750 results about "Mesh node" patented technology

The invention discloses an environment modeling method and system for realizing intelligent security and protection, and relates to the technical field of intelligent security and protection, and the method comprises the steps: collecting a visual image and depth data of a monitoring region, and generating a monitoring scene feature matrix; performing hierarchical feature extraction on the monitoring scene feature matrix by using a deep convolutional neural network, and constructing a scene semantic feature map; projecting the scene semantic feature map to a three-dimensional monitoring space according to the depth data, and constructing a three-dimensional scene grid model; extracting spatial topological characteristics of each grid node in the three-dimensional scene grid model, and calculating association weights among the grid nodes; and constructing a scene dynamic knowledge graph based on the spatial topological features and the associated weights, and carrying out modeling analysis on abnormal events. According to the method, through cooperative collection of the multi-view vision sensor and the depth sensor, in combination with information entropy weighted standardization and principal component analysis, accurate generation of the monitoring scene feature matrix is realized, and the problems of information redundancy and feature coupling in traditional vision data processing are effectively solved.

The invention relates to a transformer multi-physics field coupling numerical simulation method and device and a storage medium. The method comprises the following steps: performing coupling calculation on a target working condition by using an electromagnetic, heat, flow and force coupling calculation model of a transformer to obtain transformer loss data and temperature rise data; mapping the temperature rise data to a transformer electromagnetic and force coupling calculation model by using a grid node data mapping method to serve as an initial value, and performing coupling calculation on a target working condition to obtain dynamic data of an internal structural member of the transformer; performing fast Fourier transform on the dynamic data in a preset frequency range to obtain dynamic data under each frequency; and mapping the temperature rise data and the dynamic data under each frequency to a transformer sound and force coupling calculation model as initial values, and carrying out coupling calculation on a target working condition to obtain transformer oil tank vibration and external noise data. Compared with the prior art, the method has the advantages that the calculation amount is effectively reduced, and the accuracy of predicting the internal state of the transformer is improved.

The invention discloses an algae biomass prediction method based on a bidirectional coupling hydrodynamic model and a physical information neural network, and relates to the field of algae biomass prediction.The algae biomass prediction method comprises the steps that firstly, water regimen data, water quality data and meteorological data are obtained and preprocessed, and then a hydrodynamic model based on a shallow water equation set is constructed; the model is coupled with a convection-diffusion equation and a wind stress-turbulence model so as to simulate spatial distribution of nutritive salt concentration, water temperature distribution and a vertical and horizontal mixing process driven by wind power; operating the model based on a time sequence of meteorological and water regimen data, and outputting multi-dimensional physical field data; thirdly, performing spatial interpolation on the water quality data to enable the water quality data to be in space-time alignment with grid nodes of the hydrodynamic model; a target loss function is constructed by taking a residual error in the shallow water equation set as a regular term, and a physical information neural network is trained to finally obtain a target prediction model; and the accuracy of algae biomass prediction and the robustness of the target prediction model are obviously improved.

The invention provides a tunnel deformation parameter inversion method and device based on distributed optical fibers, and relates to the technical field of tunnel deformation parameter inversion, and the method specifically comprises the steps: selecting a monitoring point in a tunnel, arranging an optical fiber sensor, and obtaining a Brillouin scattering signal generated by the optical fiber sensor under the stress effect of the corresponding monitoring point; extracting a Brillouin frequency shift corresponding to the monitoring point, and determining an environmental effect frequency shift correction value by using the temperature change data, the humidity change data and the service time of the optical fiber sensor; determining the structural strain of the monitoring point according to the Brillouin frequency shift and the environmental effect frequency shift correction value, generating a three-dimensional strain field cloud picture, performing spatial registration on the three-dimensional strain field cloud picture and the geometric topology of the model, and performing three-dimensional grid division; the structure strain of the monitoring point is mapped to the grid node at the corresponding position, the structure strain of other grid nodes is determined based on the space distance attenuation law, inversion of the whole tunnel deformation parameters is completed, and the tunnel deformation monitoring precision and efficiency are improved.

The invention relates to the technical field of equipment intelligent diagnosis, in particular to a generator digital twinning diagnosis method based on temperature field online simulation, which comprises the following steps: respectively constructing a three-dimensional virtual model, a temperature field simulation model and an intelligent agent diagnosis model; the digital twin is in data connection with the physical entity; data alignment is achieved through a unified space-time coordinate system, a mapping relation is established between a vertex of the three-dimensional virtual model and a grid node in the temperature field simulation model, and a fault probability matrix output by the intelligent agent diagnosis model is matched to a three-dimensional grid of the three-dimensional virtual model through spatial interpolation; according to a fault probability output by the intelligent agent diagnosis model, correcting a boundary condition of the temperature field simulation model, triggering local grid adaptive encryption of the temperature field simulation model, and marking a fault position in real time through a three-dimensional virtual model; and the simulation result of the temperature field simulation model verifies the fault probability output by the intelligent agent diagnosis model. Through the method, the fault identification accuracy can be effectively improved.

The invention relates to the technical field of cold-chain medicine transportation, in particular to an intelligent monitoring and early warning system for a cold-chain medicine transportation environment. Comprising a multi-source heterogeneous data acquisition module, a time-space synchronization data fusion module, a three-dimensional thermodynamic distribution modeling module, a drug property degradation risk assessment module, a dynamic grading early warning module and a path self-optimization execution module, the multi-source heterogeneous data acquisition module is used for generating multi-source heterogeneous data; the space-time synchronization data fusion module generates an environment parameter matrix; the three-dimensional thermodynamic distribution modeling module calculates an equivalent thermal load value of each grid node; the drug property degradation risk assessment module predicts residual effective time; the dynamic grading early warning module generates a dynamic early warning signal; and the path self-optimization execution module generates optimized transportation path parameters. According to the invention, the medicine is prevented from losing efficacy due to environment change, and meanwhile, the response speed of cold-chain transportation and the medicine quality guarantee are improved.

The invention discloses a penetration discrimination method and system suitable for a double-layer dam foundation, and the method comprises the steps: S1, obtaining the geological parameters of a double-layer dam, and forming a geological parameter set; s2, constructing a seepage numerical model of the double-layer dam foundation, simulating the seepage field distribution condition of the double-layer dam foundation at each grid node, and obtaining seepage field data; s3, grid node seepage force is calculated, and a potential seepage failure area is determined; s4, monitoring pore water pressure and seepage flow changes of the preset monitoring points in the potential seepage failure area; s5, constructing a seepage failure judgment model, and outputting a seepage judgment result; and S6, performing grading processing according to the judgment result of seepage failure, and outputting grade seepage early warning information through a seepage grading model. According to the method, judgment, real-time monitoring and graded early warning of seepage damage of the double-layer dam foundation are achieved, and the safety of the heterogeneous double-layer dam is guaranteed.

The invention discloses a current inversion method based on a magnetic sensor array, and the method comprises the steps: S1, setting a plurality of measurement points, uniformly dividing a conductor layout region in a to-be-measured part of a to-be-measured multi-conductor system into grids with M * N nodes, and numbering each grid node as (i, j); constructing a coordinate system and recording coordinates of all grid nodes; s2, establishing a finite element simulation calculation model, calculating a reference position coefficient matrix of all measurement points, and constructing a reference position coefficient matrix database; s3, calculating a conductor position coefficient matrix, and constructing a position coefficient matrix; s4, according to the magnetic field measurement value acquired by the magnetic sensor array, the conductor current is calculated through inversion; and S5, after resampling the magnetic field measurement value, substituting the updated measurement value and the position coefficient matrix stored in the step S4 into the linear equation set constructed in the step S4 to solve the current of each conductor. The method has the characteristics of rapid calculation and low operand while the accuracy is ensured, and the inversion calculation efficiency can be improved.

The invention discloses a transformer substation inspection method and system based on a quadruped robot, and relates to the technical field of transformer substation inspection, and the method comprises the steps: collecting topographic data and temperature data based on the quadruped robot, planning an inspection path, and carrying out the temperature monitoring; collecting sound data based on the quadruped robot, calculating a sound source direction angle, extracting a time-frequency feature and determining a feature fluctuation amplitude; constructing a sound field model based on the characteristic fluctuation amplitude, generating a simulated sound pressure distribution diagram, determining a comparison error corresponding to each grid node in the simulated sound pressure distribution diagram based on sound pressure data acquired by the quadruped robot, and determining the grid nodes with the comparison errors greater than or equal to a comparison threshold as abnormal nodes; and giving an alarm according to the abnormal node, recording early warning information, and uploading the early warning information to a cloud end to give an alarm notification. According to the method, acoustic analysis is added, abnormal sound waves or abnormal fluctuation of local noise in the substation equipment is found in time, the early failure of the equipment is effectively detected, and the inspection efficiency is improved.

The invention discloses a rapid calculation method based on a non-coordination and reanalysis theory and a computer device. The invention relates to the technical field of structural design optimization, and solves the problem that it is difficult to realize efficient structural response analysis while ensuring the calculation precision in the prior art. The method comprises the following steps: selecting a structural member of a to-be-calculated structural response and discretizing the structural member; preprocessing the data, and determining a coarse and fine grid index set corresponding to interface fine grid nodes; solving a unit shape function, and embedding the shape function into a body stiffness matrix according to a degree-of-freedom position to serve as an interface constraint condition; calculating a variable element stiffness matrix, and completing the construction of a modified model stiffness matrix; carrying out iterative calculation to obtain a basis vector; and calculating and solving the structural response of the modified model. According to the method, the efficient response analysis of the non-coordinated variable structure is realized on the premise of ensuring the calculation precision.

A method for predicting gas explosion. The method includes: obtaining a geometric model with spatial obstacles; determining a simulation dataset of the gas explosion based on the geometric model, where the simulation dataset is a dataset including process data of multiple gas explosion scenes in the geometric model, and a state vector of a spatial grid node in the simulation dataset includes a first moment, coordinate information and a target pressure value; optimizing, using the simulation dataset, a physics-informed GNN to obtain an optimized physics-informed GNN; and predicting the gas explosion in an obstructed gas explosion scenario using the optimized physics-informed GNN. This method is applied to use optimized physics-informed GNN to realize spatiotemporal second-level prediction of overpressure distribution and explosion wave propagations occurring in the obstructed gas explosion scenario, enhance the accuracy, the reliability and the efficiency of gas explosion prediction in the obstructed gas explosion scenario.

The invention provides a grid quality optimization method, computer equipment, a program product and a storage medium. The method comprises the steps that an initial grid is acquired, the initial grid is converted into a built-in data structure, and a grid object is acquired, wherein the grid object comprises a node set, a tetrahedron set and topological adjacency information; traversing each grid node of the grid object, and adding a constraint condition for each grid node; regarding the discretized three-dimensional grid as a hyperelastic body, and calculating the energy of the current grid for each tetrahedron unit in the grid object through a hyperelastic model; performing iterative calculation on the energy minimum value of the current grid according to the constraint condition, and applying random disturbance after each N iterations until a convergence threshold value or the maximum number of iterations is reached; and the grid corresponding to the minimum energy value is output as the optimal grid. According to the scheme, the overall quality of the grid can be effectively improved, and the boundary retention capability and the restoration capability of the degraded unit are enhanced, so that the simulation quality is improved.

The invention provides an offshore wind power plant regular layout design method based on a boundary adaptive algorithm, and the method comprises the steps: converting the design of a wind turbine arrangement scheme in a planning field into the design of a wind turbine arrangement scheme in a feasible region, and enabling the feasible region to be equal to the planning field, or enabling the feasible region to be a region after the limitation region of the planning field is removed; the outer boundary coincides with the boundary of the planning field area; according to the method, the grid type wind power plant layout capable of completely covering the feasible region is constructed, and on the premise that the number of the grid nodes in the feasible region is equal to the demand quantity of the wind turbines, the grid nodes, located in the feasible region, on the straight line where the unutilized wind turbine rows of the boundary line of the feasible region are located are dynamically adjusted in an equal-interval processing mode; the wind turbines at the two ends of the wind turbine row are located on the boundary of the feasible region, and an offshore wind power plant regular layout design scheme is obtained through repeated iteration optimization. According to the method, a complex scene containing or not containing a restricted area can be obtained, a regular machine arrangement scheme for fully utilizing the field area can be realized, and wind power engineering practice can be better served.

According to the WIFI mesh channel dynamic allocation method and device provided by the invention, the size and position allocation of the RU are intelligently adjusted by monitoring the network flow, the equipment density and the channel interference in real time, so that the channel resource utilization rate is improved; a four-dimensional candidate channel scoring model and a decision engine are adopted for channel allocation and interference prediction, millisecond-level RU dynamic scheduling is achieved, and the low-delay service requirements of AR / VR, 4K videos and the like are met; a global channel state is determined through signaling interaction and collaborative decision among Mesh nodes, and conflicts and performance bottlenecks caused by local optimization are avoided; and a Wi-Fi 6 / 6E / 7 RU flexible division mechanism is supported, different frequency bands and bandwidth configurations are adapted, and efficient access of heterogeneous equipment is ensured. In a word, according to the scheme disclosed by the invention, the problems of static property, low efficiency and interference in RU allocation in the existing WiFi Mesh network are solved, and high-reliability and low-delay intelligent channel resource management is realized through dynamic priority layering, service type adaptation and interference avoidance technologies.

The invention discloses a boundary grid node-oriented shipborne unmanned aerial vehicle delivery scheduling method and system, and relates to the technical field of shipborne unmanned aerial vehicle path optimization, and the method comprises the steps: carrying out the systematic grid division of a boundary region based on a geographic coordinate system and marine environment constraints, and constructing a boundary grid node set; mapping attribution is carried out based on boundary grid nodes, and path feasibility is evaluated; and according to an evaluation result, screening and scheduling candidate tasks, generating a corresponding time window, constructing an optimal path, and completing dynamic scheduling and path planning of multiple tasks through time, space and platform constraint linkage. By constructing a task space mapping structure, an airspace schedulability scoring mechanism and a path multi-dimensional cost evaluation model, dynamic, efficient and safe scheduling of the shipborne unmanned aerial vehicle in a boundary sea area is realized, the task matching precision, the path feasibility and the system robustness are remarkably improved, and the method has high intelligent cooperation capability and environmental adaptability.

The invention discloses a real-time judgment method for roof collapse caused by a fire between nuclear power station oil storage tanks, and relates to the technical field of fire safety design of roof structures between nuclear power station oil storage tanks. Acquiring time sequence temperature data of the grid nodes; establishing a three-dimensional heat conduction model of the roof structure; top plate structure heating surface temperature field mapping is realized; carrying out three-dimensional heat transfer simulation on the top plate structure; analyzing the instability critical condition of the roof structure. According to the real-time judgment method for the roof collapse caused by the fire between the oil storage tanks of the nuclear power station, time sequence temperature field mapping of the heated surface of a complex roof structure between CFD numerical simulation software and FEM software in different fire scenes between the oil storage tanks of the nuclear power station can be realized; real-time structure response behaviors of the nuclear power station oil storage tank roof structure in different fire scenes are simulated, and the method can be used for fire safety design and post-disaster damage evaluation of the nuclear power station oil storage tank roof structure.

The invention relates to the field of three-dimensional scene rendering, in particular to a three-dimensional scene data generation method, an analysis method, rendering equipment and a computer storage medium. According to the method, LOD (Level of Detail) grading processing is performed on three-dimensional scene data, foreground data in the three-dimensional scene data is divided into a plurality of LOD layers, each LOD layer is divided into a plurality of grid nodes, and each grid node is independently stored, so that the data can be loaded as required. Meanwhile, different compression modes are adopted for different data, the GPU can directly analyze and read the compressed data, decompression in a memory is not needed, occupation of the memory and video memory bandwidth is greatly reduced, and rendering efficiency is improved.

The invention relates to a valve health degree monitoring and maintaining method and system based on an electric actuator, and belongs to the technical field of mechanical control and automation. The method comprises the steps that valve maintenance data of the electric actuator are obtained, a position-pressure bimodal grid is constructed based on the valve maintenance data, pressure testing is conducted on a valve, torque-opening curves in the opening and closing processes are analyzed, and valve health degree data are obtained; an electric execution monitoring model is constructed, a valve torque curve is obtained, maintenance information labels are added to grid nodes according to the valve maintenance information through a labeling binding method, and a valve health maintenance scheme is generated; for the pressure test, identifying switching time delay, hysteresis and leakage data in a valve torque profile and an operation log through a curve feature extraction method to obtain a valve scheme optimization strategy; and executing the maintenance scheme optimized by the valve scheme optimization strategy, and automatically outputting the updated valve health maintenance scheme based on a recursive execution feedback method.

The invention belongs to the field of machine tool geometric accuracy design, and particularly discloses a machine tool geometric accuracy analysis optimization method based on dynamic sensitivity, which comprises the following steps: constructing an error transfer model, and determining a target function; selecting an SOBOL method based on the global influence demand for quantifying each error term; selecting a Morris method based on the non-linear influence demand of the evaluation error term range change; dividing the travel of each movement shaft of the machine tool into grid nodes; selecting an error initial value for calculation based on parameter input and an error range, performing sensitivity calculation by using SOBOL, and taking a result as an optimization constraint condition; performing sensitivity calculation by using Morris, and taking a result as an optimization iteration basis; carrying out loop iteration and updating a sensitivity result to guide precision optimization, and carrying out multi-round iterative optimization until iterative convergence to obtain an optimized error term; and traversing grid nodes and carrying out sensitivity normalization in the transverse direction to obtain an optimized error curve in which error terms change along with coordinates. The geometric accuracy of machine tool machining can be improved.

The invention discloses a collision parallel detection method, device and equipment and a storage medium, and relates to the field of multi-body separation numerical simulation, and the method comprises the steps: carrying out the parallel partitioning of a multi-body separation object through the grid node coordinate information of the multi-body separation object determined based on a current simulated grid file, and obtaining a partitioning result; determining the number of target bounding boxes in each region based on the grid geometric information corresponding to each region in the partitioning result, and triggering a bounding box creation operation; after the bounding boxes are created, image areas corresponding to the bounding boxes in the areas are determined on the basis of a preset rule and the information of the isolates in the areas, and the bounding boxes to be detected are determined by judging whether the bounding boxes are overlapped with the bounding boxes in the corresponding image areas in space or not; and judging whether a grid intersection point exists between the target area corresponding to the bounding box to be detected and the corresponding image area or not so as to complete collision parallel detection. According to the invention, the efficiency and accuracy of collision detection are effectively improved.

The invention provides a safety coefficient prediction method based on slope three-dimensional finite element analysis and application, and relates to the field of hydraulic geotechnical engineering. Comprising the following steps: inputting a finite element grid, and calculating a geometric topological relation of the three-dimensional finite element grid; the method comprises the following steps: inputting position information and mechanical parameters of a bottom sliding surface and a side sliding surface of a possible sliding block, calculating to obtain a description equation of the possible sliding block, performing cutting calculation by utilizing a sliding surface equation and geometry of a finite element grid to obtain polygons of a boundary surface of the sliding block, decomposing each polygon into triangular grids, and analyzing a stress result based on a slope finite element to obtain a stress result of the boundary surface of the possible sliding block. Calculating stress values of triangular mesh nodes of the boundary surface through line interpolation; integration is carried out on the sliding force and the anti-sliding force of the boundary surface, and the safety coefficient of the possible sliding block body is calculated; according to the method, efficient intersection of the sliding surface and the finite element grid is achieved, geometric processing efficiency is improved, calculation efficiency and calculation accuracy are improved, and the method is suitable for three-dimensional irregular sliding block analysis in the fields of water conservancy, mines and the like.

A method of establishing connection between a first node in a wireless network and a second node in said wireless network, wherein each of said first and second nodes comprise a primary radio receiver and a wake up receiver, each of said nodes comprising a Radio Frequency, RF, switch, arranged to connect one of said primary or secondary radios to a radio antenna, said method comprising the steps of transmitting, by said first node, to a wake-up receiver of a second radio node, a wake-up signal that indicates a frequency channel on which the second radio node is to transmit a response, receiving, by said first node, in response to transmitting said wake-up signal, response from said second radio node on the frequency channel indicated, and establishing, by said first node, a connection between said first and second nodes in order to transfer data between said first and second nodes. The present disclosure also relates to corresponding mesh nodes and a computer program product.

The invention belongs to the technical field of engineering simulation data processing, and particularly discloses a finite element grid graph structure construction method and system, a terminal and a medium. Comprising the following steps: analyzing original full-amount grid data exported by finite element simulation, segmenting unstructured grid data into a grid vertex coordinate set and a grid unit mark number set, and constructing a graph edge topological structure corresponding to a grid based on a unit mark number relationship; on the basis, loading physical field data and adopting a tolerance-based coordinate matching algorithm to realize accurate mapping of physical field labels and material attributes with grid nodes; and generating standardized finite element grid graph data which can be directly used for graph neural network processing. By means of the method, high-consistency and high-physical-reliability conversion from the finite element simulation data to the graph structure data is achieved, and the physical field modeling and simulation acceleration capacity based on graph learning is improved.

The invention discloses a petroleum pipeline service life prediction system based on a 3D technology, and relates to the technical field of pipeline service life detection, and the system comprises a contour reconstruction module S11 which is used for obtaining the surface three-dimensional point cloud image data of a petroleum pipeline housing in an actual operation environment, and carrying out the surface contour reconstruction processing based on the three-dimensional point cloud image data, extracting space geometric structure data containing a local deformation defect area; the force-heat coupling analysis module S12 is used for constructing a finite element analysis grid according to the space geometric structure data and loading operation condition data into corresponding grid nodes to generate a force-heat coupling stress field, and the operation condition data comprises a periodic internal working pressure value, along-line temperature field data and an axial disturbance stress tensor; the feature extraction module S13 is used for calculating an equivalent stress distribution value of a defect area node based on a force-heat coupling stress field; according to the invention, accurate quantification of fatigue damage evolution of the defect area is realized.

The invention discloses a wing regular metal structure stress simulation data dimensionality reduction and correction method, which comprises the following steps: firstly, carrying out wing regular metal structure finite element simulation, respectively obtaining data such as grid nodes and node stress values under dense grid and sparse grid conditions, and completing data preparation; carrying out data clustering analysis by utilizing a distance-based clustering algorithm, calculating the distance between each nearest neighbor point and the central point, and obtaining a plurality of nearest neighbor points with the nearest distance and node stress values corresponding to the nearest neighbor points; calculating the stress value of the target point according to the distance weight and the node stress of each nearest neighbor point; correcting the stress value of the target point by using the maximum value of the stress value of the target point and the relative error of the concentrated stress to obtain a corrected stress value; and finally, calculating a relative error between the concentrated stress and the maximum stress of the structure as a second relative error, and correcting the corrected stress value again. According to the method, dimension reduction and correction of large-scale and high-dimension finite element simulation data can be realized, and the accuracy degree is high.

The invention discloses a data detection method and system based on gravitational-magnetic-electric-seismic signal joint gridding, and relates to the technical field of geological prospecting, and the method comprises the steps: determining a research region according to an exploration target and geological conditions, and dividing the research region into grids with the same size; on each grid node, gravity, magnetic, electric and seismic signals are collected; the collected gravity, magnetic and electric shock signals are preprocessed; performing feature extraction on the preprocessed gravity-magnetic-electric-seismic signals by using an independent component analysis algorithm, and performing data fusion by using a convolutional neural network in deep learning; establishing an initial value estimation incidence relation model, and obtaining an initial value prediction result based on the fused data; according to the initial value prediction result, geological parameters are obtained through solving by using a joint inversion algorithm. According to the invention, efficient combined acquisition of gravity, magnetic, electric and seismic signals is realized, the precision and quality of acquired data are improved, and unified management and fusion analysis of the data are realized.

The invention discloses a finite difference seismic travel time calculation method based on Fibonacci heap sorting, and the method comprises the following steps: S1, reading parameters and a speed model, and reading related parameters and the speed model in a file; s2, a seismic source and a narrow band are initialized; s3, selecting and arranging a Fibonacci pile; s4, selecting a travel time minimum point in the narrow band; s5, judging attributes of adjacent points; s6, judging whether the narrow band is empty or not; and S7, outputting first-motion wave travel time, performing circulation until a narrow band is empty so as to complete travel time calculation of all grid nodes, and outputting a final travel time calculation result. According to the finite difference seismic wave travel time calculation method based on the Fibonacci heap sorting, the minimum travel time point in the narrow band is screened by adopting the Fibonacci heap sorting, so that the finite difference seismic wave travel time is calculated. The efficiency of grid point travel time calculation is improved, and the finite difference seismic travel time calculation method based on Fibonacci heap sorting is realized.

The invention relates to a tunnel ventilation system parameter optimization method based on neural network model driving, and the method comprises the steps: dividing a tunnel into a plurality of irregular grid nodes according to the three-dimensional geometrical characteristics, aerodynamic characteristics and pollutant distribution characteristics of the tunnel; constructing a nonlinear edge weight calculation function according to the spatial distribution data of the plurality of irregular grid nodes in combination with a pollutant diffusion coefficient, a real-time wind speed field and a spatial position relationship among the grid nodes, and generating an edge weight matrix representing interaction strength among the grid nodes; inputting the grid node information of the plurality of irregular grid nodes and the edge weight matrix into a space-time diagram neural network model to obtain multivariable space-time dynamic characteristics of the pollutants; according to the multivariable space-time dynamic characteristics, pollutant concentration overrun probabilities of the irregular grid nodes are determined; and according to the pollutant concentration overrun probability of the irregular grid nodes, ventilation regulation and control parameters of the tunnel ventilation system are optimized. The design of ventilation system parameters can be optimized.

The invention relates to the technical field of blast furnace smelting, and discloses a method, device and equipment for determining the position of a blast furnace soft melting zone and a storage medium, and the method comprises the following steps: carrying out charge level scanning based on a material distribution starting signal and a material distribution ending signal of current material distribution to obtain a charge level coordinate and a charge discharging speed; determining a first boundary condition based on the furnace charge level coordinates and the blast furnace characteristics, and constructing an initial grid structure; the initial grid structure is updated based on the furnace charge level coordinates and the furnace charge discharging speed, and a target grid structure is obtained; enabling the blast furnace burden to react, obtaining the distribution condition of each grid unit in the target grid structure under the condition that a plurality of burden performance parameters of each grid node in the target grid structure converge, and generating a temperature field distribution diagram; and determining the position of the soft melting zone of the blast furnace based on the plurality of furnace charge performance parameters and the temperature field distribution diagram corresponding to each grid node in the target grid structure. According to the method, the accuracy of determining the position of the soft melting zone is improved, and dynamic changes in the blast furnace are reflected.

The invention belongs to the technical field of control detection, and particularly relates to a laser cutting machine cutting control method and system.The laser cutting machine cutting control method comprises the following steps that S1, frequency sweeping excitation is applied to a plurality of preset grid node positions of a laser cutting machine workbench, and vibration response data of a cutting head is collected; a dominant pole and a zero point of a vibration transfer function of each grid node are identified and extracted, spatial distribution is fitted by using a non-uniform rational B-spline surface, and a spatial model of continuous mapping between a cutting head position and a vibration transfer function parameter is established; s2, decomposing a to-be-processed path into a plurality of path infinitesimal segments, and calculating a preliminary feed-forward compensation instruction of each path infinitesimal segment based on a space model and a zero-phase error tracking control algorithm; according to the invention, the contour error caused by structural vibration and non-linear factors is reduced, the processing precision and the cutting surface quality of the laser cutting machine in a full working range are improved, and the forming effect of a complex contour at a high speed is improved.