1028 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 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 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 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 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 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 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 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 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 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 relates to a microwave wireless energy transmission reflector antenna fast multi-objective optimization method comprising the following steps: establishing an MWPT system simulation model, adopting a Bernstein polynomial basis function to carry out dimension reduction processing on a decision space of an antenna, and reducing the number of decision variables; expressing the constructed MWPT system transmitting antenna optimization model as a multi-objective optimization model through a multi-objective optimization function; constructing an agent model based on Gaussian process regression GPR; a proxy model and an evolutionary strategy are integrated through a Gaussian process regression proxy model and a covariance matrix adaptive evolutionary algorithm, a non-dominated solution set is obtained through iterative optimization, and then the multi-objective design of reflector antenna aperture illumination is optimized. According to the method, three performance indexes of BCE, PRL and APC are comprehensively considered, the Bernstein polynomial basis function is adopted to carry out dimension reduction processing on the antenna design decision space, the number of antenna design decision variables is effectively reduced, the proxy model is introduced into the antenna optimization design method, and the optimization design efficiency is improved.

The present disclosure provides a semi-physical simulation verification method for a control strategy of a distributed hybrid power system, including the following steps: designing a rapid prototyping controller; completing a connection between a semi-physical simulation test platform and an upper computer; building a distributed hybrid power system simulation model using MATLAB / Simulink; and forming a code in Simulink and generating a MATLAB Function module, setting a signal output module for a control signal output under a control strategy, and establishing a corresponding relationship between the signal output module and an output signal interface of the rapid prototyping controller. According to the present disclosure, the test cost generated during verifying the feasibility of the control strategy of the distributed hybrid system is effectively reduced.

The invention provides an automatic simulation test system and method for a semiconductor EAP system, and belongs to the field of semiconductor manufacturing, and the method specifically comprises the steps: defining a test scene through test case coding; constructing a test environment by using the equipment simulation module and the external system simulation module; driving a test process of the tested EAP program through an automatic execution engine and generating real-time output data corresponding to the tested EAP program; and comparing the real-time output data generated by the automatic execution engine with an expected result, and generating a test report. According to the processing scheme, behaviors of equipment and an external system are truly simulated in a software simulation mode, an actual production scene is accurately restored in a test link, dependence on a physical environment is reduced, and test coverage is improved; and moreover, the test scene is solidified through codes and configuration files, so that the versioning management and one-key automatic regression test of the test cases are realized, the test efficiency is remarkably improved, and the quality of secondary development is guaranteed.

The invention discloses a sub-microsecond simulation-based network construction type multi-converter modeling method, and relates to the technical field of converter modeling and simulation. Discretizing a switch element, and constructing a generalized constant admittance switch model based on an LC equivalent circuit; then, expansion modeling from a single converter to a multi-converter system is realized through a discrete system state matrix, and a complete network-forming type multi-converter model including a control link is established in combination with inertia characteristics of a virtual synchronous generator; and finally, building a simulation model of the network construction type multi-converter system in the PSCAD / EMTDC, and verifying the correctness and effectiveness of the method. According to the method, the generalized constant admittance switch model and the inertia characteristic of the virtual synchronous generator are fused, good applicability and stability are achieved under the sub-microsecond-level simulation step length, the system simulation precision and efficiency are remarkably improved, and meanwhile rapid convergence of the transient process of the network construction type multi-converter and active supporting of the power grid voltage frequency are achieved.

The invention discloses a simulation test method and system for an unmanned aerial vehicle control algorithm, relates to the field of intelligent system simulation test, and can solve the defects of an unmanned aerial vehicle simulation system in high real scene rendering and physical engine precision at the present stage. The method solves the problems that the real characteristics of a visual sensor and a flight platform cannot be accurately simulated, the performance of an algorithm in a complex real scene is difficult to effectively evaluate, and the adaptability of the algorithm to a hardware environment is difficult to verify, and comprises the following steps: constructing a high-trueness virtual environment according to scene requirements and rigid body dynamics simulation requirements of an unmanned aerial vehicle simulation test; constructing a simulation model according to the physical motion characteristics of the unmanned aerial vehicle hardware and the performance of the sensing equipment; importing the simulation model into a high-reality virtual environment, and performing parameter setting on the simulation model; and testing and verifying a control algorithm of the unmanned aerial vehicle based on the high-trueness virtual environment and the simulation model completed by parameter setting. The method is used for performing simulation test and verification on the control algorithm of the unmanned aerial vehicle.

The invention particularly relates to an integrated simulation test system and method for a diesel engine speed regulation system, and belongs to the field of diesel engine speed regulation system testing. The system comprises a diesel engine analogue simulation module which is used for simulating and outputting the working mode of a diesel engine, responding to and entering an off-line test working mode or an on-line monitoring working mode, and providing off-line test working parameters or on-line monitoring working parameters for a diesel engine speed regulation system; and the diesel engine speed regulation system analog simulation test module is used for responding to enter an off-line test working mode or an on-line monitoring working mode and acquiring off-line test working state parameters or on-line monitoring working state parameters of the diesel engine speed regulation system in real time. According to the method, the simulation test of the diesel engine speed regulation system is carried out by using the device. The off-line test function verification of the diesel engine speed regulation system is realized, the function verification cost and risk of the diesel engine speed regulation system are reduced, the comprehensive test of the diesel engine speed regulation system is realized, and the usability and reliability of the functions of the diesel engine speed regulation system are improved.

The present invention relates to the field of system simulation, and more specifically, to a compressor station operator training system and data interaction method thereof. The system comprises a compressor station simulation model, a compressor station control system model, and a method for data interaction between the simulation model and the control system model. The control system model is the main body of the control logic. This compressor station operator training system can provide advance understanding of the compressor station's operating characteristics, perform control system pre-verification, debug compressor unit start-up and shutdown logic, identify the optimal operating point and optimal operation method for the compressor unit cascade, and provide operator training.

The invention relates to the technical field of power system frequency modulation control, in particular to a thermal power generating unit primary frequency modulation parameter optimization method and system considering industrial air exhaust heat supply influence. A thermal power generating unit high-precision dynamic model capable of simulating wide load regulation is formed by establishing a dynamic simulation model of a medium-low pressure communicating pipeline steam extraction module and connecting a series single reheating type steam turbine and a speed regulation system simulation model of the series single reheating type steam turbine, and the coupling effect relation and the influence degree of heat supply steam extraction amount change and frequency disturbance change are obtained through simulation evaluation. The optimization intervals of the frequency modulation dead zone, the frequency modulation amplitude limiting and the difference adjustment coefficient are quantified, a parameter optimization design scheme considering the adjustment speed and the system stability is given, the problems of power overshoot and adjustment delay under the deep peak regulation working condition are solved, and the unit frequency stability can be improved.

The invention discloses an industrial steam pipe network control method and system based on multi-source data fusion and adaptive learning, and the method comprises the steps: obtaining multi-source real-time operation data of an industrial steam pipe network system, and carrying out the calculation based on a digital twin model to obtain a state variable calculation value of an industrial steam pipe network; comparing the state variable calculated value with a state variable measured value in real-time operation data to generate a residual error, taking minimization of the residual error as an optimization target, and automatically inverting and updating one or more time-varying physical parameters in the digital twinborn model on line through an optimization algorithm, so as to obtain a digital twinborn model. And performing system simulation, state monitoring or optimization control by using the updated digital twin model. The simulation error is controlled within an extremely low range allowed by engineering for a long time; a self-adaptive learning mechanism enables the model to be quickly self-adjusted and keep effective when facing working conditions such as pipe network topology change and equipment performance degradation, so that the adaptability of the digital twin system to a complex dynamic environment is greatly enhanced.

According to the heat exchanger system management method based on the digital twinborn body, operation parameters of the heat exchanger are collected in real time, and a multi-physical field simulation model including a thermodynamic system simulation model and a vibration stress simulation model is built in combination with a heat transfer mechanism and material characteristics of the heat exchanger; a digital twinborn body capable of accurately reflecting the actual state of the heat exchanger is constructed; the operation state of the heat exchanger is monitored and diagnosed in real time through the digital twinborn body, and accurate recognition of faults, prediction of the service life of key components and optimization of the operation working condition are achieved. The management efficiency and reliability of the heat exchanger system are remarkably improved, the equipment maintenance cost and downtime are reduced, and powerful technical support is provided for efficient and stable operation of the heat exchanger in industrial production.

The invention provides a hydroelectric generating set shutdown rule optimization method considering a rotating speed rising extreme value and a water head fluctuation extreme value. The method comprises the following steps of S1, obtaining water turbine modeling data; s2, constructing a high-precision water turbine model based on a BP neural network; s3, constructing a high-precision servo system model; s4, building a water turbine adjusting system simulation model based on an Octave tool; s5, constructing a comprehensive objective function considering the rotation speed rise extreme value, the water head fluctuation extreme value and the standard ITAE index; and S6, optimizing the closing inflection point and the closing speed of the guide vane of the hydroelectric generating set in combination with a snow-melting optimization algorithm, the water turbine regulating system simulation model and the comprehensive objective function. According to the hydroelectric generating set shutdown rule optimization method considering the rotation speed rising extreme value and the water head fluctuation extreme value, the influence of the shutdown rule on the rotation speed rising extreme value and the water head fluctuation extreme value can be fully considered, and safe and stable operation of the hydroelectric generating set is effectively guaranteed.

The invention relates to the technical field of industrial control system security testing, and provides a construction method and device for a dynamic attack and defense testing environment of an industrial control system. The method comprises the following steps: realizing virtualization operation and behavior modeling of industrial control firmware through a hardware system simulation technology based on logic self-learning; constructing a meta-aggregation data resource pool to realize intelligent scheduling and automatic deployment of industrial control component resources; when it is detected that the behavior of the industrial equipment is abnormal, deviation behavior data are complemented based on a causal relationship reasoning mechanism, and a simulation model is driven to be adjusted; constructing a digital-analog fusion model supporting space-time driving and data synchronization, and realizing data consistency and linkage between a virtual environment and a real environment; an AI agent mechanism is introduced, an attack path is automatically deduced, a defense strategy is optimized, and intelligent evaluation of a drilling process is completed; attack protection scene configuration and control are carried out through an interactive user interface, and simulation and verification operations in a complex dynamic attack and defense environment are realized.

The invention relates to the field of fault detection, and discloses a fault diagnosis system for a pipe network, and the system comprises a data collection module which is used for obtaining pipeline operation data from an SCADA system, a simulation environment, an intermediate database, AP I transmission, and manual inspection data entry; the data preprocessing module is used for performing cleaning, normalization and structured storage on the acquired data, including data availability inspection, basic statistic calculation and box plot drawing; the data analysis module is used for constructing a scoring model according to the pipeline operation data and determining a data distribution type according to the scoring model in combination with a dynamic threshold judgment mechanism; the model development module is used for selecting an optimal model according to the data distribution characteristics, supporting integration of various models, generating and evaluating a plurality of model results, and outputting a visual model result by adopting a hybrid modeling strategy; and the real-time early warning module is used for monitoring the operation state of the pipe network in real time, sending out early warning information based on the diagnosis result and carrying out visual display.