters and mask skeleton parameters; extracting circuit elements in the first wiring diagram based on fusion mask parameters and mask skeleton parameters, and classifying the circuit elements to obtain a first element set of the first wiring diagram; performing port connection line pairing processing and topological optimization processing on the first element set, and determining a second element set and a corresponding second wiring diagram; according to the second element set, performing multi-dimensional verification and global topological structuring processing on the second wiring diagram to obtain a topological graph data model; and determining a JSON file, a visual topological graph, a VF2 check report and a Neo4j graph database of the wiring diagram according to the structured data in the topological graph data model. According to the invention, a more accurate wiring diagram can be identified.

The invention relates to a BIM digital building operation management technology, and discloses a space splitting and merging method and system based on BIM vector modeling data, and the method comprises the steps: obtaining vector data of a target room model, obtaining a preliminary disassembly range drawn by a user and a target area input by the user, and obtaining a target area; and performing dynamic iterative optimization on the initial disassembly range based on a difference value between an intersection area of the initial disassembly range and the vector data and the target area to obtain a final disassembly range, and performing disassembly operation on the vector data by using the final disassembly range to obtain a spatial graph set. And according to the division results of the overlapping regions and the non-overlapping regions between the spatial graphs in the spatial graph set, performing merging processing on the spatial graphs in the spatial graph set to obtain a merging result, and performing topological optimization on the merging result to obtain an optimized merging result. According to the method, the efficiency and precision of space splitting and merging in the BIM model can be improved.

The invention relates to the technical field of radiator design and thermal management, in particular to a radiator cooling channel design method based on three-dimensional topological optimization. The method comprises the following steps: carrying out thermal imaging scanning on the electronic equipment, obtaining temperature distribution data, and generating a hotspot map; calculating a temperature gradient according to the hot spot map, determining a temperature gradient threshold value, dividing a main circulation area and a secondary circulation area, performing circulation area boundary smooth optimization, and generating a circulation partition map; based on the cyclic partition map, determining an inlet position and a heat flow demand, and identifying a thermal anchor point set; determining a hierarchical branch structure of a primary loop and a cellular network structure of a secondary loop; generating a channel skeleton graph based on the hierarchical branch structure and the cellular network structure; and a basic isolation wall is determined, a reinforcing structure is added, and thickness optimization is conducted according to the local temperature difference to form a heat conduction valve structure. According to the invention, the problem of low efficiency of the radiator under a complex thermal load is solved through radiator design and a thermal management technology.