7168 results about "Simulation test" patented technology

The invention provides a wind measurement laser radar optical automatic calibration method and system based on reinforcement learning, and relates to the technical field of calibration, and the method comprises the steps: obtaining the initial state information and environment parameters of a wind measurement laser radar optical system, constructing a three-dimensional simulation model of the wind measurement laser radar optical system, performing a multi-field coupling simulation test on the three-dimensional simulation model to obtain wind measurement data and wind measurement error data under the current environmental condition, and constructing a mapping model of wind measurement errors and environmental parameters and wind measurement laser radar optical system state parameters; and inputting the wind measurement error data and the mapping model into a preset reinforcement learning model to obtain an optimal calibration parameter set in a current state, generating a calibration instruction of the wind measurement laser radar optical system according to the optimal calibration parameter set, and performing aberration correction by combining online wavefront detection and adaptive optical compensation to obtain a calibration result of the wind measurement laser radar optical system. And automatic calibration of the wind measurement laser radar optical system is completed.

The invention provides an intelligent networked automobile chassis drive-by-wire simulation method and system based on multi-domain modeling, and relates to the technical field of adaptive control, and the method comprises the steps: obtaining structural parameters and kinetic parameters of an intelligent networked automobile chassis, constructing a finite element grid, building a multi-flexible-body kinetic model corresponding to the intelligent networked automobile chassis, and constructing a multi-flexible-body dynamic model corresponding to the intelligent networked automobile chassis; introducing a coupling coordination equation, establishing a multi-flexible-body kinetic equation, and solving to obtain vibration response and stress-strain distribution under different working conditions; generating a plurality of finite element models, performing multi-physical field fusion and multi-error source fusion models, performing online error identification and active compensation, performing all-condition drive-by-wire chassis closed-loop control, and generating a drive-by-wire chassis closed-loop integrated simulation model; constructing a road three-dimensional parameterized model, generating a vehicle-road coupling model, generating a simulation test case, identifying a performance short board, constructing a knowledge graph and an optimization rule base, and generating an optimal control strategy.

The invention provides a hardware-in-the-loop simulation test method and device for a network construction type energy storage converter, and relates to the technical field of electric power grids. The network construction type energy storage converter is connected with the simulation energy storage system and the power grid simulation device, a hardware-in-the-loop simulation test system is constructed, and control parameters of the simulation energy storage system and the power grid simulation device are adjusted based on the simulation test system in combination with test types. Various types of hardware-in-the-loop tests and semi-physical tests such as fault ride-through tests, electric energy adaptability tests and black start tests are realized, and effective evaluation of the performance of the network-forming type energy storage converter is realized. According to the method, the problem of power grid oscillation caused by the fact that the network construction type energy storage converter is connected into the power grid for testing is avoided, the accuracy of the testing result of the network construction type energy storage converter is guaranteed, accurate capturing of performance parameters of different types of network construction type energy storage converters is achieved, and the testing effect of the network construction type energy storage converter is improved.

The invention discloses an electromagnetic environment simulation method and system of a display module, a medium and a product, and relates to the field of electromagnetic variable measurement, and the method comprises the steps: receiving a test identification code inputted by a user, extracting a plurality of target scenes corresponding to the test identification code from a preset scene library, and generating a scene change sequence; determining a radio frequency interference source combination and a mechanical vibration parameter corresponding to the target scene; setting test parameters of the test time periods corresponding to the multiple target scenes, and generating a dynamic test sequence; receiving a key test scene marked by a user, and adjusting a test time period and test parameters corresponding to the key test scene to obtain a target test sequence; simulating an electromagnetic environment of the target display module, and recording simulation test parameters of the target display module; the simulation test parameters comprise display brightness, contrast and response time; and determining an electromagnetic compatibility evaluation result based on the target test sequence and the simulation test parameters. According to the invention, the accuracy of an electromagnetic compatibility test result can be improved.

The invention discloses a vehicle-mounted boost inductance monitoring simulation test system and a test method thereof. The vehicle-mounted boost inductance monitoring simulation test system comprises a vehicle-mounted power supply simulation module, an accelerated life test module, an environment test box, a fault early warning module and a data analysis and diagnosis module. The actual stress state of the inductor is comprehensively simulated by constructing a power supply simulation model matched with the actual working condition of the electric vehicle and combining a multi-environmental-factor coupled accelerated life test; real-time monitoring and fault early warning of inductive performance degradation are realized by adopting an acoustic emission technology; an inductance fault diagnosis knowledge base and an intelligent reasoning system are constructed by applying big data analysis and machine learning technologies. According to the system and the method provided by the invention, the inductance reliability test efficiency can be remarkably improved, the early warning of inductance degradation is realized, the accuracy and the intelligent level of fault diagnosis are improved, a solid basic guarantee is provided for safe operation of a new energy electric vehicle, and the system and the method have wide application prospects and popularization values.

The invention relates to the technical field of software development management, in particular to an internet software development management system and method. The method comprises the following steps: collecting an original function demand set and carrying out function clustering analysis; extracting and classifying demand function features and generating independent demand units; carrying out dependency analysis on the independent demand units; constructing a dependency relationship set and a demand logic structure; the method comprises the following steps: generating a demand framework matrix, carrying out organization network simulation to obtain a demand connection network, carrying out code reverse evolution according to the demand connection network, carrying out basic parameter matching to obtain evolution basic parameters, carrying out a pressure simulation test on the evolution basic parameters to generate a pressure test result, and capturing resource pressure defects based on the pressure test result. And optimizing and adjusting the evolution basic parameters to generate optimized development parameters. According to the invention, a more efficient Internet software development management method is realized.

The invention relates to the technical field of grouting simulation tests, in particular to a sandy gravel stratum catastrophe grouting prevention and control virtual-real blending collaborative test method and system, and the method comprises the steps: carrying out a grouting test on a sandy gravel stratum simulation model, and obtaining grouting parameters and monitoring parameters in the grouting process; based on the resistivity and the radar data, further obtaining a slurry diffusion path and a diffusion range of the area with the higher surrounding rock grade; based on the resistivity and the optical fiber sensing data, the slurry diffusion path and the diffusion range of the area with the low surrounding rock grade are further obtained; inputting the initial grouting parameters into the trained neural network model to obtain simulation data; carrying out preprocessing and alignment operation on the previous data, and carrying out fusion analysis; and according to the fusion analysis result, grouting equipment parameters and a grouting scheme are pre-controlled and adjusted. And real-time regulation and control of a grouting scheme and equipment are realized.

The invention provides a material simulation test method and platform for mold flow analysis, and relates to the technical field of material simulation testing, and the method comprises the steps: carrying out the product demand analysis of a target test material, and obtaining the product demand information; performing injection molding analysis to obtain an injection molding control parameter threshold; obtaining an injection molding simulation test model; carrying out an injection molding simulation test, and carrying out image pre-acquisition to obtain a first pre-acquired image; defect feature analysis is carried out, attention area distribution is carried out, and a target attention area is obtained; an injection molding defect area image is obtained, and defect feature information is obtained; and feedback testing and parameter optimization are carried out, optimized injection molding control parameters are obtained, and injection molding control is carried out. The technical problems that in the prior art, injection molding analysis generally depends on a fixed mathematical model and limited technological parameters, and problems in the molding process cannot be recognized and adjusted in real time, so that the production efficiency and the product quality are low are solved.

The invention discloses a simulation test method for a vehicle-mounted communication network. The method comprises the following steps: S1, initializing a vehicle-mounted communication environment; s2, generating a dynamic network topology; s3, environment adaptability dynamic interference is generated; s4, co-simulation of the dynamic network and interference; s5, testing and evaluating communication performance; and S6, visualizing and exporting a test result. According to the invention, the network topology reflecting the real-time motion state of the vehicle is dynamically generated, the communication change between the vehicles can be reflected in real time in different traffic environments, and the interference conditions in various complex environments are simulated in combination with the environment adaptability dynamic interference generation module, so that the performance of the vehicle-mounted communication network can be comprehensively evaluated.

The invention discloses a mechanical arm force feedback control method based on deep reinforcement learning, and the method comprises the following steps: 1, data collection and preprocessing: collecting environment data, collecting operation data, and preprocessing the data; 2, designing a self-adaptive deep reinforcement learning algorithm, including initial model training, self-adaptive learning module and model online updating; 3, introducing a prediction model, including human operation intention prediction and motion trail prediction; and step 4, performance test and optimization, including simulation test and safety and efficiency evaluation. The force feedback control precision of the mechanical arm during operation in a complex environment and the safety and efficiency of man-machine cooperation are improved. According to the method, a control strategy is updated and adjusted in real time by designing an adaptive deep reinforcement learning algorithm and introducing a human operation intention prediction model, so that environmental changes and unknown interference can be better coped with.

The invention relates to the technical field of data analysis, in particular to a wind tunnel test analysis method and system for a large-span warehouse structure. The method comprises the following steps: executing a wind tunnel simulation test operation, and collecting wind tunnel test data of the wind tunnel simulation test operation; performing wind pressure quantitative distribution simulation analysis of multi-scale wind direction angles based on wind tunnel test data to generate multi-scale wind pressure quantitative distribution data; designing a wind tunnel test large-span warehouse model according to the wind tunnel simulation test operation; based on the multi-scale wind pressure quantitative distribution data, carrying out wind load analysis on each node of the warehouse on the wind tunnel test large-span warehouse model to generate warehouse wind load data; based on the warehouse wind load data, large-span warehouse structure design parameter analysis is carried out, and large-span warehouse structure design parameters are generated; and transmitting the large-span warehouse structure design parameters to a terminal to execute large-span warehouse structure design parameter feedback operation. According to the method, optimization design of large-span warehouse structure parameters is realized through wind tunnel simulation test analysis.

The invention discloses a parameter feature-based test case generation method and a related product. In the scheme, a parameter document of target simulation software is obtained; and extracting parameter feature information of the target simulation software based on the parameter document. And on the basis of the parameter feature information, matching a test case template and a code generation rule in a pre-constructed code knowledge base, and generating an initial test case code. And dynamically optimizing the initial test case code according to feedback data generated in a simulation test process to generate a target test case code. According to the technical scheme, the parameter feature information is automatically extracted, the complex dependency relationship between the parameters is accurately analyzed, the test case is automatically generated based on the knowledge base matching template and rule, software changes are adapted in real time in combination with a dynamic optimization mechanism, dynamic and efficient generation of test case codes is achieved, and the test efficiency is improved. The coverage degree and the adaptability of the test case codes are improved, and then the accuracy, the comprehensiveness and the efficiency of the test are improved.

The invention relates to the technical field of hydraulic engineering, geotechnical mechanics and geological disaster prevention and control engineering, and discloses a landslide surge physical and numerical hybrid model construction method and system and application. Analyzing the landslide instability evolution motion process, the landslide warehousing first wave height and the surge propagation process of the landslide surge; performing a numerical simulation test according to a second result of the landslide surge numerical model test; adjusting the particle size and the kernel function in the landslide surge numerical simulation test, so that the first wave height, the opposite-bank arrival height and the surge pressure distribution in the landslide surge numerical simulation test and the landslide surge physical model test are consistent; and taking the adjusted landslide surge numerical model as the obtained landslide surge hybrid model. The system comprises a first result acquisition module, a second result acquisition module, a test parameter adjustment module and a hybrid model acquisition module. According to the method, different calculation working conditions can be conveniently analyzed.

The invention relates to the technical field of machining, and discloses a hard alloy discrete element parameter calibration method based on a BP neural network, and the method comprises the following steps: constructing a discrete element constitutive model according to material physical property parameters; setting to-be-calibrated parameters and ranges; performing combination experiment design (DOE) according to the to-be-calibrated parameters and the range; the DOE is combined with an experiment design result to serve as input data to be imported into the discrete element constitutive model for discrete element simulation; enough training samples are obtained; establishing a training set by data; obtaining an approximate model between the to-be-calibrated parameter and the output data simulated by the discrete element; and calibrating to-be-calibrated parameters by taking the actual mechanical property as a target, and then comparing a simulation result with a physical test result. According to the technical scheme, the problems that existing hard alloy particle parameters are high in acquisition difficulty and low in measurement precision are solved, and an effective technical means is provided for determining the BPM bond key parameters in the hard alloy particle numerical simulation test.

The multi-ECU simulation test method includes: obtaining a pre-developed application applied to a target ECU; inputting the application into a pre-built multi-ECU simulation environment; querying a simulated vehicle-mounted ECU having a unique identifier the same as the target ECU from a plurality of simulated vehicle-mounted ECUs in the multi-ECU simulation environment as a target simulated ECU; and simulating a communication process of the target simulated ECU via a simulated controller area network or a simulated Internet network in the multi-ECU simulation environment, running the application based on the target simulated ECU, and outputting a running result of the application.

The invention provides a credibility measurement method and system for an unmanned multi-mode perception algorithm, a data-driven virtual simulation test platform is constructed, and feature distribution is counted on the basis of actually-collected actual measurement data. Through dynamic model modeling and state transition, an end-to-end closed loop sensing process is described. Afterwards, for the problem that a traditional combined test method is low in efficiency due to the high dimension of scene parameters, a black box substitution model between the scene parameters and a perception test result is established, historical test data is evaluated by using a Bayesian optimization algorithm to generate the most antagonistic scene parameters in a next iteration test, and the efficiency of the traditional combined test method is improved. In this way, the confrontation of the test environment is continuously improved, and the test efficiency is effectively improved. And finally, a perception algorithm credibility measurement module is constructed, a perception failure scene is extracted through playback test data, a credibility evaluation index system is constructed, and comprehensive credibility evaluation of the tested perception system is realized.

The invention discloses a probe card simulation method and system based on counter-acting force analysis, which are used in the field of wafer simulation test, and the probe card simulation method comprises the following steps: integrating multiple physical field working conditions to construct a probe card geometric model, and importing the probe card geometric model into finite element simulation analysis software; carrying out grid division on the geometric model of the probe card by utilizing the hybrid voxel tree model, adjusting the grid density according to the distribution requirement of the multi-physical field, and setting a simulation boundary condition by utilizing a preset boundary condition template according to the actual simulation requirement; starting a simulation calculation process based on the adjusted grid density and simulated boundary conditions; and providing a visual interface of physical field distribution and a structural stress state in the simulation calculation process, and performing iterative optimization on the performance of the probe card in the simulation process according to a reactive force distribution result. According to the method, the grid density is automatically adjusted to adapt to changes of a physical field, and it is ensured that higher simulation precision is obtained in a key area.

The invention relates to the technical field of data processing, in particular to an automatic rule configuration process processing method, system and device and a medium, and the method specifically comprises the following steps: obtaining first delivery rule data, and carrying out semantic analysis and structured extraction on the first delivery rule data to form second delivery rule data; establishing a standard index library, and performing index systematic construction on the second putting rule data according to the standard index library to generate a multi-way tree rule; performing automatic verification on the multi-way tree rule according to a rule verification tool, determining whether the multi-way tree rule is reasonable or not, and if the multi-way tree rule is not reasonable, optimizing the multi-way tree rule; and obtaining historical advertisement putting data, and performing an advertisement putting scene simulation test on the multi-way tree rule according to the historical advertisement putting data. According to the invention, through generation, optimization and application of the multi-way tree rule, intelligent configuration, management and optimization of the advertisement putting rule are realized.

A grouting simulation test system and method for high-temperature water-rich filled fractures. The grouting simulation test system comprises: a water head intelligent sensing and adjusting module, a fracture medium intelligent simulation module, a double-liquid grouting module, a data analysis module, and an intelligent control module. The fracture medium intelligent simulation module comprises a water bath circulation temperature control unit, a fracture model (11), and an opening degree adjustment unit. The water bath circulation temperature control unit is arranged on upper and lower sides of the fracture model (11). Circulating water is provided in the water bath circulation temperature control unit, and the temperature of the circulating water is controllable. The fracture model (11) is formed by combining a plurality of model units. The opening degree adjustment unit is connected to the water bath circulation temperature control unit above the fracture model (11) and is capable of raising and lowering the water bath circulation temperature control unit. The present test system can achieve the study of a grouting diffusion mechanism under the coupling action of two or more factors such as different slurry properties, dynamic water flow velocity, dynamic water temperature, fracture medium multivariate factors, medium temperature, and filling conditions.

The invention discloses an integrated verification and test system and method for complex rules of a substation monitoring system, and the system comprises a rule editing module which provides a visual interface to support a user to edit the complex rules containing various types of variables and time sequence constraints; the analysis and verification module is used for performing grammar, variable conflict and business compliance multi-level verification on the rules; the intelligent test case generation module is used for automatically generating test cases covering normal, boundary and abnormal conditions based on the rule tree structure; the simulation test interface module converts the use case into a standard test script, submits the standard test script to a simulation tool for execution, and outputs the standard test script to a monitoring system through protocol conversion; the result analysis module is used for comparing an execution result with an expected result and generating a structured test report; according to the invention, full-process automation of rule verification and testing is realized, the verification efficiency is remarkably improved, and the test requirements of various transformer substation business scenes are met.

The invention provides an automobile wire harness performance parameter test system, and relates to the technical field of automobile wire harnesses, the automobile wire harness performance parameter test system comprises a test assembly and a control module, the test assembly comprises a simulation test group and a mute test box, and the control module comprises an acquisition module, an analysis module, a judgment model unit and a visual feedback platform; a simulation system is constructed in the simulation test group, and when the automobile wire harness is installed in the simulation system for operation, operation state parameters of an automobile under different road conditions and environment conditions are simulated; the simulation system is constructed to simulate the running state parameters of the automobile under different road conditions and environment conditions, the change relevance between the running state parameters and the current parameters of the automobile wire harness is analyzed, the reference variable is obtained, the first performance of the automobile wire harness is comprehensively judged, the actual running requirements of the automobile wire harness are met, and the reliability of the automobile wire harness is improved. The sound of the automobile wire harness is synchronously recognized and collected through the mute test box, the abnormal type of the wire harness represented by the sound is recognized, the second performance of the automobile wire harness is judged, and the method is more comprehensive.

The invention relates to the technical field of data exchange, in particular to a TCP-IP protocol-based application program data interaction method, which comprises the following steps of: collecting a signal quality index of application program data in a physical layer, capturing signal quality data of each node through real-time network monitoring, and performing time sequence analysis; and extracting a signal quality trend and an abnormal point, and generating an initial signal analysis result. According to the invention, through real-time analysis and trend prediction, potential problems in the network path can be effectively predicted, network path optimization is realized, the data are analyzed through the reinforcement learning model, the network path is predicted and optimized in real time, the adaptive adjustment capability of the network is enhanced, and the data transmission efficiency is greatly improved. Through simulation testing and real-time monitoring, delay reduction of data transmission and bandwidth utilization maximization are ensured, and then through dynamic adjustment of the size of a TCP window, adjustment is performed according to real-time network congestion conditions, and the overall performance of the network is greatly optimized.

The present disclosure provides an automatic driving test method. The method includes: acquiring test configuration information input by a user; generating test cases according to the test configuration information, and allocating the test cases to corresponding test types, wherein test types comprise a virtual simulation test, a whole vehicle in-loop test, a closed site test, and an open road test; and under each test type, testing a to be tested vehicle based on the corresponding test cases to obtain test results corresponding to each of the test type, and the test results comprise a simulation test result, a whole vehicle in-loop test result, a closed road test result, and an open road test result. Thus obtaining rich comprehensive test evaluation results makes the test results for autonomous vehicles more accurate.

The utility model relates to the technical field of model tests, and discloses a landslide damage simulation test device which comprises a model test box, a rainfall frame, a hydraulic assembly, a plurality of spraying assemblies, a water tank assembly and a constant temperature system. The angle of the landslide model box can be adjusted through the hydraulic machine so as to change the slope of a model test landslide soil body; the multiple spraying assemblies are arranged at the top of the rainfall frame and located over the model test box, the output ends of the spraying assemblies aim at a test soil body in the model test box, the influence of rainfall on landslide slippage is simulated by adjusting the spraying size, and the constant temperature system is arranged at the top of the model test box and used for regulating and controlling the temperature of the test soil body. The constant temperature system is used for measuring the influence of the dry-wet cycle effect on the landslide soil body.

The invention discloses a big data prediction model intelligent ammonia spraying control method and system suitable for kiln flue gas denitration. According to the ammonia spraying control method, historical and real-time data of multiple parameters such as the fuel gas flow of the glass kiln are collected firstly, the NOx amount is predicted through modeling of the LSTM-GRU hybrid neural network, the ammonia spraying amount is calculated through self-adaptive control, and the accuracy is ensured through two-stage correction. And the calculated ammonia spraying amount is transmitted to a production master control system to adjust an ammonia supply valve, and automatic alarm and manual control are switched in case of failure. The system comprises a data acquisition module, an intelligent prediction module, a self-adaptive control module and the like, and further comprises a dynamic catalytic reaction simulation test platform for optimization. According to the invention, intelligent automatic control of the big data model is realized, the ammonia spraying amount is accurately adjusted, the denitration efficiency and the ammonia utilization rate are improved, the operation cost is reduced, and the system reliability and stability are enhanced.

Techniques associated with categorizing simulation instances associated with simulation testing comprise categorizing simulation instances that produce unique or otherwise interesting results for further testing, review, and validation. In some cases, the system may be configured to determine low period of resource consumption and to schedule simulation testing during those periods of time.

The invention discloses an intelligent driving algorithm simulation test method, device and equipment and a storage medium, relates to the technical field of intelligent driving testing, and discloses an intelligent driving algorithm simulation test method which comprises the following steps: acquiring vehicle-end environment data and road-end environment data, obtaining a target scene according to the vehicle end environment data and the road end environment data; according to the vehicle end environment data, the road end environment data and the target scene, training based on a diffusion transformation model to obtain a world model; generating a simulation scene according to the target scene and the world model; and performing intelligent driving algorithm simulation test according to the simulation scene. Through vehicle end and road end environment data fusion and training based on a diffusion transformation model, high-fidelity simulation scene generation and efficient simulation testing of an intelligent driving algorithm are realized.

The present application relates to a simulation test method and simulation test platform for an energy-storage battery management system. The method comprises: receiving an energy-storage system real-time simulation result that is sent by an energy-storage system real-time simulation module by means of a high-speed communication protocol; converting a data format of the energy-storage system real-time simulation result into a data format of a target communication protocol, and sending to a battery management control module a target energy-storage system real-time simulation result that is obtained after conversion; receiving a battery management control message that is sent by the battery management control module in response to the target energy-storage system real-time simulation result; and converting a data format of the battery management control message into the data format of the target communication protocol, and sending to the energy-storage system real-time simulation module a target battery management control message that is obtained after conversion, thus making the energy-storage system real-time simulation module perform a test on the battery management control module on the basis of the battery management control message. By using the present method, the simulation test efficiency of an energy-storage battery management system can be improved.

The invention discloses an intelligent digital rail transit simulation test system based on a digital twinborn technology, which comprises a digital track simulation platform, a digital track internal test platform and a central digital track server, and a visual digital track 3D scene model is constructed by joint design based on the rubber wheel train dynamic model data and the digital track urban construction coordinate graph. The digital track internal test platform comprises a test navigation control unit, and a digital track mathematical model, an electronic map, magnetic coding data and environment perception simulation information are preset in the test navigation control unit. The train equipment state can be monitored, the train equipment state transition can be controlled in real time, the artificial intelligence machine learning technology is introduced, and the test effectiveness is improved; and a real vehicle and a simulation machine can be accessed at the same time to be converted into a test platform before internal product release. The invention further discloses an intelligent digital rail transit simulation test method based on the digital twinning technology.

The invention provides a simulation test scene parameter generation method of an automatic driving system and electronic equipment. The method comprises the following steps: acquiring road condition information transmitted by at least one road monitoring device in a target road in real time; the road condition information comprises a long-tail problem identification result; reconstructing road scene parameters based on pre-stored road attribute data and road condition information; searching a target vehicle running on a target road in an automatic driving mode by accessing an automatic driving system, and acquiring sensor configuration parameters of the target vehicle; and generating simulation test scene parameters according to the sensor configuration parameters and the road scene parameters, so as to generate a simulation test scene for the target road, the target vehicle and the automatic driving system based on the simulation test scene parameters. According to the invention, the simulation test scene covers a wide range of driving environments and emergencies, and the diversity and comprehensiveness of the scene are ensured, so that the method is used for realizing the efficient offline verification of the automatic driving system.