1256 results about "Systems simulation" patented technology

Disclosed in the present invention are a fault identification method and system based on the operating condition of a continuous system in an open-pit mine. The method comprises: establishing a simulation model for a continuous system in an open-pit mine, and monitoring device data in real time; pre-processing the data, and performing potential fault identification; on the basis of a system pressure change rate and an adaptive adjustment mechanism of the continuous system in the open-pit mine, optimizing fault identification output; and designing a fault response and real-time adjustment mechanism to prevent fault occurrence. The fault identification method and system based on the operating condition of a continuous system in an open-pit mine provided in the present invention improve the speed and accuracy of fault diagnosis, particularly the rapid processing capability for complex data relationships. A breakthrough is achieved in fault prevention, thus enabling early warning and adaptive adjustment to be implemented before faults occur. Thus, the stability and safety of continuous systems in open-pit mines are significantly improved, and a more efficient technical solution is provided for operation management of modern open-pit mines.

A method for conditioning and maintaining power with predictive load compensation using an uninterruptible power supply system is disclosed. The method includes measuring an electrical input from a primary power supply using analog sensors and transmitting the input through an impedance to introduce a controlled delay. During the delay, input parameters and downstream system effects are determined based on telemetry sensor data. Digital identities are generated for the electrical input and the downstream load and compared to a stored digital identity representing historical conditions. Using the comparison, a system simulation is performed with analog twinning to predict downstream system responses. The predicted response is used to adjust a power converter parameter, modifying the electrical input to an intermediate output that compensates for voltage fluctuations and harmonic distortions. A secondary power supply with a bidirectional high-discharge battery supplements or stores energy as needed, ensuring stable power delivery to the downstream load.

A watershed pollution control measures optimization method employing response surface methodology coupled with a genetic algorithm, the method relating to the cross-disciplinary field of environmental engineering, environmental system simulation and prediction technology, and computer technology. The present invention solves the problem of low optimization efficiency in existing optimization methods. The invention comprises: by using known data, establishing a geographic database for an area; by using the geographic database, calculating a single load of each pollution source, and accordingly calculating the load reduction amount of each pollution source in a single control measure scenario; calculating the total nitrogen pollution load reduction rate and the total phosphorus pollution load reduction rate, and computing the total economic benefit in the single control measure scenario; setting the maximization of the economic benefit, total nitrogen load reduction rate, and total phosphorus load reduction rate as objectives, and establishing a regression function by adopting response surface methodology; and by adopting an NSGA-II genetic algorithm, performing multi-objective optimization on the regression function, and selecting an optimal management measure for a watershed to undergo pollution control. The present invention is suitable for optimizing pollution control measures for a watershed.

The invention provides a water conservancy construction progress intelligent management method and system. Wherein hydraulic engineering project plans are collected, dynamic changes in a life cycle are obtained through an integrated building information model technology, and a hydraulic engineering construction progress management framework is generated; extracting multi-source heterogeneous data, performing cross-modal information integration by applying a multi-modal fusion network algorithm, evaluating specific influence of external environment factors by adopting a causal forest technology, and generating a water conservancy construction progress and risk early warning report; establishing a kinetic equation by applying a graph neural differential equation algorithm, performing dynamic system simulation, and constructing a virtual water conservancy construction environment by adopting an enhanced digital twinborn simulation technology to capture construction efficiency and resource utilization conditions and generate a water conservancy construction resource allocation optimization report; and a lean six-sigma methodology is introduced to set a lean improvement plan, project feedback is collected, and a water conservancy construction progress intelligent management scheme is generated. According to the technical scheme provided by the invention, the intelligent level of water conservancy construction progress management is remarkably improved.

The invention provides a multi-agent control system based on a large language model. The system comprises an analogue simulation subsystem and a coordination control subsystem. The analogue simulation subsystem comprises a data acquisition module, an initial reward function generation module, an error correction module, a dense reward function generation module and a strategy network updating module, wherein the data acquisition module is used for acquiring a multi-agent reinforcement learning training code; the initial reward function generation module is used for generating an initial reward function code; the error correction module is used for generating executable reward function codes; the dense reward function generation module is used for generating dense reward function codes; and the strategy network updating module is used for obtaining the strategy network with the maximized reward. The coordination control subsystem comprises a data collection module and a strategy distribution module; wherein the data collection module is used for receiving observation data; and the strategy distribution module is used for guiding multiple agents to execute a control task by adopting a strategy network generation action for maximizing rewards based on the observation data.

The invention discloses a wind power grid-connected oscillation suppression method and system based on a self-adaptive damping controller, and relates to the technical field of oscillation suppression of a power system. According to the method, a self-adaptive damping controller structure is designed, and parameter setting is completed; then building a wind power grid-connected system simulation model; after voltage signals are collected, an FFT processing method is used for identifying oscillation frequency, and whether an unstable oscillation mode exists in the system or not is judged; if unstable oscillation exists, a self-adaptive damping controller is connected between the wind power plant side and the power grid side; the self-adaptive damping controller filters out signal components causing system oscillation and performs phase modulation; a signal component generated by the self-adaptive damping controller is injected into the power grid and counteracts with an original signal, and oscillation suppression is achieved. According to the self-adaptive damping controller designed by the invention, the oscillation frequency identification module and the phase shift parameter calculation module are introduced, so that measured data can be fully utilized, control link parameters are adjusted according to vibration frequency changes, and oscillation is effectively suppressed.

The invention discloses a smart city street lamp intelligent control system and method. The method comprises the following steps: performing multi-aspect inspection on each hardware device through a comprehensive intelligent control module and a communication module; the environment monitoring module is used for collecting multi-source data in real time and integrating and analyzing the multi-source data through the data fusion module; generating a dynamic dimming strategy of the common road section and the high-priority road section according to the collected data and regional requirements; brightness adjustment and on-off control are executed one by one through the single lamp control module, and equipment operation parameters are collected through the real-time feedback and monitoring module. The remote management platform is used for monitoring the running state of the street lamp in real time and dynamically adjusting strategy optimization analysis; different operation scenes are simulated through a system simulation test, actual deployment is carried out in a pilot area, and parameters and operation logic are optimized. Through modular design, intelligent decision making and data driving modes, the management efficiency and the energy-saving level of urban street lamps are remarkably improved, and reliable technical support is provided for smart city construction.

The invention discloses a medium and low voltage real type power distribution network defect simulation system and a test method thereof, and relates to the technical field of power system fault diagnosis and recovery, and the method comprises the steps: deploying a sensor to collect power distribution network operation data, carrying out the preprocessing, integrating a power distribution network data set, extracting a power distribution network fault feature vector from the power distribution network data set through FFT conversion, and carrying out the fault diagnosis and recovery; the method comprises the following steps: constructing a fault diagnosis model by using a support vector machine (SVM) based on a power distribution network fault feature vector, establishing a simulation model of a medium and low voltage power distribution network by using power system simulation software PSCAD, simulating a power distribution network fault in the simulation model, diagnosing the fault in the simulation model by using the fault diagnosis model, and formulating and implementing a recovery strategy according to a diagnosis result. Evaluating the effect of the recovery strategy, adjusting the recovery strategy according to the evaluation result, repeatedly testing in the simulation environment until the optimal recovery strategy is found, applying the optimal recovery strategy to the actual power distribution network, and continuously monitoring and improving the performance of the actual power distribution network.

The invention relates to the field of air conditioning unit control, in particular to an industrial park elevator system optimization control system and a method thereof.The hardware part comprises a sensor unit, an executing mechanism, a field control unit, communication equipment and a server unit; the software part comprises a real-time operating system, a sensor data acquisition and fusion preprocessing module, a digital twinborn simulation platform, a model prediction control module and a cloud deep reinforcement learning module; the method comprises the steps of S1, data acquisition and primary processing, S2, data transmission and caching, S3, digital twin modeling and system simulation, S4, optimization control strategy generation and issuing, S5, online scheduling and deep reinforcement learning optimization, S6, safety monitoring and exception handling, and S7, closed-loop feedback and continuous optimization. Efficient integration of elevator modules is achieved through digital twinning and model prediction control cooperation; intelligent data processing is realized through deep reinforcement learning and adaptive data fusion; and safe and energy-saving operation is realized through fault tolerance and safety monitoring.

The invention provides a marine engine lubricating oil system fault diagnosis method and system based on transfer learning from a simulation domain to a real domain, and the method comprises the steps: carrying out the fault simulation of different working conditions based on a built marine engine lubricating oil system simulation model, and obtaining a simulation fault signal response; acquiring real domain fault data of different working conditions of an engine lubricating oil system based on an engine experiment platform; a feature fusion structure based on an encoder-decoder is adopted to obtain simulation domain fault data; an engine lubricating oil system fault diagnosis model based on data migration and algorithm migration dual migration learning is obtained; and based on the engine lubricating oil fault diagnosis model, performing real-time fault diagnosis on the marine engine lubricating oil system to obtain a diagnosis result. According to the method, transfer learning from simulation domain fault features to real domain fault features is realized, so that the problems of high construction cost and insufficient generalization performance of a diagnosis model are solved.

The invention relates to the technical field of power system simulation, in particular to a new energy power system simulation method, which comprises the following steps: S1, constructing a multi-dimensional information acquisition system, S2, constructing a new energy station model, S3, constructing a power grid control system model, S4, constructing a typical transient scene model, and S5, carrying out optimization solution and model correction. A full-chain model covering a new energy station, a power grid control system and a typical transient scene is constructed, and parameter optimization and a multi-objective decision technology are combined, so that the dynamic characteristics of the new energy power system are accurately simulated.

The invention provides a cross-regional air conditioner regulation and control strategy modeling method and a cross-regional air conditioner regulation and control method and system, and is applied to the technical field of intelligent regulation and control of air conditioners. The method comprises the steps that clustering processing is conducted on air conditioner load data of users in all regions, and a clustering result is obtained; constructing a regional cold supply system simulation model corresponding to the clustering cluster based on the users in the same clustering cluster in the clustering result; the operation safety of an actual regional cooling system is considered, modeling is carried out on the regulation and control process of the simulation model based on the Markov decision process, and an optimization strategy model is constructed by taking expected return maximization of a value function corresponding to an operation strategy of the simulation model as a target; and training an optimization strategy model based on simulation operation data of the simulation model. According to the method, the problems that in the process that the DCS participates in power grid load regulation and control, a trial-and-error training-based model is prone to system damage in practical application, and single-model regulation and control cannot guarantee the load regulation and control effect of a whole power grid are solved.

The invention belongs to the technical field of automatic driving automobile testing, and particularly relates to an intelligent automobile key scene optimization generation method based on large model knowledge guidance. Comprising the following steps: S1, constructing a knowledge expression module, and designing a knowledge result, a large language model application mode and a dynamic updating process from scene theoretical knowledge and scene exploration knowledge; s2, constructing a parameter optimization module, designing a multi-stage optimization strategy including global exploration, local optimization and spatial pruning, and fusing the multi-stage optimization strategy with the knowledge model; s3, establishing a simulation test module, and based on a Carla simulation platform, establishing a scene establishment component, a to-be-tested system component, a simulation execution component and a data export component through LLM-Agent; s4, selecting a model and pre-training a large language model, designing a model selection index and selecting the model; and S5, constructing an evaluation and memory module, evaluating a test result, and storing all test and knowledge data. According to the method, the key scene of the intelligent automobile can be quickly generated through mutual combination of the knowledge model, the large language model and optimization search.

The invention provides an energy-saving, carbon-reducing and synergistic technical path optimization method for a steel production system. The method comprises the following steps: establishing a steel production process mechanism and data driving hybrid model; accounting heat, energy, # imgabs0 # quantity and pollutants on the basis of a steel production process mechanism and a data driving hybrid model, and performing process connection to form a steel production system simulation model; on the basis of the steel production system simulation model, a value flow analysis model is embedded, and steel production system value flow accounting is carried out; on the basis of the steel production system simulation model, embedding low-carbon, zero-carbon and negative-carbon technologies in a substance or energy connection mode, and establishing a steel production system coupling carbon reduction technology simulation model; setting an optimization target of the coupling carbon reduction technology simulation model of the steel production system; and optimizing the material energy input parameter variable, the process operation parameter variable and the technical application parameter variable by adopting a U-NSGA-III method to obtain a technical optimization path of the steel production system.

The invention relates to the field of network simulation, in particular to a lossless Ethernet simulation model and a data processing method. The lossless Ethernet simulation model comprises a switch simulation model, a terminal simulation model and a network system simulation model; the switch simulation model has a switch modeling function, a lossless Ethernet flow control function, a fault injection function, a configuration loading function and a simulation result statistics function; the terminal simulation model has a terminal system modeling function, an RDMA modeling function, a flow control function, a configuration loading function and a simulation result statistics function; the network system simulation model has the functions of simulation information import, simulation model input configuration generation, VLAN management, network topology generation, network management, fault injection, simulation report management and simulation result analysis.

The invention discloses a network fault repairing method and device, a nonvolatile storage medium and electronic equipment. The method comprises the steps that state data of all network devices in a system and topological connection relations among all the network devices are collected, a network topological graph is updated according to the state data and the topological connection relations, nodes in the network topological graph correspond to the network devices, and edges in the network topological graph correspond to connection links among the network devices; determining an abnormal probability predicted value of each node in the network topological graph and a health state score of each edge; determining whether a fault occurs or not according to the abnormal probability predicted value and the health state score, and determining a repair mode corresponding to the fault after determining that the fault occurs; and verifying the repair mode through a system simulation model corresponding to the system, and repairing the fault by adopting the repair mode after verification is passed. The technical problem of low network fault repair efficiency caused by manual inspection in related technologies is solved.

The invention relates to the field of nuclear power unit accident analysis, in particular to a coupling method of a VVER unit system program and a neutron dynamics program. The method comprises the following steps: adding an interface function in a reactor core three-dimensional neutron dynamics program, compiling the reactor core three-dimensional neutron dynamics program into a dynamic link library, and accessing and calling the dynamic link library by a reactor system program in a plug-in manner; establishing a neutronics physical model of a specific loading scheme of the VVER type reactor; establishing an accident analysis system simulation model of the VVER type pressurized water reactor; establishing control logic of main systems and equipment of a primary loop and a secondary loop in the VVER type reactor; establishing control logic and conservative condition settings for specific accidents; executing coupling calculation of a reactor system program and reactor core three-dimensional neutron dynamics; and obtaining key safety parameters of the VVER type reactor in a specific accident based on a coupling calculation result. According to the invention, simulation of changes of physical and thermal parameters in a primary loop system and a secondary loop system and action response of a main system after a reactor has an accident can be realized, and efficient and reliable accident analysis can be conveniently carried out on a VVER type nuclear power unit.

The invention provides an HIL simulation test system of a commercial vehicle domain controller. The system comprises an HIL system software platform, an HIL system simulation model, an HIL system simulation hardware platform and a vehicle body system special simulation assembly which are electrically connected. The HIL system simulation hardware platform is used for providing hardware support and executing the hardware-in-the-loop simulation test; the HIL system software platform is used for controlling a simulation test process, managing a test task and automatically generating an interface model; the HIL system simulation model is used for constructing a virtual test environment of a controller and performing signal interaction with the HIL system simulation hardware platform; the simulation assembly special for the vehicle body system is used for simulating vehicle body control, air conditioner control, gateway and vehicle control functions so as to improve the test coverage degree, and efficient development and iteration of a commercial vehicle domain controller are facilitated.

A computer-implemented method for simulating an aircraft system in a closed-loop functional simulation environment is disclosed. The computer-implemented method may include: receiving, at a computer system, one or more control inputs from an interface; processing, by a control system model, the one or more control inputs to generate one or more system command signals; applying the one or more system command signals to one or more virtual system models; simulating a physical response of the aircraft based on output generated by the one or more virtual system models in response to application of the one or more system command signals; generating, responsive to monitoring the output generated by the one or more virtual system models, sensor data; transmitting the sensor data to the control system model; and outputting simulation results, wherein the simulation results at least comprise an indication of the physical response of the aircraft.

The invention relates to the technical field of desert vegetation recovery planning and monitoring systems, in particular to an intelligent desert vegetation recovery planning and monitoring system and method. And the planning optimization module is used for comparing and analyzing the image data of each time node in the data set to obtain the current ecological situation, carrying out simulation experiments based on different vegetation restoration schemes, and planning and designing vegetation restoration according to simulation experiment results. Obtaining a planning design scheme including a vegetation recovery type, a vegetation recovery region, different plant configuration, regional environment simulation and regional water system simulation; the monitoring module is used for monitoring the planning and design scheme, obtaining a vegetation image through an infrared sensor, and processing the vegetation image to obtain vegetation parameters; the service layer carries an artificial intelligence engine, undertakes core algorithm functions of data processing, change detection, growth prediction and the like, and provides an intelligent brain for scheme generation and problem diagnosis.

The invention discloses a method for evaluating the influence of reservoir-water transfer project combined regulation on downstream ecological flow. The method comprises the following steps: step 1, collecting data of a research area; 2, constructing a water transfer project water source area natural water circulation model WEP-NHA; step 3, constructing a natural-social binary water circulation coupling model WEP-HA; 4, simulating the runoff of the water source area by using a WEP-HA model; 5, the system analyzes the change degree of the key control section water quantity and the ecological flow guarantee rate of the water source area under the condition that the reservoir and the water transfer project are overlapped. According to the method, system simulation of disturbance response of a complex system in a water source area can be achieved, the comprehensive influence of a complex water conservancy project system on water resources and the ecological environment is effectively revealed, high adaptability and predictability are achieved, the problem of regulation and storage effect simulation of a reservoir without data or with little data is effectively solved, and the method is suitable for popularization and application. And decision support is provided for scientifically formulating the water transfer scale and guaranteeing the ecological flow.

The invention provides a simulation scene construction and simulation method and system for a large-scale unmanned cluster, and relates to the technical field of unmanned system simulation. The method comprises the steps of modeling a target task based on execution logic for the target task of the large-scale unmanned cluster to obtain an execution structure; decoupling the target task into a plurality of weak coupling subsystems based on the execution structure, and constructing a parallel simulation environment for the target task; based on the execution function category of the target task, constructing a bus interface of a corresponding category; constructing an intelligent algorithm plug-in corresponding to the execution function category based on the bus interface of each category; integrating the intelligent algorithm plug-in into the execution structure of the target task to form an execution model of the target task; and deploying the execution model to a parallel simulation environment to obtain a simulation scene of the target task. The problems that in large-scale unmanned cluster complex task simulation, the calculated amount is large, real-time simulation cannot be achieved, and the simulation accuracy and effect of cross-platform complex tasks are poor are solved.

The invention belongs to the field of power electronic system simulation, and particularly discloses a power electronic system simulation method and system based on rigid self-switching, and the method comprises the steps: employing a rigid algorithm and a non-rigid algorithm for switching in a power electronic system simulation process, and the switching mode is that when the current algorithm is the non-rigid algorithm, when the step size change rate is detected to be-0.1-0.1, the step size change rate is detected to be-0.1-0.1, and the step size change rate is detected to be-0.1-0.1. When the algorithm is # imgabs0 #, switching to a rigid algorithm; the # imgabs1 # is the current integral step length, the # imgabs2 # is a self-adaptive threshold value, and the # imgabs3 # is the maximum integral step length; when the current algorithm is a rigid algorithm, switching to a non-rigid algorithm when it is detected that the step size change rate is smaller than-1 and # imgabs4 #; # imgabs5 # and # imgabs6 # are cost functions of a non-rigid algorithm and a rigid algorithm respectively, and are determined based on calculation time consumption of the algorithms. The method is oriented to a power electronic system, a cross-magnitude variable step size adaptive algorithm is realized, and compared with a single rigid or non-rigid algorithm, the method can provide a faster simulation resolving speed.

The invention discloses a visual arrangement system and method for urban rail cloud simulation test resources, and aims to assist a user to conveniently and efficiently arrange a simulation test service scene, convert the service scene into a template, namely a reusable service scene architecture script, and enable a scheduling engine to schedule the simulation test service scene according to template data information. The method comprises the following steps: respectively docking with an on-cloud platform, an under-cloud system and a simulation interface, establishing a simulation test scene instance of a service system from the on-cloud to the under-cloud, and enabling a user to carry out the simulation test work of the service system on the scene instance. According to the method, a certain resource can be selected as a template to be stored, when needed in the follow-up simulation test process, a template file is flexibly called, the environment is pulled up and deployed through a scheduling engine, the problem that the resources of the test environment are limited is solved, and the convenience and efficiency of cloud simulation environment scene construction are improved.

The invention discloses an air conditioning-storage-charging micro-grid and power distribution network collaborative optimization control method, which comprises the steps of constructing a multi-target optimization model with low carbon, economical efficiency and low load as targets, and realizing dynamic prediction and rolling optimization of a system state based on model prediction control; introducing an online decision-making tool, and dynamically adjusting an energy exchange strategy of the micro-grid and the power distribution network according to the air quality and the operation state; and the control effect is verified through system simulation. Compared with an existing static optimization method, the method has the advantages that dynamic cooperative mutual aid control under multiple targets is achieved, higher real-time performance, higher adaptive capacity and higher operation efficiency are achieved, and the stability and the overall performance of a building energy system in a complex environment are remarkably improved.

The invention belongs to the technical field of aircraft fault diagnosis, and particularly relates to an aircraft fuel control system fault path mining and root cause diagnosis method. The method comprises the following steps: providing a fault propagation-oriented fault root cause diagnostic graph model to realize more interpretable fault source positioning, and backtracking from an alarm node to a fault source based on propagation mechanism information; constructing a variable propagation graph of the aircraft fuel control system in combination with correlation coefficient analysis and a Lingam causal algorithm, and then performing correction based on a system simulation structure in a manual inspection mode so as to establish an interpretable data structure; introducing an edge propagation quantization factor and a path scoring criterion integrating nodes, edges and path lengths to measure the possibility of candidate fault propagation paths; and learning an optimal threshold set of each node in the propagation graph structure by adopting a particle swarm optimization algorithm. The method supports path-level transparent backtracking, improves the accuracy and flexibility of the model, and can excavate a plurality of fault propagation paths.

The invention belongs to the technical field of analog simulation, and particularly relates to an intelligent simulation system with an autonomous decision-making capability, which comprises simulation management used for task scene initialization, system parameter configuration and simulation process control and operation. The display system is used for 2D / 3D visual display and playback of simulation results; the model implementation system is connected with the simulation management and display system and is used for implementing a target model and a flight mode model according to configuration parameters; the intelligent target generation system is used for automatically generating a maneuvering combination strategy, a task load control strategy and a radar control strategy according to the simulation situation information generated by the model implementation system, and feeding back the maneuvering combination strategy, the task load control strategy and the radar control strategy to the model implementation system to drive simulation deduction; wherein the system can execute a plurality of simulation modes including large sample space random task simulation, task simulation without autonomous capability level and task simulation with certain autonomous capability level according to simulation types set by the simulation management and display system.

The invention provides a flange assembly predictive maintenance method based on residual life distribution dynamic identification, which comprises the following steps: firstly, establishing a linear Wiener model of a flange assembly degradation process, and designing a Bayesian parameter dynamic updating mechanism based on normal-inverse gamma conjugate prior; secondly, deducing residual life complete probability distribution considering parameter uncertainty through a Monte Carlo sampling method, overcoming the limitation of point prediction, and providing a maintenance decision rule based on a time-probability threshold; and finally, establishing a decision parameter optimization model with the goal of minimizing the long-term average cost rate, and solving an optimal maintenance strategy through system simulation. Compared with the prior art, the residual life prediction accuracy is remarkably improved, the maintenance cost and the equipment reliability are effectively balanced through a probabilistic decision-making mechanism, the full-life-cycle maintenance cost is remarkably reduced while the flange sealing safety is ensured, and the method has important popularization value in engineering equipment predictive maintenance.

The invention discloses a data filtering method and system for a digital twin industrial control safety target range. The method comprises the following steps: firstly, marking an IP address of an industrial control system network in a segmented manner; feature extraction is carried out on the network behavior data of each IP segment, and splicing is carried out on the IP segment label to serve as a feature sample for constructing an industrial control network security identification model; a plurality of inverted residual modules with the same structure are adopted as core construction units, network behavior features in the feature samples are extracted and learned, and classification training is carried out; deploying the trained industrial control network security identification model to a pre-filtering module of a digital twin industrial control security target range, and carrying out classification, identification and filtering on network behavior data flowing in each IP segment in real time; and the misjudged sample is subjected to backtracking analysis, and the IP marking rule is updated. According to the technical scheme, the accuracy of network behavior data identification can be improved, so that the effectiveness of industrial control system simulation is improved.

The invention discloses an H-infinity intermittent sampling load frequency safety control method for a multi-region power system under spoofing attack, and belongs to the technical field of power system safety control. According to the method, the intermittent control signal is only used in the working interval, the control cost is effectively saved, the limited network bandwidth can be saved through sampling control, and the influence of spoofing attacks on the multi-area power system is effectively resisted through safety control. Firstly, according to the characteristics of intermittent control and sampling control, the influence of spoofing attack is considered at the same time, and a multi-region power system intermittent sampling load frequency safety control dynamic model under the spoofing attack is established. Secondly, a switching Lyapunov functional is provided, meanwhile, under the framework of an LMI, sufficient conditions for existence of an intermittent sampling load frequency safety controller are given, and the conditions guarantee that the index of a multi-area power system is stable and meet the H infinity performance; and finally, verifying the effectiveness of the H-infinity intermittent sampling load frequency safety controller through three-region power system simulation under spoofing attack.