41 results about "Steady state" patented technology

The invention relates to an evaluation method of a water-energy-grain stochastic system. The evaluation method of the water-energy-grain stochastic system comprises the following steps: constructing the water-energy-grain stochastic system under the risk influence, and constructing a corresponding stochastic differential equation for the water-energy-grain stochastic system; based on the stochastic differential equation, performing stochastic simulation on a plurality of state variables in the water-energy-grain stochastic system by using a stochastic simulation method to obtain an instantaneous probability and a steady-state probability; and deriving an elastic index according to the instantaneous probability and the steady-state probability, and evaluating the water-energy-grain stochastic system based on the elastic index. According to the embodiment of the invention, the evaluation analysis accuracy under the risk influence can be improved.

The invention discloses a novel heat-flow-force coupling simulation method based on a near-field dynamics differential operator, and the method comprises the steps: defining the geometric dimension of a material, and setting initial parameters; fluid and solid areas are divided into a plurality of near-field dynamic points, a fluid point family and a solid point family are divided, and a discrete model is generated; calculating a temperature field of the fluid; calculating dimensionless heat related parameters of the fluid, and applying boundary conditions of dimensionless temperature, heat insulation and speed of a flow field; calculating a temperature field of the solid material; calculating the dimensionless heat flux density of the fluid-solid interface; calculating dimensionless thermal parameters of the solid material, and applying adiabatic boundary conditions and displacement boundary conditions; calculating the mechanical parameters of the material to comprehensively evaluate the mechanical properties of the system; updating a displacement field and a temperature field of the fluid point and the solid point through iterative calculation by adopting a self-adaptive dynamic relaxation method; in the iteration process, whether the system reaches a steady state or not is judged, and heat-flow-force coupling simulation is completed after the system reaches the steady state.

The invention discloses an initial steady-state compiling method and an initial steady-state compiling system for a Modelica model. The initial steady-state compiling method for the Modelica model comprises the following steps: putting an initial value equation / initial constraint condition and a fixed initial value constraint condition in the Modelica model into an initial value equation system set; when a user starts an initial steady-state mode, removing a corresponding redundant initial constraint condition from the initial value equation system set according to an initial steady-state option, and supplementing the initial steady-state constraint condition; putting the initial steady-state constraint condition and the compiled model state equation into an initial value equation system set; and packaging the initial value equation system set into an initialization function, and calling the initialization function to realize initial steady-state solution of the Modelica model. According to the method, by removing the redundant initial constraint conditions and automatically adding the initial steady-state constraint conditions, the initial state of the model is constructed into the steady-state value, and the modeling efficiency of the complex system model is improved.

The invention relates to the technical field of coal-fired unit energy flow analysis and prediction, in particular to a coal-fired unit boiler energy flow analysis and prediction method under rapid variable load, which specifically comprises the following steps of: firstly, combining a thermodynamic physical framework with a recurrent neural network, and representing a function relationship between a time-varying parameter and a state variable in a mechanism model through a neural unit; rapid fluctuation of energy in the boiler is accurately captured; secondly, a multi-mode switching strategy based on an attention mechanism is introduced, flexible switching is carried out between a strong coupling state and a weak coupling state, and the prediction precision under high-speed load change is guaranteed; and finally, introducing an error compensation model, and dynamically correcting a hybrid model prediction residual error. According to the method, physical constraints of mechanism modeling, multi-mode switching of an attention mechanism and an error compensation model are integrated and fused, so that the problems that most of hybrid modeling studies in the prior art mainly focus on steady-state or finite transient prediction, and studies on energy flow dynamic characteristics under rapid load change are still relatively deficient are solved.

The invention relates to a multi-physics field prediction method and system of a trunk branch PINN architecture, and relates to the field of PINN model application, and the method comprises the steps: obtaining a multi-physics field prediction network architecture; obtaining a porous medium steady-state flow and heat transfer model, and configuring a physical law constraint loss function according to a physical constraint equation; collecting a plurality of groups of data, wherein any group of data comprises space coordinate data and labels for identifying physical field attribute record values; and taking the space coordinate data as input, taking a label for identifying a physical field attribute record value as output supervision, performing minimum loss optimization on a physical law constraint loss function through multiple groups of data, and training a multi-physical field prediction network architecture to generate a first multi-physical field prediction model to execute multi-physical field prediction. The technical problem that in the prior art, due to the fact that research on flow and heat transfer characteristics in a porous medium mostly focuses on the flow problem, a feasible scheme for achieving overall physical field prediction of flow and heat transfer lacks exists is solved.

The invention discloses a liquid level nonlinear dynamic feature construction method and device and a storage medium, and relates to the technical field of system control, and the method comprises the steps: carrying out the preprocessing of collected input data and output data of a steady state working condition at any moment of a system, and constructing an input data state vector and an output data state vector; constructing a system time sequence basic structure function according to the input data state vector and the output data state vector; constructing a state time sequence vector and a time factor attenuation to rewrite the system time sequence basic structure function into a system state space equation; and solving a nonlinear dynamic characteristic matrix of the system based on the system state space equation. According to the method, a state vector and a time sequence basic structure function are constructed, the dependence on a mechanism model is reduced, a state-space equation is constructed by using data, a tedious model simplification process is avoided, dynamic characteristics of the system are directly extracted from input and output data, and a large number of structure parameters do not need to be counted.

The invention provides a post-fault system frequency balance point determination method considering a detailed dynamic element model. Comprising the following steps: carrying out load flow calculation on a system before a fault to obtain a load flow calculation result, and determining a balance point state variable steady-state value and a balance point algebraic variable steady-state value of the system under a given operation condition according to the load flow calculation result; determining a whole system model according to the element model of the system, the balance point state variable steady-state value and the balance point algebraic variable steady-state value; the phase reference node selection equation is used for determining phase reference nodes, the initial iteration condition of the system is determined according to the fault type of the system, the whole system model is solved according to the initial iteration condition, and the frequency balance point of the system after the fault is determined through the phase reference node selection equation. The problems that in the prior art, after-fault frequency balance point solving depends on system time domain simulation, and after-fault system behavior analysis is slow due to the fact that the online application time domain simulation process is slow are solved.

The application relates to a coaxial heat exchange well heat exchange efficiency prediction method in oil exploitation, which comprises the following steps: a coaxial heat exchange well coupling heat transfer physical model is established; according to the engineering structure and the geological conditions of a target block, a standardized heat transfer model directly used for mathematical solution is established; according to the temperature control equation in the oil pipe and the annular space, the wellbore temperature field partial differential equation is calculated by using Laplace transformation, the fluid temperature at a position of the wellbore is calculated, and the wellhead outlet temperature is obtained; the analytical solution of the formation temperature changing with the radial distance and the time in the target block is obtained, the range of the formation temperature drop in the radial direction after the coaxial heat exchange well runs for a predetermined time is evaluated; and the coaxial heat exchange well heat exchange efficiency is calculated and predicted according to the obtained wellhead outlet temperature and the known well inlet temperature. The application can solve the problems of long solution time in numerical simulation and inaccurate calculation results in the analytical solution based on the steady-state assumption, improve the oil production efficiency and reduce the energy consumption.

The invention belongs to the technical field of engineering simulation data processing, and particularly discloses a multi-physics field iterative coupling prediction method and system, a terminal and a medium. Comprising the steps of performing state initialization on a to-be-predicted object based on prediction batch input, and constructing structured feature representation for multi-physics field prediction; constructing a temperature prediction model and a pressure prediction model which are mutually independent; performing multiple rounds of prediction updating on the temperature physical field by adopting the temperature prediction model, and dynamically adjusting related state parameters according to the prediction state of the temperature physical field in the prediction updating process to obtain a stable prediction state of the temperature physical field; and on the basis, performing prediction processing on the pressure physical field by adopting a pressure prediction model to obtain a pressure physical field prediction result corresponding to the temperature physical field prediction state, and outputting a multi-physical field steady state prediction result. By introducing a multi-physics field iterative coupling prediction mechanism, the physical consistency and stability of a multi-physics field prediction result are improved.

The invention belongs to the technical field of vehicle control, and relates to a control method for a transient switching process of a vehicle under extreme working conditions and application of the control method. When the vehicle is in the transient switching process, the motion state of the vehicle is expressed as a coordinate point in a phase plane, namely a drift point, and a steady-state equation of the drift point is constructed according to a vehicle kinetic equation; solving a controllable domain in a steady state through a steady-state control variable, namely, a value boundary of a drift point, and searching a moving track for moving from a current drift point to a target drift point within the shortest time in a phase plane by utilizing a track searching method based on a graph theory, the actual moving track is adjusted and controlled through the optimal track adjusting control strategy to be close to the moving track, and the vehicle in the limiting working condition can be controlled to be in a normal state or a drifting state; the method solves the problems of difficult nonlinear solution and low switching speed, and can be applied to drift control.

The invention provides a rub-impact fault nonlinear characteristic evolution law analysis method based on peak statistics in a period, and the method comprises the steps: firstly building a rub-impact fault model, and selecting two kinetic parameters in the model as analysis parameters; according to the selected dynamic parameter value interval range, a two-dimensional parameter space is established, grid division is carried out, a plurality of grid points are obtained, and each grid point corresponds to one parameter combination; performing numerical integration on each parameter combination to obtain a converged model output steady-state track; and continuously capturing a plurality of extreme points in the steady-state track to perform cycle similarity test, counting the number Nspike of spike pulses in a single cycle as a characteristic quantity, mapping the characteristic quantity to a two-parameter plane to generate an isoperidic map, and obtaining a distribution range of a chaos interval in the isoperidic map. According to the method, the calculation complexity of parameter sensitivity analysis can be remarkably reduced on the premise of keeping accurate identification of chaotic threshold parameters by counting the peak characteristics of the system in periodic oscillation.

The invention relates to the technical field of industrial control, in particular to a control method and system for an insulating material production line. The method comprises the steps of obtaining initial operation data of an insulating material production line in real time; calculating a transient specific energy index in combination with a standard plasticizing reference absolute temperature; performing smooth filtering on the machine head melt pressure to extract a time differential item to obtain a pressure change rate; deducing a dynamic thinning coefficient by combining the transient specific energy index, the previous sampling moment value, the pressure change rate and the machine head melt pressure; constructing a state matrix mismatch correction factor based on the dynamic thinning coefficient, a sliding data window historical maximum thinning limit value and a standard steady-state thinning reference value; and correcting the discrete state space model system matrix in a targeted manner by using the correction factor, and executing adaptive model prediction control to output an optimal control instruction. The method can effectively solve the mismatch problem of the static model under the nonlinear sudden change condition, improves the control precision and reliability, and guarantees the stable and efficient operation of a production line.

The invention discloses a steady-state parameter determination method and device, which are applied to the field of data processing, and the method comprises the steps: determining iteration variable information and dependent variable information under a target scene configured by a user, the iteration variable information comprises the name of an iteration variable and the initial value of the iteration variable, and the dependent variable information comprises the name of the iteration variable and the initial value of the iteration variable; the dependent variable information comprises a name of a dependent variable and a target value of the dependent variable, constructing a relation equation of the target scene according to the iterative variable information and the dependent variable information, and if a loss function of the relation equation reaches a minimum value, determining a current initial value of the iterative variable in the relation equation as a steady-state parameter, and if the loss function of the relation equation does not reach the minimum value, according to a preset initial value selection rule, re-determining the target initial value to iterate the relation equation until the loss function reaches the minimum value or the number of iterations reaches an iteration number threshold, and determining the corresponding target initial value as a steady-state parameter. Therefore, the steady-state parameter can be automatically determined, and the steady-state problem in the system is solved.

The present invention discloses a bearing friction dynamics response analysis method integrating pseudo-statics and dynamics, which belongs to the field of friction dynamics of mechanical engineering technology. A reference coordinate system is established according to the installation direction and rotation direction of a solid-lubricated angular contact ball bearing, and a pseudo-static equilibrium equation and a dynamic differential equation of the solid-lubricated ball bearing with consistent displacement variables are established according to the reference coordinate system; according to the relationship between the contact angle and the contact parameter, the friction force and the friction torque in the pseudo-static equilibrium equation are calculated; according to the friction force and the friction torque, the pseudo-static equilibrium equation is solved to obtain a steady-state analysis result, and the steady-state analysis result is used as the initial value of the dynamic differential equation to solve the dynamic differential equation to obtain the friction dynamics response of the bearing. The present invention can effectively and accurately analyze the tribological and dynamic characteristics of the solid-lubricated ball bearing under stable or time-varying working conditions, and provide guidance for the tribological analysis and design of the solid-lubricated ball bearing.

This application discloses a method and apparatus for predicting the electrical risk of oil-paper insulated equipment. The method includes: acquiring multiple oil and gas sample data with labels and confidence levels from the oil-paper insulated equipment at different time windows; generating a molecular model formulation of the mixture; constructing a molecular simulation mixture model of the mixture formulation at the current temperature; and performing geometric optimization, model annealing, and ensemble balancing to obtain a steady-state model. The method then calculates the total dipole moment of the molecular dynamics system of the steady-state model and the dielectric loss factor, using the planned quantitative value of the dielectric loss factor to assess the degree of electrical risk of the oil-paper insulated equipment. Therefore, this method provides a mechanistic and quantitative mapping from monitoring data to electrical risk, accurately calculates real-time dielectric parameters, considers individual equipment differences, quantifies risk values, and classifies them, improving the accuracy of early degradation identification and thus enhancing the accuracy of electrical risk monitoring for oil-paper insulated equipment.

The application relates to the technical field of industrial control, in particular to a control method and system of an insulating material production line. The method comprises the following steps: acquiring initial operation data of the insulating material production line in real time; calculating a transient specific energy index in combination with a standard plasticization reference absolute temperature; extracting a pressure change rate by performing smooth filtering on a time differential item of a head melt pressure; deducing a dynamic thinning coefficient in combination with the transient specific energy index, a value at a previous sampling moment, the pressure change rate and the head melt pressure; constructing a state matrix mismatch correction factor based on the dynamic thinning coefficient, a historical maximum thinning limit value of a sliding data window and a standard steady-state thinning reference value; and performing adaptive model predictive control to output an optimal control instruction by using the correction factor to target correct a discrete state space model system matrix. The application can effectively solve the mismatch problem of a static model under a nonlinear mutation condition, improve control precision and reliability, and guarantee stable and efficient operation of the production line.

Embodiments of the present application disclose a fluid steady-state characteristic determination method and related device, the method comprising: obtaining physical properties and state parameters of a fluid in a target system; constructing a fluid dynamics equation according to the physical properties and the state parameters, and discretizing the fluid dynamics equation into a linear equation set, the linear equation set being expressed as a product of a coefficient matrix and a vector corresponding to unknown quantities being equal to a constant vector; constructing a quantum circuit to solve the linear equation set according to a target unitary operator, and obtaining steady-state characteristics of the fluid, the target unitary operator acting on two registers, when a quantum state of one of the registers represents an arbitrary row of the coefficient matrix, the target unitary operator performs a NOT operation on the other register, and when the quantum state of one of the registers represents an orthogonal complement space of an arbitrary row of the coefficient matrix, the target unitary operator does not perform any operation on the other register. By using the embodiments of the present application, the steady-state characteristics of the fluid can be quickly determined.

The invention discloses a quantitative prediction method for an icing load of a power transmission line, and the method comprises the following steps: collecting and fusing multi-source meteorological data: employing a dual-polarization radar to invert the particle size distribution of liquid drops through differential reflectivity, calculating the content of supercooled water through a differential phase, and obtaining an atmosphere liquid water path and a vertical temperature profile; according to the measured wind speed, wind direction and wind shear index, an environment parameter field is constructed, and icing early warning is triggered; conducting wire state parameter real-time sensing: monitoring conducting wire three-axis amplitude and galloping frequency, obtaining conducting wire surface temperature gradient, quantifying damping effect of conducting wire galloping on collision efficiency and providing boundary conditions for a thermodynamic equation; mixed phase state dynamic discrimination: constructing a phase state discrimination matrix based on a combination rule of a temperature interval and droplet particle size distribution; dynamic collision efficiency correction: calculating the dynamic collision efficiency by adopting an unsteady state collision formula; thermodynamics-fluid mechanics coupling calculation is carried out; and ice coating load accumulation and output: calculating the ice coating thickness, mass and mechanical load.

The present application provides a method and device for determining the steady-state frequency response of an MHD angular velocity sensor element. The method comprises: obtaining structural dimension parameters and material property parameters of the MHD angular velocity sensor element in response to a modeling instruction; generating an average magnetic induction intensity of a radial magnetic circuit in a conductive fluid ring in the MHD angular velocity sensor element based on the Maxwell equations according to the structural dimension parameters and the material property parameters; generating an average circumferential velocity of the conductive fluid relative to the magnetic field based on a low magnetic Reynolds number incompressible equation group according to the structural dimension parameters and the material property parameters; generating a frequency response characteristic function of the MHD angular velocity sensor element based on the average magnetic induction intensity and the circumferential average velocity based on the Faraday motional electromotive force method; and solving the frequency response characteristic function to obtain amplitude-frequency response data and phase-frequency response data of the MHD angular velocity sensor element.

The invention relates to the field of automatic control technology, and discloses a system setting value tracking accuracy control method based on variable input, comprising the following steps: establishing a linear time-invariant system model and a steady-state equation of the system under steady-state conditions, obtaining a state variable of the system and an error equation of the state variable of the system under steady-state conditions; obtaining an original controller equation and analyzing it, and when the system parameters of the controlled object are inconsistent with the actual parameters of the system, establishing a control equation of the actual parameters of the system, introducing a negative slope function, establishing a new control function after introducing the negative slope, and establishing a new controller equation based on the control equation of the actual parameters of the system, replacing the actual parameters of the system and the state variables of the system under steady-state conditions, obtaining an optimal control equation and solving it, and substituting the obtained solution into the original controller to realize control of the controlled object; the method greatly reduces the influence of the actual parameters of the system and improves the tracking accuracy of the system for the setting value.

The application discloses a numerical calculation method for a high-temperature and high-pressure flash evaporation process, and comprises the following steps: a Laval nozzle fluid domain model is established, the model is divided into a structured grid to obtain a grid model, the grid model is imported into simulation software, an energy equation is enabled, high-temperature and high-pressure inlet boundary conditions, pressure outlet boundary conditions and wall surface conditions are defined, the dependence of the physical property parameters of water and steam on temperature is written into the simulation software as a user-defined function, solver parameters are set, and a steady-state flow field result is obtained, the steady-state flow field result is taken as an initial condition, a ZGB model considering thermodynamic non-equilibrium effects is selected and activated, transient solution parameters are set, and a transient simulation result is obtained, and the transient simulation result is imported into CFD post-processing software to extract and obtain the physical quantity change curve of a key position. The method can predict a flash evaporation starting position and steam volume distribution, and realizes qualitative and quantitative prediction of flash evaporation under complex working conditions.

The application discloses a kind of regularized constraint heat transfer coefficient dynamic determination method and system.The application introduces sine oscillation in jacket temperature, data is divided into sliding window;Linear model containing low-frequency term and simple harmonic term of the same frequency is constructed in window, and the energy balance equation is established by extracting the same frequency complex amplitude;Further, the least square target function with regularization term is constructed with the estimation value of the previous window as prior, and the non-negative constraint based on the interpolation of the boundary before and after reaction is applied, and the UA dynamic evaluation is realized by cyclic solution.The application effectively decouples non-steady-state drift and noise, suppresses numerical mutation, obtains smoother and more physical law heat transfer coefficient and heat release rate result, and significantly improves the robustness of complex reaction process calorimetry.

The application provides a micro-cantilever generalized parameter inversion method, system and device, relates to the micro-cantilever parameter inversion technical field, and the method comprises the following steps: obtaining the steady-state response data of the micro-cantilever system to be measured at a preset driving frequency as observation data for model training; constructing a PINN model, the input is time, and the output is corresponding predicted displacement; the geometric parameter to be inverted is used as a trainable variable to construct a composite loss function containing data residuals and physical residuals; the model is iteratively trained and inverted to solve; the weights of the model and the geometric parameter to be inverted are jointly optimized until the model converges; and the final learned geometric parameter value in the model is extracted as the actual physical size of the micro-cantilever system. The scheme not only greatly reduces the dependence on experimental data, but also has strong structure generalization ability, and can accurately identify micron-level size deviation caused by process errors and the like through single observation data.

The application belongs to the technical field of engineering simulation data processing, and specifically discloses a multi-physical field iterative coupling prediction method, system, terminal and medium. The method comprises the following steps: based on a prediction batch input, initializing the state of a to-be-predicted object, and constructing a structured feature representation for multi-physical field prediction; constructing a temperature prediction model and a pressure prediction model which are independent of each other; performing multi-round prediction update on the temperature physical field by using the temperature prediction model, and dynamically adjusting relevant state parameters according to the predicted state of the temperature physical field in the prediction update process to obtain a stable temperature physical field prediction state; on this basis, performing prediction processing on the pressure physical field by using the pressure prediction model to obtain a pressure physical field prediction result corresponding to the temperature physical field prediction state, and outputting a multi-physical field steady-state prediction result. By introducing the multi-physical field iterative coupling prediction mechanism, the physical consistency and stability of the multi-physical field prediction result are improved.

This invention proposes a method and system for obtaining the trajectory of a periodic time-varying system based on Chebyshev placement, belonging to the field of power electronics technology. The method includes: establishing a periodic boundary value problem model of the periodic time-varying system, determining the system period and the number of placement points; performing time-scale mapping on a single-period interval, selecting Chebyshev placement points and constructing a spectral differential matrix; applying system dynamic constraints at each placement point, discretizing the differential equations into a system of nonlinear implicit algebraic equations; introducing periodic closure constraints to form a closed nonlinear algebraic equation system; and using an internal and external iterative strategy to solve the closed equation system, outputting the steady-state periodic discrete trajectory. This invention, by placing Chebyshev points within a single-period interval and constructing a spectral differential matrix, directly transforms the differential equations into a system of algebraic equations, avoiding long time-domain integration, and possesses advantages such as high computational efficiency, fast convergence speed, good numerical stability, and strong engineering feasibility.

The invention provides a hot water force multi-field monitoring analysis method and system suitable for a TEHB test system, and the method comprises a model framework building step, a steady-state initial field solving step, a hot water force coupling solving step, and a multi-field response data collection and recording step. The invention further provides a hot water force multi-field monitoring and analyzing system suitable for the TEHB test system, a three-dimensional model containing the six-direction waveguide rod and the rock sample is established, a mechanical, seepage and temperature steady-state initial field before impact loading is obtained, hot water force coupling dynamic calculation is carried out under the action of triaxial six-direction synchronous impact, and the test result is obtained. And curves and statistical indexes of key results such as stress, fracture, pore pressure, temperature and the like are automatically output. According to the invention, the impact process simulation can be realized under the hot water-force coupling loading condition, and multi-field response data can be monitored and analyzed, so that the dynamic mechanical behavior of the rock under the hot water-force coupling effect can be revealed, and a basis is provided for the scientific design of deep engineering.

The application discloses a network-constructed energy storage capacity configuration optimization method and system, belongs to the technical field of power system planning and operation control, and substitutes initial capacity into a constructed multi-time scale nonlinear differential algebraic equation model to perform time domain simulation until each state variable in the network-constructed energy storage system reaches a periodic steady state, and the periodic steady state trajectory of each state variable is obtained; according to the periodic steady state trajectory, a state transition matrix in a fundamental period is obtained, and Floquet characteristic indexes are determined based on Floquet theory; the real part of the Floquet characteristic indexes is taken as a system electromagnetic stability index; the network-constructed energy storage capacity is gradually increased from the initial capacity through a search step, and when the index is greater than a preset safety threshold for the first time, the capacity value corresponding to the last search step is taken as the maximum allowed network-constructed energy storage capacity satisfying the electromagnetic dynamic stability safety threshold. The method can optimize the network-constructed energy storage capacity configuration under the premise of ensuring the system electromagnetic dynamic stability.

The present application belongs to the field of vehicle control technology, and relates to a control method for transient switching process of vehicle extreme working condition and application thereof. When the vehicle is in transient switching process, the vehicle motion state is represented as a coordinate point in a phase plane, i.e. a drift point. A steady-state equation of the drift point is constructed according to a vehicle dynamics equation. A controllable domain under steady state, i.e. a value boundary of the drift point, is solved through a control variable of the steady state. A trajectory searching method based on graph theory is used to find a moving trajectory in the phase plane for moving from a current drift point to a target drift point in the shortest time. An optimal trajectory adjustment control strategy is used to adjust and control an actual moving trajectory so as to make it approach the moving trajectory, so as to control the vehicle in the extreme working condition to a normal state or a drift state. The present application solves the problems of nonlinear solving difficulty and slow switching speed, and can be applied to drift control.

The invention discloses a power system equivalent damping identification method based on an improved grey wolf algorithm, and relates to the field of power system parameter identification, and the method comprises the steps: building an SFR improved model; six unknown parameters in the SFR improved model are classified, weighted summation is adopted for a system equivalent inertia time constant, a prime mover high-pressure cylinder output power proportion and a prime mover reheating time constant to obtain a fitting value, a parameter constraint relation of a final steady-state value based on power disturbance and frequency deviation is established to determine an equivalent damping coefficient, and the equivalent damping coefficient is calculated. According to the inertia time constant of the speed regulator and frequency response data and disturbance power measured based on a wide area measurement system, an improved grey wolf algorithm is adopted for optimizing and calculating an equivalent damping coefficient, model parameters are determined by means of equivalent calculation, steady-state data extraction, parameter identification and the like, the improved model parameters are reasonable in setting, and the stability is high. Frequency response can accurately represent key indexes of system frequency, and the model precision is remarkably improved compared with a classic model.

The invention provides a steady-state quantum turbulence generation method and a steady-state quantum turbulence generation system capable of guaranteeing particle number conservation. The method comprises the following steps: constructing an evolution model of the quantum fluid system, wherein the evolution model is obtained by introducing an external driving item and a particle number conservation dissipation item based on a Gross-Pitaevskii equation; the external driving item is an additional external potential of spatio-temporal variation and is used for injecting energy into the system; the particle number conservation dissipation item depends on the time change rate of the particle number density and is used for dissipating the energy of the system; the external driving item and the particle number conservation dissipation item are configured to keep the total particle number conservation of the system; and performing time evolution on the quantum fluid system based on the evolution model until the system reaches a steady-state quantum turbulence state of total kinetic energy dynamic balance. According to the method, the loss of chemical potential compensation particles does not need to be adjusted, quantum turbulence structures of different scales can be stably generated and regulated, and the physical self-consistency and long-term stability of the quantum fluid evolution process are guaranteed.