86 results about "Grid computing" patented technology

The invention provides a mechanical arm curved surface scanning path planning method based on a least square conformal algorithm, and the method comprises the steps: carrying out the digital-to-analog conversion of a to-be-scanned curved surface into a triangular mesh, and calculating the curvature and normal vector of the vertex of the triangular mesh; performing point clustering according to the curvature and the normal vector of the vertex to obtain a point set of a plurality of areas capable of being continuously scanned; projecting the three-dimensional vertex to a two-dimensional plane through a least square conformal algorithm; solving a two-dimensional scanning path point corresponding to a point in the point set of each continuous scanning area; the adjacent scanning areas are connected end to end according to the nearest neighbor relation, and a complete two-dimensional scanning path point array is obtained; performing inverse mapping back to three dimensions, and offsetting the path points according to the normal directions of the path points and the parameters of the scanner to obtain a complete three-dimensional scanning path point array; and finally converting the data into executable data of the mechanical arm to complete path planning. According to the method provided by the invention, the curved surface scanning path which is efficient, comprehensive in coverage and high in adaptability and can be executed by the mechanical arm is generated.

The invention discloses a field soil heavy metal pollution health risk dynamic assessment and intelligent early warning system, and relates to the technical field of soil environment monitoring. The system comprises a multi-source data acquisition unit, a data preprocessing unit, a risk calculation engine and a visual interaction terminal. The key technical point is that a dynamic field evolution analysis module and an adaptive grid rendering control module are introduced; the dynamic field evolution analysis module constructs a pollution potential energy field matrix representing a pollutant migration trend based on soil heavy metal concentration and hydrogeological parameters, and calculates a space-time gradient change vector of the pollution potential energy field matrix; and the latter dynamically adjusts the grid local density according to the gradient vector module value, and automatically encrypts the computational nodes in the region with severe risk change. In cooperation with a time sequence prediction deduction and feedback correction mechanism, the method can simulate the dynamic evolution of the pollution plume in the porous medium in real time, solves the problems that a migration rule is difficult to capture and the calculation efficiency of a uniform grid is low in traditional static evaluation, and achieves three-dimensional dynamic risk early warning with high precision and low calculation power consumption.

The invention discloses a multi-sensor fusion-based people flow dynamic identification method and system, relates to the technical field of intelligent traffic, and is used for solving the problems of people flow perception distortion and shielding tracking interruption in a complex environment. The method comprises the following steps: firstly, constructing an environment interference matrix, and dynamically distributing sensor weights according to a radar electromagnetic attenuation rate, thermal imaging illumination abrupt change and a piezoelectric mechanical noise factor; when the thermal imaging density weight is too low and the radar speed weight is greater than a threshold value, triggering piezoelectric gait verification and outputting calibration fusion data; mapping the fusion data to a dynamic grid, calculating three indexes of density entropy, velocity mutation and flow direction consistency, generating a congestion vector, and marking a risk boundary; for a shielding target, generating a virtual track by combining the final known position, speed and density distribution, and optimizing model parameters when a re-identification error exceeds a limit; and finally, a hierarchical dredging instruction is judged and triggered through the virtual track and the risk area space overlapping, and the gate is dynamically adjusted based on the congestion vector to release.

A power conversion device is disclosed in which a grid following amplitude command value and a grid following phase command value are output in response to receiving a switching signal instructing switching from grid following control to grid forming control. The grid following amplitude command value indicates a target value of an amplitude computed by the grid following control. The grid following phase command value indicates a target value of a phase computed by the grid following control. When the grid following control is switched to the grid forming control, an initial value of the target value of the amplitude in the grid forming control to be the grid following amplitude command value is set, and an initial value of the target value of the phase in the grid forming control to be the grid following phase command value is set.

The invention relates to a material stacking method, device and system, a loading machine, a storage medium and a program product. The material stacking method comprises the following steps: acquiring point cloud data of a material pile; projecting the point cloud data to a two-dimensional plane, and dividing the point cloud data into a plurality of grids; the height and the local volume of a corresponding point of each grid are calculated, and the local volume is the volume of the current grid; determining a plurality of shoveling points and a selection sequence of the plurality of shoveling points from the corresponding points of all the grids according to the height and the local volume of the corresponding point of each grid; and according to the selection sequence of the multiple shoveling points, the material piles of the loading machine are stacked. According to the method, the shoveling priority is optimized by combining physical characteristics (potential energy and volume density) of the material pile, and an efficient path planning algorithm suitable for the low dispersed material pile is developed, so that intelligent stacking of the low dispersed material pile based on two dimensions of potential energy and efficiency is realized.

The invention discloses a bare concrete appearance quality evaluation method, which belongs to the field of concrete quality evaluation, and adopts the technical scheme that process data are synchronously acquired in a bare concrete pouring process; obtaining concrete surface appearance index data after demolding; performing time synchronization and spatial inverse registration on the acquired data, and performing gridding association on the appearance indexes and the process data in the corresponding time windows; for each grid unit, extracting vibration effective energy, pumping pressure fluctuation characteristics, template deformation characteristics and environment correction factors from the process data in the corresponding time window and space range, and combining the vibration effective energy, the pumping pressure fluctuation characteristics, the template deformation characteristics and the environment correction factors into a joint characteristic vector; constructing a structural causal model, calculating the cause posterior probability of the appearance defect for each grid, and outputting cause probability distribution of under-vibration, over-vibration, unstable pumping, insufficient template rigidity and environmental sensitization; and generating an appearance quality score according to the cause probability distribution. The method has the beneficial effect that the method for evaluating the appearance quality of the fair-faced concrete is provided.

The invention relates to the field of image processing, in particular to a thermosensitive coating defect detection method and system for thermosensitive paper, and the method comprises the steps: collecting a historical thermosensitive coating original image with defect marks; the defects are clustered, the size of the center point of any cluster serves as the size of an initial window, grid division is conducted on a thermosensitive coating grey-scale map obtained in real time, and a gray-scale co-occurrence matrix of each grid is obtained; taking any grid as a central grid, calculating the sum of differences between the central grid and the gray-level co-occurrence matrixes of all other grids in a preset neighborhood, and normalizing the sum of differences to obtain a texture difference matrix of the central grid; and calculating the probability that the grid has texture defects, calculating the integrated defect probability of pixel points in the grey-scale map, and if the integrated defect probability of the pixel points is greater than a preset threshold value, judging that the pixel points are defective pixel points. According to the invention, potential defects can be effectively detected from the thermosensitive coating image, so that the accuracy of defect detection is improved.

The invention discloses a surveying and mapping route optimization method based on unmanned aerial vehicle remote sensing. The method comprises the steps of collecting historical data, disassembling the historical data into components, calculating a component difference, generating a dynamic offset vector, calculating a stability index based on the dynamic offset vector, a wind speed time sequence and a wind direction change rate, and generating a segmented path; a real shot image of the unmanned aerial vehicle is obtained, grids are generated according to the real shot image and the critical points of the segmented paths, and the paths are adjusted; acquiring real-time water area data to generate a water area grid, calculating a feasibility index of the grid, and planning an optimal water entry track based on the feasibility index and the model; obtaining an optimal water outlet track based on the feasibility index, extracting water outlet data according to the water outlet track, and converting the water outlet data and the air data; the optimal water entry trajectory, the underwater surveying and mapping path and the optimal water exit trajectory are integrated into an optimized path, the influence of wind on the flight path of the unmanned aerial vehicle is reduced, and the surveying and mapping precision and the task success rate are improved.

The invention discloses a space-borne laser radar matching verification method based on spatial variability and a flow field. The method comprises the following steps: calculating the spatial variability of water color remote sensing data of each month by adopting a multi-scale grid; traversing the grid points, and searching the maximum grid size of which the spatial variability is smaller than a threshold value; calculating a space matching window and setting a time matching window according to the size of the maximum grid; measuring time and position according to the in-situ data, searching satellite-borne laser radar data by adopting a maximum space matching window and a set time matching window, and correcting the position of the in-situ data hour by hour according to the corresponding ocean current speed; searching a corresponding space matching window according to the corrected position, and matching the space matching window with satellite-borne laser radar data; and performing quality control on the matched spaceborne data to form a spaceborne laser radar-in-situ data matching pair. According to the method, the matching of the satellite-borne data and the in-situ data can be realized, and the reasonability of space matching window selection is improved.

The embodiment of the invention discloses an ionosphere parameter determination method based on user crowdsourcing data, and relates to the technical field of satellite navigation and positioning, and the method comprises the steps: obtaining ionosphere data uploaded by a plurality of user sides, respectively taking each user side as a target station, calculating a standardized residual error corresponding to each user side through a Kriging interpolation method, and determining the ionosphere parameters of each user side; the user sides with the standardized residual errors larger than the standardized residual error threshold value are removed; and determining a target grid corresponding to each user side on the pre-constructed Q4DIM network, calculating an inclined path ionospheric delay corresponding to the target grid, extracting the inclined path ionospheric delay according to the target grid corresponding to the user side, and sending the inclined path ionospheric delay to the user side. Through combination of the Q4DIM network and the ionosphere data uploaded by the user side in real time, the resolution of the ionosphere data can be improved, the coverage range of ionosphere products can be expanded, the accurate ionosphere data can be broadcasted to the user side, and the rapid positioning precision of the user side far away from the base station can be improved.

The invention discloses an ancient building group fire early warning method and system based on an internet platform, and relates to the technical field of fire early warning, and the specific implementation scheme is as follows: obtaining a visible light image, and determining a scene type based on smoke detection confidence; the method comprises the following steps: after triggering to execute registration operation on an original infrared image, extracting an infrared feature map and a visible light feature map, generating an attention weight map according to the infrared feature map and the visible light feature map, and generating a preliminary fusion feature by combining the infrared feature map and the visible light feature map; performing dimension reduction compression processing on the preliminary fusion feature to obtain a low-dimensional feature vector, and inputting the low-dimensional feature vector into a classifier to obtain a fire occurrence probability of the current monitoring grid so as to select an early warning scheme; and marking the current monitoring grid as a risk source grid, calculating a directional propagation coefficient, updating a fire occurrence probability of an adjacent target grid, and adjusting an early warning scheme. According to the technical scheme of the invention, the problem of poor effectiveness of fire early warning of the ancient building group caused by abnormal fire behavior recognition is solved.

The invention discloses a data center micro-grid computing cooperation double-layer deep reinforcement learning scheduling method, and belongs to the technical field of power systems, and the method comprises the steps: firstly, providing a double-layer multi-agent deep reinforcement learning framework for a high renewable energy penetration scene of a geographically distributed data center micro-grid; a double-layer multi-agent deep reinforcement learning framework containing a global layer and a local layer is constructed, the global layer carries out distribution calculation tasks through centralized deep reinforcement learning training, and the local layer optimizes internal energy scheduling through distributed deep reinforcement learning; and cross-layer interaction and rapid convergence are realized in combination with a layered multi-agent double-delay depth deterministic strategy gradient algorithm. Through cooperation of space-time task adjustment and energy storage, the cost of non-renewable energy sources is reduced by 15%-20%, the convergence speed is increased by 5 times compared with the prior art, dynamic data backup is supported, and the reliability and economical efficiency of the system are remarkably improved while the service quality is kept.

To provide a magnetic core and a magnetic device with excellent DC superimposition characteristics, and also to provide soft magnetic powder suitable for the magnetic core and the magnetic device.SOLUTION: There is provided soft magnetic powder including a soft magnetic particle 2 containing at least one selected from Fe and Co. The soft magnetic powder satisfies the relation of σFeCo(S)-σFeCo(C)≥0.005, where an element distribution obtained by analyzing a surface layer part S of the soft magnetic particle using a 3D atom probe (3DAP) method is divided into a plurality of grids to calculate a sum of a content ratio of Fe and a content ratio of Co in each grid and a standard deviation of the sum of the content ratio of Fe and the content ratio of Co is represented by σFeCo(S) where a population is the plurality of grids, and an element distribution obtained by analyzing a center part C of the soft magnetic particle using the 3DAP method is divided into a plurality of grids to calculate the sum of the content ratio of Fe and the content ratio of Co in each grid and a standard deviation of the sum of the content ratio of Fe and the content ratio of Co is represented by σFeCo(C) where the population is the plurality of grids.SELECTED DRAWING: Figure 2

The present invention relates generally to a system designed to provide application graphical display while using High-Performance Computing systems which are based on GRID systems, in which applications can be executed on any one out of multiple compute nodes while the user interactive session (also known as an X session) is viewed from a control session. In specific, the invention relates generally to a system which creates a separate selfsustained X Display session for each launched application, while a list of available sessions is provided to the main user graphical session allowing interacting with the remote application without directly affecting its integrity in case of disconnection.

The invention provides a two-dimensional flow field calculation method and system for a vertical axis wind turbine, and relates to the technical field of computational fluid mechanics, and the method comprises the steps: building a two-dimensional numerical model for a middle plane of the vertical axis wind turbine; based on the two-dimensional numerical model, determining a two-dimensional flow field of the vertical axis wind turbine at the current moment; according to the two-dimensional flow field, blade lift force is determined; generating a target blade tip vortex element, and calculating the strength of the target blade tip vortex element through the Rogowski lift theorem; updating the position and strength of the vortex element of the blade tip vortex; traversing all grids in the two-dimensional flow field drainage basin based on the updated blade tip vortex elements, and for each grid, calculating the blade tip vortex induced velocity of the position where the grid is located; calculating and applying a required mass source item and a required momentum source item according to the induced velocity; and after the preset updating frequency is reached, outputting a calculation result. The calculation amount is reduced, and the calculation efficiency and accuracy are improved.

The invention discloses an intelligent pressurization and decompression oil return control method and system for an air conditioner system, and relates to the technical field of air conditioner lubricating oil control. The method comprises the steps that grids are divided through oil pipe layout data, single-grid oil resistance is calculated, a resistance thermodynamic diagram is generated, and pressure partitions are dynamically adjusted; a valve distribution strategy is set according to the pressure partitions, valve circulation scores are obtained, and three valves with the highest valve circulation scores are selected as main oil return paths; setting an oil pressure dynamic adjusting algorithm, compensating oil pressure deviation by combining plateau pressure, and adjusting the rotating speed of a variable-frequency oil pump and the opening of an electric adjusting valve; and dynamically adjusting the subarea heating power of the trunk road according to the real-time irradiance and the pressure subarea. The method solves the problem that in the plateau or extreme low-temperature environment, the temperature fluctuates violently, and the oil viscosity rises, so that the decision of the oil return route of the air conditioner is wrong.

The invention provides a tight gas reservoir gridding evaluation method, system and device and a storage medium, and the method comprises the steps: obtaining dynamic and static data of a target block, the dynamic and static data comprising geological data and production dynamic data; geological reserve gridding parameters are determined based on the geological data, and the geological reserves are gridded; determining the dynamic reserves of each well in the target block based on the production dynamic data, and meshing the dynamic reserves of each well; calculating the unused reserves and the ratio of the dynamic reserves to the static reserves of the target block grid by grid based on the geological reserve gridding and the dynamic reserve gridding of each well; and obtaining a gas reservoir evaluation result based on the unused reserves and the dynamic and static reserve ratio. According to the method, fine evaluation and infilled well arrangement of the tight gas reservoir are achieved, well pattern infilled evaluation refinement is high, calculation is convenient, and the method has great significance in development evaluation of the tight gas reservoir, development scheme compiling, recovery ratio improving countermeasure making and the like.

The present invention relates to the technical field of server scheduling, and discloses a large model reasoning scheduling method based on an off-grid computing server, comprising the following steps: collecting hardware information of the off-grid computing server and constructing a server resource vector; decomposing the large model reasoning task into multiple subtasks and constructing task modeling; dividing the tasks using an optimization method based on the hardware information and task dependencies of the off-grid server; dynamically scheduling the subtasks based on the current load status of the server; dynamically migrating some tasks to other servers based on the real-time computing load of the server to ensure load balance between servers; executing the assigned tasks, monitoring the operating status of the server and the completion of the tasks, and dynamically adjusting the task allocation strategy based on the feedback data. By modeling task requirements and server resources, combined with real-time monitoring and optimized scheduling, efficient computing and maximizing resource utilization of large model reasoning in an off-grid environment are achieved.

The invention provides a GNSS interference detection positioning method and system based on an ADS-B network, and relates to the technical field of satellite navigation. And based on the historical state data of the aircraft, predicting the state of the aircraft by using the time sequence prediction model to obtain a predicted value of the state of the aircraft. And if the deviation between the predicted value and the received true value is greater than a preset threshold value, judging that the aircraft is interfered, and calculating the interference confidence coefficient. A monitoring area is divided into grids, interference indexes in the grids are calculated, and a potential interference area is determined. And the ADS-B message of the aircraft with the highest interference confidence in the potential interference area is selected as an interference source to trigger a virtual signal. And finally, calculating the time when the interference source triggers the virtual signal to the ground station, and obtaining the position of the GNSS interference source based on the time. According to the interference detection positioning provided by the invention, the GNSS interference source can be efficiently and accurately detected and positioned, and the reliability of interference identification and the aviation safety monitoring capability are improved.

The invention discloses a space target three-dimensional reconstruction and intelligent identification method based on an RGB-D camera, and the method comprises the steps: obtaining a depth image and a color image of a space target through the RGB-D camera, converting an original depth image in an image coordinate system into point cloud data in a camera coordinate system through a pre-calibrated camera internal reference and a transformation matrix, and carrying out the recognition of the point cloud data in the camera coordinate system; obtaining corresponding color information from the color image through the camera parameters; a visual odometer of SLAM is adopted to transform all the point cloud data to the same global coordinate system for accumulation, and a complete point cloud model representing a space target contour is obtained; preprocessing the point cloud model, searching for a triangular mesh on the real model closest to each point in the point cloud model, calculating the Euclidean distance from each point to the corresponding triangular mesh, and endowing each point with color information according to the Euclidean distance; and performing automatic semantic annotation on the point cloud model, and realizing three-dimensional intelligent identification of the component based on an improved Pointnet + + architecture.

The invention provides a method for classifying urban land by using heavy truck travel data. The method comprises the steps that a city is divided into equal-area grids in space, the truck inflow, outflow and net inflow of each grid within a certain time are calculated, the freight time sequence of each grid is obtained, network community division is conducted on all the grids according to the similarity between the freight time sequences of all the grids, and the freight time sequences of all the grids are obtained. And analyzing the freight time sequence characteristics of each network community, identifying the urban land use type corresponding to each network community, and obtaining the spatial position distribution characteristics of various types of network communities in the city. The method can provide scientific support for urban freight traffic policies and plans, can reveal space-time laws of different areas in freight activities, can provide scientific basis for the urban freight traffic policies and logistics plans, can reflect freight characteristics of urban land, can dynamically update classification results, and can adapt to urbanization requirements of rapid development.

The invention relates to the cross technical field of geographic information science and environmental science, in particular to an urban carbon emission regression prediction method, which comprises the following steps: acquiring urban annual statistical data as original characteristics, and acquiring corresponding carbon dioxide emission; dividing a city latitude and longitude extreme value range into uniform grids, and calculating a coordinate deviation vector and an Euclidean distance from the city to a grid center point; carrying out vector projection on the deviation vector along three unit directions which form 120 degrees with one another, and combining geometric progression spatial frequency coding to generate a spatial embedded feature map; flattening the feature map, obtaining an original attention score through a full connection layer, and combining with spatial distance gating mask screening and merging to obtain a weighted feature; and splicing the weighted features and the original features to obtain an enhanced feature map, training the model, obtaining a carbon emission prediction model, inputting the enhanced feature map of the city to be predicted, and obtaining a carbon emission prediction value.

The invention discloses an induction heating optimization method and system based on numerical simulation. The method comprises the following steps: S1, establishing a three-dimensional geometric model comprising an induction coil, a workpiece and a magnetizer; s2, electromagnetic parameters and thermal field parameters are set based on the three-dimensional geometric model; s3, performing grid division on the three-dimensional geometric model; s4, operating an electromagnetic-thermal sequential coupling solver, calculating transient distribution of an electromagnetic field and a temperature field based on the parameters set in S2 and the grids generated in S3, dynamically updating material attributes according to the current temperature field in each time step, and performing iterative solution; and S5, processing the field distribution data obtained by solving in the step S4, generating a visual result and extracting key performance indexes. According to the invention, the distribution of the magnetic field and the temperature field can be accurately optimized, and meanwhile, extremely high heating efficiency, excellent temperature uniformity and excellent process controllability are realized.

The application discloses a kind of NGSO constellation to GSO earth station lumped interference determination method and system, belong to satellite communication and radio electromagnetic compatibility analysis technical field, method includes: acquisition NGSO constellation and GSO earth station core parameter;Analysis orbit parameter determines reference satellite position plane, conversion geocentric angle and divide coarse grid;Iterate coarse grid and deduce whole constellation satellite three-dimensional position;Calculate link angle and screen collinear interference satellite, mark initial CIR;Satellite position probability density function is constructed, and the total interference probability that initial CIR is integrated is obtained;Compare threshold probability and optimize CIR range;Subdivide final CIR into fine grid, calculate each point lumped interference and probability;Local cumulative distribution curve is constructed, and interference determination is completed by comparing with protection limit value.The application is combined with physical geometric constraint and probability density distribution theory, greatly reduce the amount of calculation, guarantee determination accuracy and compliance, applicable to spectrum coordination, satellite network declaration and other engineering scenarios.

The present invention provides a method and system for simulating debris flow confluence areas based on a multi-grid method, relating to the technical field of multiphase flow simulation. Based on the existing MAC method for simulating debris flow confluence areas, the present invention introduces multi-grid technology to accelerate the solution process. The simulation results can well simulate the morphology and water level distribution of the intersection of the debris flow and the mainstream, and thus be used in the field of debris flow disaster prevention and control. The multi-grid technology makes the algorithm more computationally efficient and converges faster, making it more suitable for large-scale grid computing solutions. Compared with traditional MAC solution technology, the simulation of debris flow confluence areas is more efficient and less time-consuming, which is beneficial to large-scale grid computing solutions.

Embodiments include methods for synchronizing an augmented reality (AR) object placed in a 3D mesh onto a video feed. A computing device may first receive a video feed including a sequence of frames of a scene and depth or motion data captured by a camera. The computing device may generate a three-dimensional (3D) mesh based on the depth or motion data. The computing device may texture the 3D mesh to create a 3D model. Upon performing object recognition, the computing device may identify anchor points in the 3D model and anchor points in the video feed. The anchor points are used to calculate the location of the AR object.

The invention provides a submarine cable burial depth monitoring method, a computer program product and electronic equipment. The method comprises the following steps: acquiring basic temperature data of a to-be-measured space point in a first submarine cable in each unit time of a preset time period; the basic temperature data comprises soil temperature data; obtaining a feature set of the spatial point to be measured according to the basic temperature data; and inputting the feature set into a burial depth monitoring model to obtain burial depth data of the to-be-measured spatial point. And reasoning the feature set by using the burial depth monitoring model to obtain the burial depth data of the to-be-measured spatial point without calculating the heat dissipation condition, thereby reducing the error introduced by parameter estimation in the calculation, avoiding a large amount of grid calculation, saving the calculation resource, reducing the complexity of submarine cable burial depth measurement and calculation time consumption, and improving the calculation efficiency. And the burial depth measuring and calculating efficiency is improved.

The embodiment of the application discloses a method for determining ionospheric parameters based on user crowdsourcing data, and relates to the technical field of satellite navigation and positioning. The method comprises the following steps: acquiring ionospheric data uploaded by multiple user terminals, taking each user terminal as a target station, calculating the standardized residual error corresponding to each user terminal by using the Kriging interpolation method, and eliminating the user terminal whose standardized residual error is greater than the standardized residual error threshold; determining the target grid corresponding to each user terminal on the pre-constructed Q4DIM network, calculating the slant path ionospheric delay corresponding to the target grid, and extracting the slant path ionospheric delay corresponding to the target grid and sending it to the user terminal according to the target grid corresponding to the user terminal. The ionospheric data uploaded by the user terminal in real time can improve the resolution of the ionospheric data, expand the coverage range of the ionospheric product, broadcast accurate ionospheric data to the user terminal, and improve the rapid positioning accuracy of the user terminal far away from the reference station.

The invention provides a combustion device control method based on Simulink and Fluent cooperation, and the method comprises the following steps: importing a combustion device mesh file into Fluent, initializing a computational domain, setting a time step length and a total step length, and starting Fluent solution; when the calculation is converged or reaches the set number of iterations, the Fluent UDF traverses a combustion device grid to calculate the average temperature, and data is sent to a server side of the Simulink S function module; the temperature data is converted into a temperature time sequence value, a difference value between the temperature data and a preset characteristic temperature curve is calculated, the difference value is input into a fuzzy PID controller to obtain a natural gas inlet flow variable quantity, a control parameter is output, and the natural gas inlet flow variable quantity is packaged and sent to a client of a Fluent UDF through a Simulink S function module; and adjusting the natural gas inlet flow so as to update the boundary condition of Fluent, then calculating the next time step length, and repeatedly solving until the total iteration time is reached. The control accuracy of the combustion device is improved.