520 results about "Control equation" patented technology

The invention discloses a PINN-based high-precision hydrodynamic numerical simulation method and system, and the method comprises the steps: firstly building a computational domain, setting reasonable geometric parameters and boundary conditions, and constructing a dimensionless Navier-Stokes control equation set; then designing a deep neural network architecture with space-time coordinate input and flow field variable output, and adopting a loss function combining physical constraint and data driving; the core innovation lies in providing a timing sequence sensing RAR-D adaptive sampling strategy, dividing a time domain into a plurality of time frames, performing residual error evaluation in each frame, constructing a probability density function related to residual errors, and balancing priority sampling and overall coverage of a high residual error region; adam and L-BFGS optimizers are adopted to carry out network training, the weight of a loss function is dynamically adjusted, and a sampling point set is periodically updated; and finally, the solution precision is verified through multi-dimensional flow field visualization analysis. Therefore, the prediction precision of the complex flow field is effectively improved, and the calculation efficiency is remarkably improved.

The invention is applicable to the technical field of coal bed gas development and geological sequestration, and provides a THMC multi-field coupling simulation method and system for a process of displacing CH4 by coal bed CO2, and the method comprises the following steps: collecting multi-source parameter information of a target coal bed; according to the multi-source parameter information, constructing a coal seam structure model comprising a matrix and a crack system; constructing a control equation system based on the coal seam structure model, and introducing a multi-field coupling mechanism to obtain a fully-coupled mathematical model; performing numerical solution on the fully-coupled mathematical model to obtain a spatio-temporal evolution result of the key field variables; and according to the spatio-temporal evolution result of the key field variable, evaluating the index of the target coal seam. According to the invention, a heat-force-gas-chemical multi-physical field full-coupling simulation system is constructed, so that the CH4 recovery rate and the CO2 storage stability can be accurately predicted. The method is suitable for gas injection-storage coupling optimization of a multi-coal-rank and low-permeability coal seam, and has high precision, high adaptability and remarkable engineering guidance value.

The invention provides a deep energy reservoir multi-scale heat-fluid-solid coupling simulation method and system, and belongs to the field of deep energy reservoir numerical simulation. Acquiring spatial distribution characteristics and physical property parameters of different lithologic reservoir media under a micro-scale, and constructing a digital structure model of the reservoir media; a micro-observation action mechanism and a flow mechanism are embedded in the model to obtain a micro-observation numerical model; establishing a mapping relation by solving model structure parameters and physical property parameters of the microscopic numerical model under different thermal-fluid-solid coupling conditions; and on the basis of the mapping relationship, in combination with the macrogeological and engineering data of the target reservoir, establishing a macroscale heat-fluid-solid multi-field coupling control equation and solving, and outputting the multi-physics field response of the target reservoir under the given working condition. According to the method, fine simulation of physical property parameter dynamic transmission and a multi-field coupling evolution process from a micro view to a macro view is realized, and the accuracy and reliability of deep complex reservoir engineering behavior prediction are remarkably improved.

The invention provides a flow field solving method based on a time sequence physical information neural network, and belongs to a partial differential equation calculation method. The method comprises the following steps: firstly, determining a flow field motion law and a flow field computational domain based on a fluid motion control equation, configuring data points for training and performing data fusion operation; secondly, constructing a physical constraint residual equation, taking the training data set as input data of a neural network, calculating a data residual term, weighting a calculation result of the physical constraint residual equation and a calculation result of the data residual term, and constructing a data-physical mixed loss function; and finally, constructing a time sequence-based physical information neural network, performing training optimization on parameters of the time sequence-based physical information neural network, completing training and obtaining simulated flow field features. By introducing the time sequence module, the accuracy of flow field dynamic simulation based on the time sequence physical information neural network is improved, the requirement for the model solving speed can be met, and the feasibility and accuracy of the model are guaranteed.

The invention provides an optical element surface type simulation method based on a physical information neural network, and relates to the technical field of element design and simulation, and the method comprises the steps: constructing a feedforward neural network; generating a deformation control equation model library; constructing a three-dimensional simulation database; forming a machine learning parameter library; training the PINN deformation simulation model in combination with a deformation control equation model library, a three-dimensional simulation database and a machine learning parameter library, and screening out a target PINN deformation simulation model meeting a preset condition; inputting the design parameters, the support structure parameters and the given external load parameters of different combinations into the target PINN model to obtain a key performance prediction result of the optical element; according to the method, the key performance of the element under various parameter combinations can be rapidly evaluated, the design iteration period is shortened, the trial and error cost is reduced, direct data support is provided for supporting structure optimization design, and the bottleneck problem that a traditional method restricts the research and development efficiency of a high-precision optical system is effectively solved.

The invention discloses a CFD calculation method and system based on a neural network and adaptive parameter optimization, and belongs to the technical field of computational fluid dynamics. Initializing a flow field by reading calculation parameters and a grid file; solving the N-S equation, recording solving parameters and outputting an intermediate flow field; inputting the intermediate flow field into a pre-trained physical constraint neural network, sequentially applying boundary condition hard constraint and soft constraint based on control equation residual error, and outputting a corrected flow field; based on the convergence dynamic characteristics and the solving parameters, outputting a parameter adjustment amount through a strategy network of reinforcement learning training, and dynamically optimizing the solving parameters; and taking the corrected flow field as an initial flow field of the next iteration step, updating solving parameters, and circularly executing until convergence. According to the method, the physical prior is embedded into the neural network, intelligent self-adaptive regulation and control of solving parameters are realized through reinforcement learning, and the prediction precision and convergence efficiency of complex flow simulation are remarkably improved.

The invention provides a real-time prediction method and system for milling deformation of a thin-wall part and electronic equipment. The method comprises the steps that a partial differential equation set used for reflecting the deflection and stress coupling relation in the milling machining process of the thin-walled workpiece is constructed based on a von Karman control equation set; constructing a deformation prediction model based on a depth operator network; according to the partial differential equation set, constructing a loss function comprising a partial differential equation residual term and a boundary condition term; training the deformation prediction model according to the loss function and two-dimensional coordinate points and load function sampling points used for training the deformation prediction model; and deploying the trained model in a machine tool system, inputting real-time load data and real-time coordinate data of the thin-wall part in the milling process, predicting deformation response of the thin-wall part in the milling process, and obtaining a target prediction result. The method can quickly and accurately predict the deformation response of the thin-wall part under the complex load working condition, and improves the machining quality and efficiency of the thin-wall part.

The invention discloses a stress corrosion crack propagation simulation and prediction method and system based on a phase field method. The method comprises the following steps: constructing a stress corrosion dynamic evolution model based on the phase field method; the stress corrosion dynamic evolution model is a control equation set for coupling a displacement field, a material concentration field and a crack phase field to carry out stress corrosion cracking evolution; establishing a discrete numerical value format for analyzing the stress corrosion dynamic evolution model, and performing simulation program development of the stress corrosion dynamic evolution model based on an ABAQUS platform according to the discrete numerical value format; and acquiring a specific load working condition, and performing stress corrosion crack growth rate simulation prediction on the nuclear reactor primary circuit 690 alloy material under different working conditions based on a developed simulation program to obtain the crack growth rate. According to the invention, the phase-field function is introduced to describe the crack morphology to simulate the stress corrosion crack propagation, and the rule of the stress corrosion crack propagation of the primary loop 690 alloy under different working conditions is accurately simulated.

The invention discloses a GIS equipment shell vibration fault identification method and system based on a physical information neural network, and relates to the technical field of GIS fault diagnosis, and the method comprises the steps: collecting a vibration acceleration signal of the surface of a GIS shell; establishing a simplified physical model of the vibration system, and determining a control equation, initial conditions and boundary conditions of the vibration system; based on the HFT-MPINN or the RL-PINN, constructing a parameter inversion model; fusing physical constraint loss, experimental data loss and multi-parameter coupling loss of the vibration system to construct a composite loss function; training a parameter inversion model by using the vibration acceleration signal to obtain key physical parameters of the vibration system; time-frequency domain analysis and finite element simulation verification are combined, and the mechanical fault type and degree of the GIS equipment shell are recognized. According to the method, the modeling precision, the noise robustness and the multi-working-condition adaptability of the high-frequency vibration signals are improved, and reliable technical support is provided for intelligent fault diagnosis of GIS equipment.

The invention discloses a direct coal liquefaction pump thermal wear prediction method considering a high temperature effect, and belongs to the technical field of fluid machinery and reliability engineering.The method comprises the steps that the high temperature effect is considered, a liquid phase control equation and a solid particle dynamic model are subjected to coupling iteration, and a solid-liquid two-phase flow numerical model is obtained; the method comprises the following steps: performing full flow field modeling on a fluid domain formed by flow passage components of a pump for direct coal liquefaction, and performing grid division on the fluid domain; constructing a heat-flow-solid multi-field coupling calculation system, and solving the solid-liquid two-phase flow numerical model by adopting a large eddy simulation method based on temperature correction and a discrete element method coupling method to obtain information of flow fields and particle fields at all positions in the pump; operation condition parameters are obtained, the thermal wear rate is obtained through a thermal wear rate calculation formula on the basis of flow field and particle field information of all positions in the pump, and the predicted wear amount of the flow passage component is obtained; and the prediction precision and applicability of the wear model are improved.

The invention discloses a mass concrete construction temperature control anti-cracking integrated system and method, and the system comprises a construction module which is used for constructing a cooling water pipe fine model based on concrete thermodynamic parameters and construction conditions, solving a heat flow coupling control equation through a heat flow coupling algorithm, and determining a concrete internal temperature field and stress field distribution cloud chart; the monitoring module is used for collecting attribute data of concrete; the comparison module is used for comparing the attribute data with the concrete internal temperature field and stress field distribution cloud atlas, correcting model parameters of the heat flow coupling model according to a comparison result, generating a regulation and control instruction and sending the regulation and control instruction to the execution module; the execution module is used for receiving and executing the regulation and control instruction; the regulation and control instruction comprises at least one of temperature regulation and pouring time sequence optimization. A temperature field and a stress field are accurately predicted, complex construction working conditions are matched, mechanical and thermal state changes of the whole life cycle of concrete are captured in real time, temperature control adjustment is effectively conducted, and the construction quality is improved.

The invention discloses a split type three-box girder nonlinear vortex vibration steady-state amplitude intelligent prediction method, belongs to the field of bridge vortex-induced vibration control, and aims to solve the problem of low accuracy of three-box girder vortex vibration nonlinear modeling and amplitude prediction. The method comprises the following steps: acquiring displacement time sequence data through a reduced scale model wind tunnel test, preprocessing to obtain displacement, speed and acceleration dimensionless data, and dividing a data set; constructing a candidate function library containing high-order polynomial terms of the primary function; performing nonlinear system sparse recognition by taking acceleration data as a target item and combining an improved algorithm to obtain a preliminary feature set; a final feature set is obtained through energy-statistics-self-adaption three-stage screening; and finally, constructing a control equation to predict the steady-state amplitude. The method can accurately predict amplitude, coincide test and real bridge observation results, and is less in computing resource occupation and high in numerical value precision.

Provided is a three-dimensional thermal-hydraulic analysis method and system for a reactor core. The method includes: analyzing a type of a reactor core, dividing an outer-layer mesh and a computational mesh, and establishing a conservative mapping relationship and a set of transport equations; decomposing a coolant viscosity-induced frictional effect, and representing a turbulent mixing-induced exchange of a physical quantity through a source term; establishing a three-dimensional set of governing equations including mass, momentum, and energy conservation equations to describe a flow and heat transfer phenomenon within coolant channels, and forming a fully assembled matrix system based on the set of transport equations; setting a boundary condition and an initial condition for a physical field of the reactor core, and setting an initial field; and iteratively solving the fully assembled matrix system, and obtaining a thermal-hydraulic parameter.

The invention discloses an intelligent well site comprehensive management system based on digital twinning and AI analysis, and belongs to the technical field of digital twinning. Uniformly representing the multi-physical field data as a tensor data structure including a space dimension, a time dimension and a physical quantity dimension; performing data fusion on the tensor data structure and the three-dimensional geometric model of the well site, and establishing a spatial association relationship of multi-physical field data at grid nodes; establishing physical field control equations based on the fused data, and correlating the equations through a coupling operator to form a multi-physical field coupling equation; solving the coupling equation to obtain a numerical solution of each physical field distribution; generating a control instruction sequence for adjusting the operation parameters of the well site equipment according to the numerical solution; according to the invention, accurate sensing and intelligent regulation and control of the operation state of the well site equipment are realized, and the intelligent level of well site management is obviously improved.

The invention discloses a free vibration semi-analytical calculation method for a liquid filling functional gradient pipeline on an elastic foundation, and relates to the technical field of solid mechanics and fluid-solid coupling vibration analysis. The method comprises the following steps: acquiring materials, geometry and boundary parameters of a pipeline, a fluid and a foundation, establishing a fluid-solid coupling model based on a three-dimensional elastic theory, simulating foundation support by adopting a two-parameter Pasternak model, and deducing a control equation and boundary conditions of a pipeline structural domain and a fluid domain; discretizing a pipeline reference surface and a fluid boundary through a two-dimensional high-order spectrum unit, and converting an equation into a standard coordinate system in combination with proportional boundary coordinate transformation; proportional boundary finite element control equations of a structural domain and a fluid domain are deduced respectively and converted into a first-order differential equation set, then a fine integration method and an eigenvalue decomposition method are adopted for solving, and then based on a fluid-solid coupling condition coupling equation, the equation is converted into a generalized eigenvalue problem for solving the inherent frequency and the vibration mode. According to the method, only precision, efficiency and discrete boundaries are considered, and support is provided for pipeline design optimization and safety evaluation.

The invention discloses a reaction steam turbine through-flow method and system based on variable reaction degree optimization, and belongs to the technical field of steam turbine through-flow design. The method comprises the steps that an initial geometric model of a steam turbine through-flow part and thermal boundary conditions of all stages are obtained; inputting the initial geometric model and the thermal boundary conditions into a flow field solver, and solving a flow control equation to obtain an original flow field solution; constructing a functional taking through-flow efficiency as a target, and deducing an adjoint equation corresponding to the flow control equation; solving the adjoint equation to obtain gradient information of the target functional to each level of reaction degree; inputting the gradient information into a sequential quadratic programming optimizer, and iteratively updating the reactance of each stage by combining the maximum equivalent stress upper limit of the moving blade and the lower limit of the through-flow throat area to generate a variable reactance distribution scheme; and adjusting molded line geometric parameters of each stage of stationary blade and moving blade, and outputting optimized three-dimensional molded line data and a digital model file for numerical control machining. According to the method, the in-stage flow loss is reduced, and the design robustness is enhanced.

The invention discloses a method for predicting shock waves through a multi-region conservation enhanced physical information neural network, and belongs to the field of flow field prediction of shock waves and strong nonlinear physical phenomena in high-speed flow, and the method comprises the steps: S1, carrying out numerical simulation through fluid dynamics software to obtain a reference flow field solution of a to-be-solved N-S control equation, the verification module is used for verifying a model solving result; s2, constructing a neural network comprising an integral layer, a micro-layer and a loss function error layer; s3, constructing a physical information neural network; s4, training is carried out after physical information neural network training parameters are set, and whether a convergence standard is met or not is determined by constructing a joint loss function corresponding to the physical information neural network; and S5, applying the trained neural network model to shock wave prediction of high-speed flow field simulation under different working conditions. Through the multi-region local conservation constraint, the width of the shock wave transition region is effectively compressed, so that the relative error of the physical quantity is obviously reduced compared with the existing method.

The invention discloses an intelligent temperature control system for mass concrete, and the system comprises a state collection module which collects initial parameters of the concrete in real time, carries out the time sequence alignment and noise filtering of the state parameters of the concrete, and obtains the temperature state data of the concrete; the intelligent analysis module is used for inverting concrete thermal parameters through a physical information neural network based on the concrete temperature control data, substituting the concrete thermal parameters into a heat conduction finite element control equation to calculate space-time evolution of the whole-field temperature and stress field, and obtaining twin data of the concrete structure; and the prediction optimization module is used for executing multi-step rolling in a multi-input single-output branch mode based on the twin data of the concrete structure to predict temperature and stress evolution in a future time period, and learning dynamic association among the temperature, the stress and the cooling flow to execute minimum energy consumption screening of a temperature control standard and stress constraint to obtain an optimal cooling control instruction.

The invention discloses a network construction type energy storage transient stability optimization control method and system considering reactive power degradation, and belongs to the field of power system transient stability control. According to the method, a network construction type energy storage grid-connected system model is constructed, a reactive power degradation effect dynamically triggered by a reactive power control loop is analyzed, and an active power loop optimization control equation is established according to the reactive power degradation effect. On the basis, a self-adaptive torque adjusting module is embedded in an active control module, and when it is monitored that the internal voltage of the inverter is reduced to 50% of a rated value, the reference torque is automatically and dynamically corrected so as to improve the power angle transient stability margin of the system. Simulation results show that the method can effectively restrain the instability of the network construction type energy storage power angle, obviously enhance the transient stability of the system, and guarantee the safe and reliable operation of the power grid.

The invention relates to a multi-physical-field deformation analysis method and system based on a COMSOL platform and a particle finite element. The method comprises the steps that a physical deformation analysis model is built, and an initial finite element grid is generated; solving the control equation by using a solver of the COMSOL platform to obtain a multi-physical-field state variable; carrying out particle space position updating on finite element grid nodes according to the multi-physical field state variables, and carrying out Delou inner triangulation and boundary identification based on an updated particle point set to obtain a free boundary; reconstructing the grid based on the free boundary, and mapping the state variable of the previous grid to the new finite element grid; according to the new finite element mesh, updating boundary conditions of the physical deformation analysis model, and iteratively updating the physical deformation analysis model in a COMSOL platform; and outputting a deformation analysis result based on the final physical deformation analysis model. According to the invention, stable and high-precision numerical analysis of large-deformation and multi-field coupling processes in energy geotechnical engineering is realized.

The invention relates to the technical field of Isa furnace metal smelting processes, in particular to a numerical simulation method and system for reaction of pulverized coal at the upper part of a hearth of an Isa furnace and monitoring of flue gas components at an outlet, which are based on reasonable basic assumption and in combination with field parameters, construct a simulation equation and perform parameter coupling on a control equation in the simulation process. The physical quantity field distribution in the hearth in the metal smelting process of the Isa furnace can be subjected to accurate numerical simulation, the obtained data is matched with the actual production data, the corresponding production rule can be obtained, and the method has important guiding significance for controlling the coal consumption of the Isa furnace and the flue gas components at the outlet; besides, the numerical simulation method for monitoring the pulverized coal reaction at the upper part of the hearth of the Isa furnace and the flue gas components at the outlet and the corresponding data can be used as a basic support for intelligent feeding or other related parameter management and control in the metal smelting process, so that more accurate management and control in the smelting production link of the Isa furnace can be realized; and the effects of reducing cost and increasing efficiency are achieved.

The invention discloses a numerical simulation method and system for a corrosion process of a three-dimensional fracture network, a medium and a terminal, and the method comprises the steps: obtaining geological parameters of a target reservoir, and constructing a geometric model of the three-dimensional fracture network; performing mesh generation on the geometric model, and embedding a fracture network into a bedrock mesh by adopting an embedded discrete fracture method; determining a solute transport-fluid flow-water-rock reaction multi-field coupling control equation; carrying out numerical simulation of a crack corrosion evolution process based on the control equation; and outputting the geometrical morphology, solute concentration distribution and flow conductivity change of the crack network after corrosion. The method has the advantages that the real geometrical morphology of the fracture is kept, the technical problem of unstructured grids is avoided, the calculation precision and efficiency are considered, the water-rock reaction, solute transport and convective diffusion processes can be effectively simulated, and the method is suitable for predicting the three-dimensional fracture network corrosion process of the soluble oil and gas reservoir.

The invention discloses an arch bridge tensioning method and system based on a physical constraint space-time diagram attention network, and the method comprises the steps: constructing a dynamic topological graph of an arch bridge cantilever construction structure, taking a structure initial state parameter, a control force system parameter and a real-time environment parameter as node input features, and taking a structure state response parameter as an output label, generating a training data set based on finite element model simulation; designing a deep learning network model combined with space diagram attention and time sequence causal convolution, and modeling a space-time dependency relationship; defining a mixed loss function of the data fidelity item and the physical residual loss item of the structural mechanical control equation; and training the model through a back propagation algorithm and deploying the model to a field decision control system. According to the method, through graph structure abstraction, spatio-temporal joint modeling and physical constraint embedding, multi-source monitoring data driven structure state online prediction and tension control strategy intelligent optimization are achieved.

The invention discloses a thermodynamic system analysis method and system based on a physical information neural network. The method comprises the following steps: constructing a thermodynamic system mathematical model; converting a solving problem of the mathematical model of the thermodynamic system into an optimization problem taking a minimum control equation set residual error as a target function; constructing a physical information neural network; constructing a composite loss function based on the control equation set residual sum of squares, and performing end-to-end training on the physical information neural network to obtain a trained physical information neural network; taking the trained physical information neural network as an approximate solver, and for any given thermodynamic system input working condition, predicting a group of approximate solutions as initial predicted values through one-time forward propagation; and inputting the initial predicted value into a traditional numerical solver for accurate solving to obtain a to-be-solved state variable. According to the method, a feasible technical path is provided for applications with strict requirements on the analysis and calculation speed of the thermodynamic system, such as real-time simulation, online optimization and digital twinning.

The invention discloses a dimensionality reduction PSO-ITA long-distance water pipe burst positioning method which comprises the following steps: taking a pipe burst point as a node to obtain N pipeline nodes; according to the liquid control equation of the long-distance water conveying pipeline system, calculating the pressure and the flow of a pipeline node adjacent to the node to be measured by using a characteristic line method to obtain the target pressure of the node to be measured; if any to-be-measured node of the long-distance water conveying pipeline has pipe explosion relative to the pipeline, determining target pressure of the to-be-measured node according to a pre-determined liquid control equation of the long-distance water conveying pipeline system, a pipe explosion orifice outflow equation, a fitness function, a pipe explosion position and occurrence moment coupling equation and a particle swarm optimization algorithm; and according to a particle swarm optimization algorithm and a fitness function, solving a final pipe explosion position, size and occurrence time. According to the method, for the pipe explosion problem occurring in a long-distance water conveying pipeline system, the dimensionality reduction PSO-ITA pipe explosion positioning model is used for accurate positioning, and the pipe explosion transient flow numerical simulation precision can be improved.

The invention relates to a GEO spacecraft maneuver detection method considering sample imbalance. The method comprises the following steps: forming time sequence data according to an SGP4 model; on the basis of a maneuvering control equation of the GEO satellite, screening feature vectors from the time sequence data; pCA dimension reduction processing is carried out on the feature vectors, then clustering is carried out on data after dimension reduction, sampling and copying are carried out according to a clustering result and a preset rule, and a balanced sample training set is generated; constructing a CCBGA deep learning framework, performing adaptive optimization on network parameters of the CCBGA deep learning framework by adopting a Bayesian optimization algorithm, and training the optimized CCBGA framework by using a balanced sample training set; and inputting orbit parameter time sequence data of the GEO spacecraft to be detected into the trained CCBGA frame, and outputting a maneuvering detection result. By adopting the method, the maneuvering detection precision and stability of the GEO spacecraft can be improved.

The invention provides a river channel flow field state determination method and device, equipment and a storage medium, and the method comprises the steps: sampling river channel model parameters based on a hydrodynamic control equation to generate a hydrodynamic response sample set covering different feature combinations; and screening abnormal samples in the sample set to obtain an effective data set. According to statistical characteristics and a physical parameter prior range of an effective data set, static attributes and dynamic states of a river channel are coded into dimensionality-fixed structured representation, and a physical enhanced agent model taking the representation as input is constructed. A joint optimization target training model containing a data fitting item and a hydrodynamic control equation physical constraint item is adopted, target river channel entity attributes are converted into matched target structured representation through a space adaptation mechanism, the target structured representation is input into the trained model for flow field deduction, and a flow field state prediction result of the target river channel at the future moment is obtained. By adopting the method, the efficiency, accuracy and suitability of flow field prediction can be improved.

The invention discloses a buried gas pipeline multi-leakage parameter identification and concentration distribution rapid prediction method, and belongs to the technical field of buried gas pipeline safety detection. The method comprises the following steps: firstly, based on a porous medium flow control equation and a component transport equation, establishing a leakage diffusion physical model by utilizing computational fluid mechanics and generating a multi-working-condition sample data set; training a neural network model by using the sample data, and constructing a rapid concentration prediction agent model; in combination with measured data of a monitoring area, an ensemble Kalman filtering algorithm is adopted, the agent model serves as a forward prediction operator, and collaborative inversion of parameters such as the soil type, the leakage direction and the flow is achieved through iterative updating; and finally, outputting complete underground gas concentration distribution in the monitoring area based on the leakage parameters obtained through identification. According to the method, rapid identification of multiple leakage parameters and accurate prediction of concentration distribution are realized under the condition of limited measuring points, and the method has remarkable disaster early warning and engineering application values.