2739 results about "Simulation based" patented technology

The invention discloses an infrastructure risk operation optimization management system based on AI driving, and belongs to the field of computer data processing and commercial management, and the system comprises a multi-modal causal twinning construction module which integrates on-site multi-modal data streams to construct a dynamic space-time causal map; the risk evolution deduction module is used for performing anti-fact simulation based on a causal atlas to construct a prospective risk model; the collaborative configuration optimization module is used for solving an optimal collaborative defense strategy according to the risk model; the instruction analysis and digital prescription generation module is used for analyzing the defense strategy into a job digital prescription for a specific risk scene; and the intervention efficiency attribution and evolution correction module performs attribution analysis according to the execution effect of the digital prescription and adaptively updates the causal atlas. According to the method, a comprehensive method of constructing a dynamic causal map for risk deduction, coupling resource constraints for collaborative optimization and performing closed-loop feedback on a correction model is adopted, and active prediction, accurate intervention and continuous learning optimization of capital construction risks can be realized.

The invention provides a construction method of a double-path collaborative decision network for multi-agent collaborative path optimization, and the method comprises the steps: obtaining multi-source heterogeneous real-time business data and historical business data, and constructing a standardized data set; converting the standardized data set into a dynamic environment input sequence; at least two domain agents perform full-process business logical reasoning based on the dynamic environment input sequence to generate a decision chain structure covering the full life cycle of the business; implementing full-flow path planning simulation based on the decision chain structure, and generating an initial path scheme including multi-resource collaborative scheduling; the environment perception intelligent agent puts the initial distribution path scheme into an actual logistics distribution scene for execution, and loads real-time environment change information to determine a logistics decision chain weight; and the logistics strategy agent optimizes the initial distribution path scheme based on the logistics decision chain weight to obtain a logistics business knowledge graph so as to construct a logistics double-path collaborative decision network.

The invention relates to the technical field of data security, in particular to a data security sharing method and system. The method comprises the following steps: acquiring original shared data, carrying out reverse mapping and block marking, generating block marking data, carrying out inter-block random arrangement on the block marking data, carrying out differential disturbance simulation based on a random sequence, forming disturbance block data, and encrypting the disturbance block data by applying a progressive encryption technology. The method comprises the following steps: carrying out fragmentation storage, generating storage shared data, carrying out access monitoring on the storage shared data, collecting shared access data, and constructing an evidence chain and generating an access traceability data chain according to the data, thereby realizing the security and traceability of data sharing. According to the invention, a safer and more credible data security sharing method is realized.

The invention discloses an unmanned aerial vehicle path planning method and system based on digital twinning. The method comprises the following steps: constructing a three-dimensional environment model based on first target environment data in first target multi-source environment perception data; constructing a digital twin based on the geometric model, the physical model, the control model, the target physical data hybrid dynamic model and the three-dimensional environment model; inputting the second target multi-source environment sensing data into the digital twin, and dynamically simulating the flight behavior of the physical unmanned aerial vehicle based on the second target multi-source environment sensing data to obtain simulated flight environment state data; and based on the simulated flight environment state data, performing path planning on the physical unmanned aerial vehicle in combination with a prediction control algorithm and a path planning algorithm to obtain a target flight path, transmitting the target flight path to the physical unmanned aerial vehicle, and controlling the flight of the physical unmanned aerial vehicle. The method can dynamically simulate the real-time change of the physical unmanned aerial vehicle, plan the optimal flight path and effectively avoid obstacles, and can be widely applied to the technical field of unmanned aerial vehicle path control.

The invention relates to the technical field of engineering management and control, in particular to an electric power engineering construction management and control method and system based on digital twinning. The method comprises the following steps: acquiring heterogeneous sensing data of a construction area, and carrying out dynamic modeling on a structural member to obtain a member-level digital twin grid; performing environmental factor-material performance response coupling based on the component-level digital twin grid to obtain a material environmental response distribution diagram; component environment sensitivity dynamic injection is carried out according to the component-level digital twin grids, and a construction process dynamic map is obtained; performing multi-mode construction state field deduction based on the construction process dynamic map to obtain a construction state evolution distribution field; and performing reversible process scheduling optimization and simulation according to the construction state evolution distribution map to obtain a reversible scheduling optimization map. The efficiency of electric power engineering construction and the resource utilization rate can be improved.

The invention relates to the field of transformer parameter regulation and control, in particular to a parameter optimization method and device for a coupling type transformer. The method comprises the following steps: acquiring multi-dimensional real-time working monitoring parameters and real-time working environment state parameters of the coupling type transformer; performing nonlinear dynamic analysis and global state sensing modeling on the multi-dimensional real-time working monitoring parameters so as to construct a transformer global state sensing model; performing multi-parameter combination definition on the multi-dimensional real-time working monitoring parameters, performing dynamic operation simulation based on a transformer global state sensing model, and collecting operation simulation response data of a plurality of schemes; performing multi-target dynamic balance analysis on the operation simulation response data of the plurality of schemes to obtain an optimal transformer working parameter combination; and carrying out environment dynamic parameter change analysis on the real-time working environment state parameters, and constructing a real-time environment condition distribution field. According to the invention, efficient and self-adaptive adjustment transformer parameter optimization is realized.

The invention relates to a campus Internet of Things terminal scheduling method based on digital twinning. The method comprises the following steps: defining a general twinning state representation structure; introducing a state mapping relationship, and establishing a one-to-many dynamic mapping relationship between a physical state and a virtual twinning state by using a finite state machine; when the state of the physical terminal changes, triggering multi-level response mapping of the twin in the virtual space; semantic fusion is carried out on twinborn real-time data, a scheduling sensitivity index is introduced, disturbance simulation is carried out based on past scheduling behaviors, and the potential influence of a certain scheduling behavior on the whole system is analyzed; carrying out local division on the situation map; using Bayesian estimation and Monte Carlo combination to sample and evaluate the feasibility and income of each solution set in a period of time in the future; simulating the expected influence of each scheduling strategy through a twin body, and selecting a scheduling path; unified modeling and semantic fusion of multiple types of terminals are realized, the intelligent level and predictive ability of scheduling decision are improved, the collaborative scheduling ability of the terminals is enhanced, and coupling unit level regulation is realized.

A stability assessment method of roadway surrounding rock includes: obtaining actual stratum rock parameters; establishing a two-dimensional geological model through numerical simulation based on a drill core columnar diagram and the actual stratum rock parameters; changing influencing factors, and recording amounts and acceleration values of deformation of roadway sidewalls, and whether failure occurs to obtain dynamic response characteristics of roadway surrounding rock, combining the changed influencing factors and the dynamic response characteristics as labels to obtain a dataset, and obtaining multiple datasets including the dataset; dividing the multiple datasets into a training set and a validation set, inputting the training set into a PSO-BP neural network and a GA-SVM deep learning model to obtain a preliminary stability assessment model, and adjusting and validating the preliminary stability assessment model by the validation set to obtain an optimized stability assessment model; and using the optimized stability assessment model to assess roadway stability.

The invention discloses an urban life body full-cycle monitoring system based on a digital twinborn technology, relates to the technical field of urban governance, integrates multi-source data such as GIS data, remote sensing information, surface permeability data and an underground drainage pipe network structure, quantifies a flood high-risk area, and provides an urban life body full-cycle monitoring system based on the digital twinborn technology. The AI flood prediction module deduces the ponding range and the drainage capacity under different rainfall situations by adopting extreme weather analogue simulation based on a historical rainfall trend, a current meteorological condition and a drainage network state, and dynamically adjusts a flood diffusion trend prediction model, so that the flood risk identification is more accurate; the intelligent emergency scheduling module automatically matches flood control resources, combines flood high-risk areas, ponding point locations and traffic flow analysis, optimizes a drainage pump station start-stop strategy, remotely regulates and controls an underground drainage gate, dynamically adjusts the overflow adjustment capability of a sewage treatment plant, and optimizes an emergency risk avoiding route in combination with an intelligent traffic management system. And the accuracy and the execution efficiency of the flood control scheduling scheme are improved.

The invention provides a method for evaluating the grouting water control effect of an underground water-sealed cave depot project. The method comprises the steps that firstly, grouting and geological parameters and hydrological monitoring data of a project area are obtained; establishing a three-dimensional seepage-grouting coupling model, and simulating the dynamic state of a seepage field by using a finite element analysis algorithm; then calculating the equivalent permeability change rate of the grouting affected zone based on a simulation result; constructing an evaluation index system, and performing quantitative evaluation by using a fuzzy comprehensive evaluation algorithm; and finally, generating a grouting parameter dynamic adjustment scheme according to an evaluation result. According to the method, scientific and accurate evaluation and engineering optimization of the grouting water control effect can be achieved, and the safety and economical efficiency of engineering are improved.

Simulation data of the autonomous vehicle is processed by executing a simulation based on the simulation data to generate a simulation result. Then a perception scenario is generated from the simulation result. The generated perception scenario is validated by verifying whether a constraint is satisfied to produce a validated perception scenario. The validated perception scenario can be used to create or refine a perception model used for controlling the operation of autonomous vehicles.

The invention relates to the technical field of intelligent laser processing path planning, and discloses a laser flight processing path planning method and device for a complex curved surface, and the method comprises the steps: obtaining the geometric continuity features of the curved surface, carrying out the region division and boundary feature extraction, obtaining the geometric features of the boundary points of each region, and obtaining the geometric features of the boundary points of each region; performing track generation based on boundary geometric features to obtain an initial processing track path, then performing heat accumulation analysis and track screening, identifying a track section needing to be adjusted, executing multi-target path scheduling optimization, and obtaining adjusted track execution feature data; processing sequence optimization is carried out based on the feature data, and an optimized processing sequence is obtained; performing thermal input analysis and parameter correction according to the processing sequence to obtain an updated processing parameter set; and finally, performing global coordination based on a simulated annealing algorithm, generating a final processing track set, completing track optimization and instruction set generation, and outputting a complete processing scheme. According to the method, the problem of insufficient track fitting degree can be solved.

The invention relates to the technical field of engineering construction management and control, in particular to an engineering construction management and control method and system based on digital twinning. The method comprises the following steps: acquiring real-time construction engineering data and regional environment data, identifying a real-time structured construction state and generating a three-dimensional simulation model, then acquiring a target construction engineering plan and performing process node positioning to calculate a real-time engineering progress deviation, performing compensation simulation based on the deviation, and determining an engineering construction development trend. And then environment constraint mapping and resource conflict analysis are performed to generate corresponding data, and an optimized construction path conforming to environment constraint and resource conditions is screened out through construction optimization path mining of the simulation model, so that the construction efficiency and the management level are improved. According to the invention, the competitiveness and sustainable development capability of the building industry are enhanced, and an efficient and transparent engineering management system is finally formed.

The invention relates to the technical field of part typesetting, in particular to a nesting typesetting mixed common-edge analysis method and system based on laser cutting. The method comprises the following steps: obtaining initial typesetting part structure data, and carrying out part common-edge relation analysis to obtain part common-edge relation data; common-edge path optimization is carried out according to the initially-typeset part structure data, and optimized part cutting path data is obtained; performing laser cutting simulation based on the optimized part cutting path data to obtain laser cutting simulation data; performing typesetting heating balance optimization according to the laser cutting simulation data so as to obtain optimized part typesetting data; and performing cutting waste rate evaluation on the optimized part typesetting data to obtain typesetting cutting waste rate data, and performing minimum cutting waste rate optimization on the optimized part typesetting data based on the typesetting cutting waste rate data to obtain optimal part typesetting data. The cutting efficiency and precision are improved.

The invention discloses an intelligent dynamic tracking and early warning method and system for carbon emission, and relates to the technical field of carbon emission management.The method comprises the steps that a digital twinborn model of a target area is constructed, grid division is conducted based on monitoring precision, and a first layer of fixed monitoring points are arranged; planning a mobile monitoring path in combination with a carbon emission attention fitting result, and configuring a second layer of mobile monitoring points; collecting data through two layers of monitoring points, and establishing a carbon emission data network; performing airflow simulation based on a digital twinborn model, performing traceability inversion in combination with a data network, and positioning an emission source; and finally, equipment-level positioning and carbon emission tracking early warning are realized through equipment matching analysis. The technical problems that in the prior art, the carbon emission monitoring coverage range is limited, the traceability is insufficient, and accurate positioning and real-time early warning of the carbon emission source are difficult to achieve are solved, and the technical effects of high-precision traceability positioning and real-time traceability early warning of the carbon emission source are achieved.

The invention provides a three-dimensional digital core reconstruction method capable of reflecting real shale pore structure characteristics and meeting pore scale numerical simulation connectivity requirements, which comprises the following steps of: firstly, acquiring a pore structure image according to a scanning electron microscope and a micro-nano CT (Computed Tomography); constructing a shale matrix digital core which is consistent with the porosity, permeability and pore size distribution of a real rock sample by adopting a method of combining a numerical value construction method and a physical experiment method; then establishing a digital core of the shale containing the micro-cracks according to the obtained spatial distribution characteristics of the micro-cracks; a matrix digital core and typical micro-crack distribution are combined to obtain a hole-crack structure digital core for pore scale simulation research. The method is reliable in principle, low in cost and accurate in reconstruction result, and solves the technical problems that a digital core obtained by adopting the prior art is poor in connectivity and cannot reflect typical pore characteristics of shale; the method can be used for researching reconstruction of different types of cores and seepage simulation established on a pore scale, and has a good application prospect.

The invention relates to the technical field of distributed simulation based on containerized deployment and elastic expansion and contraction, and discloses a distributed simulation method and system based on containerized deployment and elastic expansion and contraction. According to the distributed simulation method and system based on containerized deployment and elastic expansion, real-time resource monitoring and historical load trend data of a simulation task are collected, and unified load evaluation is carried out in combination with a simulation calculation complexity parameter and an I / O density parameter; the refined modeling and resource demand pre-judgment of the simulation task are realized, and the accuracy of task scheduling and allocation is improved; modularized deployment of simulation tasks is achieved through subtask segmentation based on minimum executable units and a standard containerization packaging mechanism in cooperation with a container arrangement platform, and then concurrent execution and elastic scheduling in a multi-node environment are supported.

The invention relates to the field of circuit board testing, in particular to a flexible circuit board testing method and system. The method comprises the following steps: obtaining a high-definition detection image of a to-be-tested flexible circuit board; detail sharpening enhancement processing is carried out on the high-definition detection image, welding defect visual visualization processing is carried out, and welding defect visual feature data is generated; performing three-dimensional structure topology modeling on the high-definition detection image, and performing dynamic mapping rendering according to welding defect visual feature data to construct a three-dimensional defect rendering model; obtaining an operation monitoring log of the to-be-tested flexible circuit board; performing multi-scene operation simulation based on the operation monitoring log to obtain simulation monitoring data in different temperature scenes; and performing scene-by-scene circuit board abnormal thermal expansion identification on the simulation monitoring data under different temperature scenes to generate an abnormal thermal expansion temperature simulation evaluation report. According to the invention, comprehensive, efficient and accurate flexible circuit board testing is realized.

A method for artificial intelligence recognition of ground penetrating radar images first obtains a noise-free high-resolution simulated ground penetrating radar image through forward simulation; obtains the ground penetrating radar field test data and determines the manual features; establishes a ground penetrating radar graph library based on the simulated ground penetrating radar image and the ground penetrating radar test image; uses a multi-layer convolutional neural network to process the measured image data of the target to determine the autonomous learning features; and finally, determines the final type and final location information of the target disease based on the manual features, the autonomous learning features, and the ground penetrating radar graph library using the committee discrimination method. The accuracy and efficiency of recognition of internal diseases in pavement structures is improved by constructing a ground penetrating radar graph library that integrates manual features, autonomous learning features, and the committee discrimination method.

Disclosed in the present invention are a method and system for simulation based on identification of a rock mass structural plane and prediction of a mechanics parameter. The method comprises: obtaining rock mass multi-scale structural plane data and a rock mass physical mechanics parameter at a tunnel construction site; according to the rock mass multi-scale structural plane data, constructing a tunnel construction numerical calculation model; inputting the rock mass physical mechanics parameter into the tunnel construction numerical calculation model, and performing tunnel excavation numerical simulation; during simulation, obtaining a real-time tunneling parameter of construction machinery; according to the real-time tunneling parameter of the construction machinery and a correlation model between tunneling parameters and rock mass physical mechanics parameters, obtaining a predicted physical mechanics parameter of a rock mass in front of a tunneling point; and updating the tunnel construction numerical calculation model by means of the predicted physical mechanics parameter of the rock mass in front of the tunneling point. The accurate simulation of excavation of a tunnel is implemented.

The invention discloses a UE4-based digital twin model construction system and method, and relates to the technical field of computer vision, and the system comprises a geometric modeling unit which generates three-dimensional model data based on geometric modeling data of a target physical entity, and achieves dynamic LOD rendering level switching through virtualization processing; the real-time data interaction unit is used for analyzing the real-time sensor data flow and generating equipment state data in combination with a transmission operation and maintenance instruction; the simulation engine unit is used for executing rigid body motion and collision simulation based on the equipment state data and outputting a collision event sequence and state transition data by utilizing an event trigger; the machine learning unit is used for training an LSTM (Long Short Term Memory) model based on the collision event sequence and the state transition data, and optimizing state covariance parameters through adaptive Kalman filtering; and the visual interaction unit is used for realizing data synchronization of the command large screen and the mobile terminal through multi-screen collaboration. According to the method, the digital model capable of accurately reflecting physical entity behaviors and characteristics is constructed.

The invention discloses a fault monitoring method and system for an analog integrated circuit, and relates to the technical field of integrated circuits, and the method comprises the steps: collecting and recording the electrical parameter data of the analog integrated circuit; preprocessing the electrical parameter data, calculating the resource utilization rate of each subunit and extracting fault feature information; constructing a digital twinborn model corresponding to the analog integrated circuit, and simulating and predicting a fault based on the digital twinborn model; according to the electrical parameter data, the resource utilization rate and the fault feature information, a reinforcement learning algorithm is introduced, and a fault early warning strategy is optimized based on a simulated predicted fault; and according to the fault early warning strategy, early warning thresholds and early warning levels of different fault types are dynamically adjusted, and fault monitoring is realized. According to the invention, abnormal conditions can be found in time, greater damage to the system caused by potential faults is avoided, the real-time performance and accuracy of the monitoring system are ensured, fault information is rapidly provided for maintenance personnel, and the maintenance efficiency is improved.

The invention relates to the technical field of mechanical engineering, in particular to a three-dimensional simulation design method and system based on an elevator structure. The method comprises the following steps that an elevator structure drawing is obtained; a three-dimensional elevator assembly is constructed according to the elevator structure drawing; lift car static load simulation is conducted according to the three-dimensional elevator assembly, and lift car static load data are obtained; detecting the structural strength of the lift car based on the lift car static load data; evaluating welding defects based on the structural strength of the lift car, and generating welding defect data; identifying a weld weak area according to the welding defect data; determining the abrasion loss of the car structure based on the weld weak area; according to the lift car structure abrasion loss, the lift car bottom plate fracture risk is predicted; carrying out welding optimization design based on the fracture risk of the bottom plate of the lift car to obtain welding optimization design data; and traction and traction simulation is conducted according to the three-dimensional elevator assembly, and traction and traction data are obtained. Based on the mechanical engineering technology, the safety and stability of the elevator structure are improved, and the design precision and efficiency are remarkably improved.

The invention discloses a three-dimensional finite element model generation and numerical simulation method and system for a wading engineering composite material XCT digital image, and belongs to the technical field of finite element analysis. Comprising the steps of collecting a composite material XCT image in an initial state and performing preprocessing; performing statistical analysis on the two-dimensional microstructure parameters; a virtual XCT image is generated based on the Pix2PixHD style migration network; the method comprises the following steps of: accurately segmenting each component region of a real XCT (X-ray computed tomography) image based on a Swinin-Transformer network; completing contour feature extraction and smoothing of the segmented image based on a mapping relation between pixels and nodes; constructing a space coordinate system and carrying out discrete derivation on all yarn center points of each segmented image; grid division is carried out based on a multi-material moving cube algorithm in a CGAL library, and a global cohesion unit is inserted; completing material attribute and local material direction distribution; and customizing proper boundary conditions, and carrying out numerical simulation based on a finite element method.

Disclosed is a computational fluid dynamics (CFD) flow analysis method for blades includes: generating an analysis automation model that predicts CFD flow analysis results according to input analysis conditions, the generating an analysis automation model comprising inputting a blade shape and flow conditions, determining analysis settings for flow analysis over blades, performing CFD simulation based on the determined analysis setting parameters to conduct flow analysis over blades, evaluating results of the performed flow analysis over blades, and training through reinforcement learning using artificial neural networks to satisfy predetermined evaluation criteria, inputting arbitrary blade shape conditions and flow conditions, and determining analysis setting parameters by applying the analysis automation model to the input blade shape and flow conditions, predicting CFD simulation, and outputting the predicted CFD simulation as flow analysis results.

The invention relates to the technical field of data processing, and discloses an ocean current simulation method and system based on a three-dimensional temperature-salinity value. The method comprises the following steps: carrying out line calculation and adaptive mesh refinement processing on a three-dimensional temperature and salt field simulation model to obtain a model operation scheme; performing three-dimensional visualization processing on the three-dimensional temperature and salt field initial data set and the model operation scheme to obtain dynamic three-dimensional temperature and salt field visualization data, and analyzing the dynamic three-dimensional temperature and salt field visualization data to obtain three-dimensional structure data and evolution process data of the key ocean phenomenon; performing data assimilation processing on the multi-source real-time observation data, the three-dimensional structure data and the evolution process data to obtain a fusion data set; and performing ocean current prediction calculation on the fused data set to obtain a three-dimensional ocean current prediction field, and performing uncertainty quantitative analysis on the three-dimensional ocean current prediction field to obtain ocean current simulation probability distribution data. According to the invention, the accuracy and timeliness of ocean current simulation based on the three-dimensional temperature-salinity value are improved.

The invention provides a forest fire spreading simulation method and system based on an unmanned aerial vehicle LiDAR technology, and the method comprises the steps: collecting forest region data based on the unmanned aerial vehicle LiDAR technology, a camera and a sensor; wherein the forest area data comprises LiDAR point cloud data, thermal infrared data, image data and meteorological data; based on the forest region data, performing forest region feature extraction to obtain feature parameters; based on the characteristic parameters, constructing a fire spread dynamic model through a fire spread dynamics reinforcement learning framework and a vertical-horizontal fire spread coupling algorithm; based on the fire spreading dynamic model, fire spreading simulation and prediction are carried out, dynamic early warning is carried out based on simulation and prediction results, and a fire fighting and fire prevention decision is obtained. The technical scheme of the invention has important significance for protecting forest resources and maintaining ecological balance.

The invention relates to the technical field of identification model construction, in particular to a method for constructing a medicinal material identification model based on an image technology. The method comprises the following steps: acquiring a medicinal material sample image and extracting features, constructing a medicinal material identification map, acquiring an original medicinal material image and performing texture remodeling, generating a standard medicinal material image, performing multi-dimensional feature extraction and fusion, forming comprehensive feature representation, and performing growth extension simulation based on the representation. Carrying out initial identification according to the generated track and the identification map to obtain an initial result, carrying out map matching based on the initial result, carrying out edge comparison, generating edge comparison parameters, carrying out centralized contour reconstruction according to the parameters, carrying out detail texture retrieval to generate a final matching result, and carrying out connection marking to generate corresponding result data. And performing model training by using the result data to generate an intelligent medicinal material identification model. According to the invention, the efficient method for constructing the medicinal material identification model based on the image technology is realized.

The invention relates to the technical field of communication and network transmission, in particular to a terminal data acquisition and transmission method for a long-distance heat supply pipeline. The method comprises the following steps that long-distance heat supply pipeline laying area data are obtained, pipe network laying form analysis is carried out, and single-pipe branched heat supply pipe network data are obtained; constructing a pipeline laying model based on the data of the single-pipe branched heat supply network; performing intelligent heat energy flow simulation based on the pipeline laying model, and calculating heat loss in the heat energy flow simulation process to obtain heat loss data; performing thermal protection thermal insulation material integration on the pipeline laying model based on the heat loss data to obtain composite thermal insulation material data; and identifying a straight pipe section of the pipeline laying model, and calculating the minimum thick wall of the straight pipe section to obtain minimum thick wall data. The heat efficiency, the stability and the intelligent management capability of the pipeline system are improved based on the communication and network transmission technology.

The invention discloses an intelligent digital rail transit simulation test system based on a digital twinborn technology, which comprises a digital track simulation platform, a digital track internal test platform and a central digital track server, and a visual digital track 3D scene model is constructed by joint design based on the rubber wheel train dynamic model data and the digital track urban construction coordinate graph. The digital track internal test platform comprises a test navigation control unit, and a digital track mathematical model, an electronic map, magnetic coding data and environment perception simulation information are preset in the test navigation control unit. The train equipment state can be monitored, the train equipment state transition can be controlled in real time, the artificial intelligence machine learning technology is introduced, and the test effectiveness is improved; and a real vehicle and a simulation machine can be accessed at the same time to be converted into a test platform before internal product release. The invention further discloses an intelligent digital rail transit simulation test method based on the digital twinning technology.