385 results about "Real-time simulation" patented technology

The invention relates to a ship automatic berthing safety control system, and belongs to the technical field of port ship operation safety control. The system comprises four core modules which are sequentially connected to form closed-loop control: a situation synchronous sensing module generates total-factor dynamic attitude information through space-time synchronization and data fusion of a ship-shore inertial unit; the digital twin deduction module performs real-time simulation based on a ship six-degree-of-freedom motion model, and predicts a ship motion track and berth acting force in a prospective manner; the safety decision and early warning module compares the prediction track with the safe berthing corridor through a track-berthing force coupling algorithm, and outputs a cooperative control strategy; and the multi-terminal cooperative execution module converts the strategy into an instruction and synchronously distributes the instruction to a tug, a navigation bridge and a wharf system. Automatic closed-loop control of the whole process from sensing, prediction, decision making to execution is achieved, and the safety, accuracy and operation efficiency of ship berthing are effectively improved.

The invention relates to the technical field of intelligent water affair and urban water supply system informatization, in particular to a water supply pipe network hydraulic model calibration and leakage locating method and system, and the method comprises the steps: obtaining the pressure and flow data of a plurality of monitoring points in a pipe network in real time; taking the model as a boundary condition to drive a hydraulic model to carry out real-time simulation, and calculating a theoretical value; calculating a residual error between a theoretical value and an actual value of the monitoring point; judging a triggering model calibration event or a leakage suspicion event based on a residual error abnormal mode; if calibration is triggered, inverting and updating global parameters of the model through an optimization algorithm to realize self-calibration; if leakage is triggered, a suspected area is determined by combining pressure space distribution analysis, and a leakage pipe section is accurately positioned through analog simulation and correlation analysis. Through closed-loop feedback of real-time data and the model, the model can adapt to changes of a pipe network system, dynamic self-calibration of the water supply pipe network hydraulic model is achieved, and the problem of precision attenuation of a traditional static model is solved.

The invention relates to the field of environment management, and discloses a watershed digital twinning environment real-time simulation and interaction platform fusing cloud edge collaboration and intelligent modeling, and the platform comprises the steps: carrying out the dynamic collection of the Yangtze River and Yellow River watershed, and generating environment state information organized according to the temporal-spatial resolution; associating the generated environment state information with multi-source environment data to form a multi-source knowledge basis of the drainage basin pollution field; establishing a rule knowledge base covering pollution identification, early warning and prevention and control business processes by utilizing a generative knowledge representation method, and generating a pollution event candidate identification result; carrying out fusion calculation on the pollution event candidate recognition result and multi-source heterogeneous data, constructing a digital twin simulation model, and eliminating data islands between modules and data sources; and executing linkage calculation on the pollution area and the risk node calibrated in the digital twinborn simulation model, generating environment state interaction information and synchronously updating the environment state interaction information to the digital twinborn environment. The method has the advantage that the regional water environment risk prevention and control capability is improved.

The invention relates to the technical field of wind driven generator control, in particular to a thermal management system and method for a wind driven generator, and the system comprises a data collection layer, a prediction module, a digital twin model, an intelligent control and diagnosis engine, and a heat dissipation execution mechanism. In the prior art, an open-loop or simple feedback control scheme based on a real-time temperature threshold value is mainly adopted, the problem of response lag exists, and all heat dissipation parts always work independently and lack cooperation, so that the energy efficiency is low; according to the invention, a closed-loop intelligent thermal management scheme based on a digital twin model is adopted, and real-time simulation and future state prediction are carried out by constructing virtual mapping of a generator thermal system, so that a control system can actively and cooperatively manage all heat dissipation resources according to a simulation result; the method has the core advantage of converting passive into active, and can intervene in advance before excessive accumulation of heat, so that collaborative optimal control of all parts of the system is realized, and the accuracy, timeliness and overall energy efficiency of heat management are remarkably improved.

The invention discloses an intelligent manufacturing real-time decision-making method and system based on digital twinning, and relates to the technical field of intelligent manufacturing. Comprising the following steps: S1, collecting multi-source operation data in a physical production system in real time; s2, dynamically constructing and updating a digital twinborn model of the physical production system based on the multi-source operation data acquired in real time; and S3, based on the digital twin model, monitoring the operation state of the physical production system in real time. According to the method, the multi-source operation data of the physical production system are collected in real time, and the digital twin model is dynamically updated, so that no lag deviation between the model and the physical system is ensured; when a dynamic disturbance event is identified, event-driven real-time simulation and predictive analysis are started immediately, delay caused by traditional batch processing is avoided, and disturbance influence can be accurately evaluated in combination with historical data and expert experience; and then an optimal decision scheme is generated and screened in real time through a multi-objective optimization algorithm.

The invention belongs to the technical field of wind power generation, and particularly relates to a fault diagnosis and early warning method and system for a wind power plant, and the method comprises the steps: collecting the state data of a plurality of physical fields through a plurality of types of sensor arrays disposed at key parts of a fan; performing preprocessing and feature extraction on the data to obtain high-dimensional feature data; driving the field-level digital twinborn model to perform real-time simulation based on the high-dimensional feature data, and determining an initial fault recognition result and severity by comparing a simulation predicted value with actual sensing data and combining with an unsupervised anomaly detection algorithm; a diagnosis result is calibrated through multi-modal high-dimensional feature data fusion; predicting the remaining useful life of the key component based on the fault severity and the evolution trend thereof, and generating a collaborative operation and maintenance decision by using a multi-objective optimization algorithm; and an operation and maintenance decision is automatically executed through a closed-loop feedback execution mechanism. According to the invention, the accuracy of fault diagnosis and early warning of the wind power plant is improved.

The invention relates to the technical field of power distribution network monitoring, in particular to a power distribution cabinet line intelligent detection method and system, and the method comprises the steps: collecting node voltage, phasor current and active / reactive power of each power distribution cabinet, attaching a sampling period and a quality identifier, and carrying out the arrangement according to a timestamp; carrying out edge calculation on harmonic waves, flicker, unbalance, missing measurement compensation and initial estimation, and generating a straight-through UDP stream and a storage stream; a real-time interface is aligned and fused with a topology version according to a unified time reference, state estimation is carried out, and a node initial value set is output; s4, according to the initial value and topological modeling node digital twinning (index recovery load), obtaining online parameters through four-stage sub-step discrete + UKF joint estimation; accessing a real-time simulation platform through HiL, and recharging in the same period; a variable damping impedance stable interface is adopted, and when consistency and a threshold value are met, a digital snapshot containing an online parameter, a steady-state quantity and a transient abstract is generated. According to the method, low time delay of measurement alignment, credible state estimation, digital twinborn self-adaption, hardware-in-loop stability and verifiable result release can be realized, so that the fault detection, positioning and evaluation capabilities of the power distribution network are improved.

The invention belongs to the field of electromechanical comprehensive thermal management, and particularly relates to a real-time analogue simulation method and system for electromechanical comprehensive thermal management of an airplane. The method comprises the following steps: constructing a comprehensive thermal management environment model of an aircraft operation environment; constructing a comprehensive thermal management system model; performing real-time coupling on the comprehensive thermal management environment model and the comprehensive thermal management system model, and simulating a real-time comprehensive thermal management process of the airplane based on a comprehensive thermal management strategy to obtain a real-time simulation result; and performing optimization iteration on the comprehensive thermal management system model according to the real-time simulation result. According to the method, through accurate simulation of the electromechanical comprehensive thermal management process of the airplane, powerful support can be provided for performance optimization, safety improvement and cost control of the airplane.

The invention belongs to the technical field of automobile testing, and particularly discloses a digital twinning-based automobile instrument testing method, which comprises the following steps of: automatically generating a structured test case through a large language model, constructing a double-digital twinning architecture by relying on a high-fidelity rendering engine and a real-time simulation engine, and realizing synchronization of a virtual model and a physical instrument; multi-modal data are collected through a multi-sensor array, and defect intelligent analysis and grade judgment are completed in combination with a large language model; and test strategy self-optimization is realized through reinforcement learning based on historical test data. According to the invention, a double-engine architecture in which a high-fidelity rendering engine and a real-time simulation engine cooperatively work is adopted, and the requirements of large-scale scene and refined rendering are met at the same time. And seamless switching and data fusion between the double engines are realized through the scene transformation matrix, so that the consistency of a virtual environment and a physical entity is ensured. Meanwhile, a large language model is introduced into a test case generation and result analysis link, and natural language understanding level test script generation and anomaly analysis are achieved.

The invention discloses a simulation method and system for improving the simulation efficiency of a PIN diode, and belongs to the technical field of semiconductor device simulation, and the method comprises the steps: firstly, employing a hash table data structure to optimize the preprocessing process of a semiconductor physical model time domain numerical method, and remarkably improving the parameter preprocessing efficiency; carrying out bandwidth compression optimization on the sparse matrix in combination with an inverse Cuthill-Mckee matrix reordering algorithm; and secondly, constructing a parallel iteration solver architecture to realize efficient distributed solution of a large nonlinear matrix equation. Through cooperative application of the method, the overall calculation efficiency of a PIN diode numerical simulation program is improved by more than three times compared with that of traditional commercial simulation software COMSOL on the premise that the calculation precision is kept, the industrial problem that the simulation timeliness of a semiconductor device is limited is effectively solved, and an innovative technical path is provided for high-precision real-time simulation. The method has important application value in the fields of power device design, integrated circuit simulation and the like.

The invention provides a system platform and method for checking adjustment characteristics of a control system based on semi-physical simulation, and belongs to the technical field of power system control equipment detection. The system comprises an all-digital real-time simulation system (ADPSS), a water turbine governor to be tested, a physical interface communication module, a wave recording device and a signal interaction module. A full-electromagnetic example model constructed based on PSASP is built in the ADPSS, a closed-loop detection environment is constructed through the physical interface communication module and a water turbine governor to be detected, bidirectional signal transmission is achieved through the signal interaction module, and key parameters are recorded through the wave recording device. The method comprises the steps of simulation environment establishment, signal interactive transmission, multi-dimensional detection and check and result judgment and output. According to the method, multi-dimensional checking of the speed regulator acquisition and display function, the transfer function consistency, the grid-connected performance and the like and power grid stability influence verification can be completed without field installation, the coverage scene is comprehensive, the checking precision is high, and the method is suitable for performance detection of different types of speed regulators and has remarkable practical value.

The invention provides an urban water supply system anti-seismic analysis method based on a multi-fineness digital twinborn model, and belongs to the technical field of intelligent disaster prevention and digital twinborn of urban infrastructure systems. Constructing a topological network model and a hydraulic model of the city-level pipe network; constructing a multi-fineness parameterized numerical model library, and designing a dynamic scheduling engine based on event response; constructing a bidirectional data conversion interface and a unified semantic framework, and constructing a multi-fineness digital twin model; performing simulation by using the multi-fineness digital twin model to obtain a real-time simulation result; based on the real-time simulation result, the comprehensive state of the urban water supply system is visualized, an emergency decision is made, and anti-seismic analysis of the urban water supply system is completed; the problems of precision and efficiency imbalance, collaborative decision-making obstacle and serious lagging of disaster scene response existing in anti-seismic analysis of an existing urban water supply system are solved.

The invention discloses a scoliosis neuromuscular rehabilitation system based on a brain-computer interface and digital twinning, and the system comprises a multi-mode sensing module which is used for synchronously collecting a neurophysiological signal, a muscle electrical activity signal and a motion posture signal of a user; the intelligent processing and simulation module is used for carrying out fusion processing on the multi-modal signals, decoding the motion intention of the user and carrying out real-time simulation prediction on a biomechanical effect generated by the motion intention based on a personalized digital twinborn model of the user; and the decision and feedback module is used for generating and executing a personalized feedback instruction according to the decoding result and the simulation prediction result of the motion intention. The invention belongs to the technical field of medical rehabilitation engineering and biomedical engineering, and particularly provides a neuromuscular function remodeling method which is capable of directly providing a scoliosis patient with biomechanical accuracy, real-time interactivity and individual adaptability from a neural control source by constructing an integrated rehabilitation system.

The invention discloses a digital twinborn driving intelligent management method for service life optimization of a hybrid energy storage system, and relates to the technical field of intelligent management of the hybrid energy storage system, and the method comprises the steps: obtaining real-time operation data and future working condition prediction data of the hybrid energy storage system, and building and updating a digital twinborn body based on a mechanism model and the real-time operation data; estimating the real-time state of the hybrid energy storage system in the simulation environment of the digital twin; life damage is predicted based on future working condition prediction data; according to a real-time state estimation result and a life expectancy damage result, an optimal power distribution strategy is solved by taking minimization of system comprehensive life damage as an optimization target, real-time simulation verification is carried out, and an optimization control instruction is generated after verification is passed; and collecting feedback data after the hybrid energy storage system executes the optimization control instruction, and carrying out iterative updating on the digital twin model and related parameters according to the feedback data. Therefore, the overall service life is prolonged to the maximum extent on the premise of guaranteeing system power balance.

The invention discloses an asynchronous intelligent control method for a real-time simulation system. The asynchronous intelligent control method is based on a simulation environment construction module, an asynchronous feedback acquisition module and an intelligent control decision module. The simulation environment construction module is used for loading nodes, channels and model configuration files and defining simulation operation parameters; the module supports node starting, stopping and parameter adjusting operation, and an executable interface is provided for subsequent intelligent control; the asynchronous feedback acquisition module is used for periodically acquiring node states, link quality, throughput rate and time delay indexes through a probe module in a simulation running process, and writing the node states, the link quality, the throughput rate and the time delay indexes into a state cache in an asynchronous mode; the intelligent control decision module is used for carrying out analysis and strategy reasoning on the asynchronously acquired state by utilizing a reinforcement learning or deep reinforcement learning algorithm; the intelligent agent generates an action decision according to the current state, and outputs a node parameter adjustment instruction, an interface control instruction, a power configuration instruction or a flow scheduling control instruction to the environment construction module; the decision-making process can be continuously carried out in simulation operation, and dynamic self-adaptive optimization is achieved.

The invention discloses an intelligent operation and maintenance system and method based on flow battery digital twinning, and relates to the technical field of flow battery energy storage. According to the method, through multi-source heterogeneous data fusion, electrical, fluid and environmental parameters and image data are collected and uniformly processed; constructing a mixed index database to add spatio-temporal information; optimizing the neural network through a PSO-BP algorithm to generate a space fusion model; constructing a multi-physics field real-time simulation model by combining data driving and a mechanism model; and finally, dynamic interaction and fault prediction of the physical and virtual systems are realized through three-dimensional virtual mapping. The system comprises a data preprocessing module, a mixed index database and the like. Unified fusion and efficient management of multi-source heterogeneous data are achieved, and the problem of data fragmentation is solved; a multi-physical-field state is simulated in real time through a digital twinning technology, and a fault is accurately predicted; and preventive maintenance is supported, the operation and maintenance cost is reduced, and the safety and economic benefits of the flow battery system are improved.

The invention discloses a real-time simulation and prediction system for river water flow based on digital twinning, and the system comprises the following modules: a multi-source data synchronous collection module which is used for constructing a core hydrological data flow; the data preprocessing module is used for outputting a core driving data stream; the hydrodynamic digital twinning construction module is used for establishing a water level difference driven twinning model; the real-time simulation and assimilation calibration module is used for performing real-time calculation by taking the core driving data flow as a boundary condition and outputting a real-time simulation twin body; the intelligent rolling prediction module is used for generating a multi-section prediction sequence by utilizing an improved Seq2Seq-Attention model based on the real-time simulated twinborn body and the core driving data stream; and the visualization and early warning output module is used for presenting the prediction result and triggering early warning. According to the method, a physical mechanism and a data model are fused, and through dynamic calibration and self-adaptive prediction, the precision, the stability and the prediction period of river flow prediction are remarkably improved.

The invention relates to the technical field of ocean engineering operation motion modeling and control, and particularly discloses a method and a system for calculating influence of dynamic response of a separation supporting device and a buffer coupling device on a ship pose in a floating support installation process. The method comprises the following steps: acquiring initial position information of a separation support device and a buffer coupling device at a previous moment; acquiring vertical position and attitude information of the dynamic positioning ship and the upper module; calculating the supporting force of the separation supporting device and the buffer coupling device at the current moment; calculating the vertical position and attitude information of the upper module and the dynamic positioning ship at the current moment based on the supporting force and the external ballast water load; outputting relevant parameters and judging whether the installation is completed or not. According to the method, a multi-degree-of-freedom coupling dynamic model is constructed, high-precision real-time simulation of device dynamic response and ship motion attitude in the continuous unsteady-state load transfer process is realized, key parameter monitoring and risk early warning are provided for floating mounting operation, and the operation safety and efficiency are improved.

The invention relates to the technical field of three-dimensional scene modeling, in particular to a dynamic event scene reproduction method and system and electronic equipment, and the method comprises the steps: collecting scene multi-modal data, and generating a three-dimensional static scene model; generating a static object supplementary description model and a dynamic object motion prediction model by using a large language model; fusing the text semantic features and the image visual features, and integrating with a dynamic object motion prediction model to generate a total behavior prediction model; motion planning and real-time simulation are carried out on a virtual role, and a virtual role model with intelligent behavior ability is output; combining the three-dimensional static scene model, the static object supplement description model, the total behavior prediction model and the virtual role model to generate a complete dynamic event scene; according to the invention, through the innovative architecture of dynamic and static separation modeling and large language model driving, the bottleneck of static property and manual dependence of the traditional scene modeling technology is broken through, and efficient and real dynamic scene automatic reproduction is realized.

The invention discloses a hierarchical simulation modeling system for a new energy station cluster and a real-time verification method, belongs to the technical field of new energy power generation simulation, and solves the problems of high simulation calculation complexity, difficulty in real-time operation and closed-loop interaction verification with an external control system of a large-scale new energy station cluster. According to the technical scheme, the method comprises the steps that a digital dynamic real-time simulation platform configured with a multi-thread parallel computing architecture is adopted, and a new energy station detailed model comprising a wind power generation unit model, a photovoltaic power generation unit model, an energy storage power generation unit model and a current collection system model is deployed on the platform; generating an independent wind speed sequence for each fan through a wind resource distribution model; and constructing a large-base station cluster model composed of a plurality of station simplified models through aggregation equivalence. The system is mainly used for real-time simulation testing of a large-scale new energy base and closed-loop verification of a control system.

Disclosed in the present invention are an FPGA-based simulation method for a high-voltage direct-connected energy storage system, and an apparatus. A power unit of the high-voltage direct-connected energy storage system is divided into an H-bridge and an energy storage unit part, the H-bridge and a grid-side topology are placed in an FPGA for simulation, an energy storage battery branch part is placed in a CPU for simulation, and the FPGA and the CPU exchange submodule voltage and current information by means of a PCIE bus. The FPGA establishes a Thevenin model of a single high-voltage direct-connected energy storage system submodule, performs algebraic superposition by using the series relationship of submodules, and calculates a submodule capacitor voltage, a submodule terminal voltage, and a bridge arm voltage; an equivalent model and the grid-side topology run with a simulation step size of 1µs in an FPGA of a simulator; the energy storage battery branch runs in a CPU of the simulator, and the CPU supports a user-defined energy storage battery model; and the respective advantages of a real-time multi-core processor and an FPGA are fully combined, so that the high-voltage direct-connected energy storage system with any number of submodules can be precisely simulated with a simulation step size of 1µs in real time on the FPGA.

The invention discloses an intelligent state monitoring method and system based on petrochemical equipment, and relates to the technical field of intelligent state monitoring, and the method comprises the steps: constructing a petrochemical equipment digital twin based on the parameters and physical characteristics of target petrochemical equipment, and collecting multi-source time sequence data; inputting the multi-source time sequence data into the digital twin of the petrochemical equipment, and performing real-time simulation to obtain theoretical operation state data; and based on the multi-source time sequence data and the theoretical operation state data, obtaining deviation data between the measured value and the theoretical value, and updating the parameters of the digital twin of the petrochemical equipment by using the deviation data to obtain equivalent real operation state data. Through deep fusion of a mechanism model, data driving and an intelligent algorithm, accurate prediction of equipment life, effective distinguishing of fault types and automatic generation of a diagnosis report are realized, and the industrial problems of high false alarm rate, poor interpretability and lack of predictability in the prior art are fundamentally solved.

The invention discloses a relay protection plug-in automatic simulation test method and system based on a universal backboard. The method comprises the steps that a relay protection plug-in to be tested is connected to the universal backboard; semantic information in the relay protection configuration file of the plug-in is analyzed and extracted, a corresponding test data model is dynamically constructed, and a matched operation scheme is generated; on the basis of the operation scheme, real-time simulation parameters are set, and a multi-dimensional excitation signal is applied to the plug-in through the universal backboard so as to simulate various operation conditions of the power system; and acquiring response data of the plug-in under the excitation signal through the universal backboard, and comparing the response data with an expected response to obtain a test result. According to the invention, plug-in level universal testing is realized, special debugging instruments of various models can be replaced by a single testing system, and the operation and maintenance efficiency and the spare part management level of the relay protection device are remarkably improved.

The invention discloses a digital twinning system of an air-breathing strong precooling engine test bed, the system comprises a real-time simulation part and a performance prediction part, the real-time simulation part carries out real-time analogue simulation on the test process through modular modeling, steady-state / dynamic calculation and physical test bed data coupling; according to the performance prediction sub-part, a reference model and an actual state model are established based on a long-short-term memory neural network, and performance prediction is conducted on the performance of the strong pre-cooling engine. The digital twin system provided by the invention is convenient for variable working condition adjustment, parameter adjustment boundary exploration and error risk and debugging cost reduction, so that a debugging rule can be summarized in a test bed debugging process, a debugging scheme of a physical test bed is assisted to be formulated, and a safe and efficient test process is ensured.

The invention relates to the technical field of motor protection, and discloses a high-efficiency motor operation safety control method, which comprises the following steps: S1, based on an embedded sensor, adopting a multi-source data fusion algorithm, and through Kalman filtering and normalization processing, collecting and preprocessing operation data of a motor in real time, generating preprocessed multi-dimensional sensor data, and sending the preprocessed multi-dimensional sensor data to a server; and S2, on the basis of the preprocessed multi-dimensional sensor data, a physical model driving method is adopted, and a digital twin model of a motor is updated through a real-time simulation engine, so that a current motor state is mapped, and high-fidelity digital twin state mapping is generated. By collecting multi-source sensor data in real time and applying Kalman filtering and normalization processing, the data quality and consistency are remarkably improved, and a reliable foundation is laid for subsequent analysis; high-fidelity digital twinning state mapping is constructed based on physical model driving and a real-time simulation engine, dynamic and accurate representation of multiple physical field states in the motor is realized, and the state sensing depth is enhanced.

The invention discloses a method for acquiring optimal measurement conditions of building room temperature monitoring. According to the method, a discrete coordinate radiation model is set, a sun tracking function is started at the same time, and wall mixed thermal boundary conditions are considered. Factors influencing the accuracy and stability of room temperature monitoring, such as temperature measurement distance, time, sunshade condition, temperature measurement position, weather condition, window opening and closing, outdoor temperature and room characteristic factors, are explored, so that the influence rule of different factors on the room temperature monitoring of the building is provided. According to the method, accurate modeling is performed according to thermodynamic behaviors in a complex building environment, and complex factors, including thermal conductivity of building materials, indoor air flow and heat source distribution, suffered by the room temperature of a building are considered; under different environmental conditions, dynamic characteristics of a building room temperature change rule are considered, a monitoring scheme is dynamically adjusted based on real-time simulation data to obtain an optimal measurement condition, and the complexity of the system is reduced in a real-time feedback process.

The invention discloses a semi-physical simulation system of an underwater vehicle and a control method of the semi-physical simulation system, and relates to the technical field of simulation control. The control system comprises a simulation tester, a depth simulator, a three-axis simulation turntable, a real-time simulator, a rudder load simulator, a visual simulation system, a data acquisition and processing subsystem, a depth sensor, an airborne computer, an inertial unit system, an inertial navigation exciter, a gyroscope and a steering engine. In the integrated navigation system, a non-real-time part comprises a turntable control computer and a triple master console; the real-time part comprises a dynamics kinematics model, a three-axis simulation turntable, a GPS / DVL simulator, an electric thrust driving simulator, a depth simulator and a surge interference model; the underwater self-propelled body control system comprises a strapdown inertial navigation assembly, a control management center, a depth sensor, a rudder feedback potentiometer and a steering engine. The method can be used for semi-physical simulation of an underwater vehicle, and can simulate a navigation environment with variable depth.

The invention provides a semi-physical simulation test method, device and equipment for a wind-heat-electricity linkage system and a storage medium. The method comprises the steps that a wind generating set virtual model is built through Bladed software, and a thermodynamic system virtual response model is built; a wind-heat-electricity linkage control strategy is implanted into the PLC, and a corresponding control signal is transmitted to the PLC; fan and thermal control signals are transmitted to the Bladed hardware test module through a PLC communication interface based on a PLC private protocol of a TCP; through the Bladed hardware test module, a fan control signal is transmitted to the wind generating set virtual model, and a thermodynamic control signal is transmitted to the thermodynamic system virtual response model; different wind conditions are given in the virtual model of the wind generating set, so that the wind-heat-electricity linkage system is subjected to real-time simulation operation, and simulation test results under the different wind conditions are obtained. According to the invention, real-time simulation testing of different working conditions of the wind-heat-electricity linkage system is realized.

The invention relates to a rapid calculation method and system for a space magnetic field of a circular coil. The method comprises the following steps: converting an integral expression of a Biot-Savart law into a closed analytical solution containing first and second types of complete elliptic integrals; on the basis of an analytical expression of elliptic integration, the magnetic field intensity and direction generated by the coil at any point in the space can be efficiently and precisely calculated, and the defects that traditional finite element simulation calculation is complex, consumed time is too long, and efficiency and precision of a direct numerical integration method are difficult to consider at the same time are overcome. The method is particularly suitable for application scenes such as WPT system design, multi-transmitting-coil amplitude-phase control optimization and real-time simulation which need to carry out rapid and frequent calculation on the magnetic field. According to the method, full-automatic rapid calculation from physical parameter input to magnetic field result output is achieved, the core advantage of the method is that an analytical formula is utilized, the tedious process of numerical simulation and integration is avoided, and the calculation efficiency is remarkably improved while high precision is guaranteed.

The invention discloses a high-speed aerodynamic derivative analysis modeling method and system based on symbolic regression, and belongs to the technical field of aircraft aerodynamic modeling and artificial intelligence cross, and the method comprises the steps: obtaining an aerodynamic data set of a high-speed aircraft, and carrying out the preprocessing; defining grammar for generating candidate symbol expressions and constructing an expression tree; modeling based on the training set by adopting a layered symbol regression framework to obtain an analytical model; the prediction precision of the analytical model is verified on the test set, and physical consistency analysis is carried out; carrying out uncertainty quantification on the analytical model to obtain predicted uncertainty estimation of the analytical model; and finally, outputting an analytic model in a mathematical expression form for describing the relationship between the aerodynamic derivative and the flight state variable and uncertainty estimation of the analytic model. The method overcomes the defects of a traditional method in precision, generalization and interpretability, realizes full-automatic efficient modeling from data to the analytic model, and improves the modeling efficiency. The method is suitable for control design, stability analysis and real-time simulation of the high-speed aircraft.