349 results about "Simulation testing" patented technology

The present invention proposes an autonomous driving testing method based on multi-alliance cluster confrontation, aiming to improve the efficiency and accuracy of autonomous driving simulation test, and comprising S1—initialization of testing environment of autonomous driving; S2—decision-making for dividing background vehicle clusters; S3—decision-making for confrontation behaviors of the background vehicles; S4—trajectory planning for the background vehicles; and S5—looping through the steps S2, S3, and S4 until cluster confrontation testing tasks are completed. The method of the present invention uses reinforcement learning and alliance games to dynamically generate testing scenarios that are highly confrontational to vehicles being tested, which can find dangerous boundary scenarios for autonomous driving more quickly and improve the efficiency of simulation testing.

The invention discloses a multi-parameter ultrahigh frequency sensor performance comprehensive evaluation method, which belongs to the technical field of sensor performance evaluation, and effectively breaks through the limitation of the traditional static test on a transient interference response blind area through a dynamic interference field simulation test and an original fidelity-false triggering joint evaluation model. The adaptive adjustment mechanism of the multi-source interference field can vividly simulate the space-time non-uniform characteristic of electromagnetic noise in an industrial field, and in combination with a time-frequency domain composite evaluation algorithm, not only is the signal distortion degree of the sensor in typical interference modes such as frequency sweeping and pulse train quantified, but also the error action acceleration rule caused by high-frequency-band noise coupling is disclosed. The dynamic immunity evaluation capability enables a designer to accurately position the electromagnetic shielding weakness of the sensor, optimizes a front-end filter circuit or a signal processing algorithm in a targeted manner, and remarkably improves the reliability of a product in strong interference scenes such as radar detection and wireless communication.

The invention relates to a physical-data hybrid drive vehicle driving state estimation method, and belongs to the technical field of intelligent vehicle chassis dynamics state estimation. Constructing a mapping relation between the state estimation vector and sensor data by adopting a ridge regression method so as to explicitly express a vehicle movement mechanism; secondly, constructing a data driving model to implicitly extract vehicle sensor data features, and constructing an enhanced LSTM neural network with a double-stage attention mechanism as the data driving model; then, performing dynamic weighted fusion on an output result of the physical model and a sensor sample sequence output by the data driving model to realize deep coupling of physical mechanism knowledge and data driving characteristics; according to the method, the superiority of the method compared with other methods is verified through simulation testing and real vehicle testing.

The invention discloses an automatic driving test scene generation method based on a large-scale language model and a probabilistic scene generation language. The automatic driving test scene generation method comprises the following steps: S1, analyzing a natural language instruction input by a user by using the large-scale language model; s2, performing structured decomposition on the scene description; s3, generating a code snippet of a probabilistic scene generation language; and S4, assembling and compiling a script of the probabilistic scene generation language. The invention further discloses an automatic driving test scene generation device based on the large language model and the probabilistic scene generation language. According to the method, direct, efficient and reliable conversion from the natural language intention to the complex dynamic simulation scene is realized, and the method can be widely applied to the technical field of simulation testing and artificial intelligence.

The invention provides an assembly type plate type foundation splitting design method based on the optimal economic size of a prefabricated part, and relates to the technical field of tower plate type foundations of power transmission lines, and the method comprises the following specific steps: under set constraint conditions, randomly generating various splicing combinations of a predetermined plate type foundation, a finite element analysis model is used for carrying out performance simulation testing and calculating cost, comprehensive performance indexes and comprehensive cost are generated through data processing, a cost-performance coupling coefficient is calculated, a double-optimal parameter combination is screened, a prediction model is constructed and trained, and an optimal combination of spliced combinations is obtained through iterative optimization in combination with a genetic algorithm. And the size is used as the optimal economic size of the splicing combination. According to the method, multi-dimensional collaborative optimization is achieved, traditional design limitation is broken through, performance and cost are accurately balanced through intelligent optimization, engineering practice is fully considered, design landing performance is enhanced, construction efficiency is effectively improved, cost is reduced, and foundation safety is guaranteed.

According to the FPGA + CPU-based permanent magnet synchronous motor hardware-in-the-loop test simulation method provided by the invention, rapid verification and optimization of a motor control system can be realized through automatic tool chain development and a high-real-time simulation technology. The method comprises the following steps: firstly, building a mathematical model of a high-precision permanent magnet synchronous motor system on the basis of an HDL Coder modeling specification, and developing a whole set of complete solution covering model design, code generation, deployment and debugging on the basis of an HDL Coder Workflow Advisor; the method has the advantages of being high in universality, high in usability and low in cost, is suitable for various power electronic models with high-frequency requirements, optimizes and adapts to an FPGA + CPU multi-core heterogeneous computing architecture through a code generation technology, and achieves efficient hardware-in-loop simulation testing.

This invention provides a method for modeling the starting performance of a marine gas turbine. First, a gas turbine aero-thermodynamic performance calculation model is established using C++, and a heat transfer model, temperature sensor model, and control law model for the gas turbine's high-temperature components are established using the M language. Then, based on test data from the gas turbine startup process, the method analyzes how the pressure ratio and efficiency of typical gas turbine components change with the physical speed of the gas generator during startup. The corresponding low-speed characteristics of the gas turbine's rotating components are generated and corrected, enabling high-precision, real-time simulation of the gas turbine's starting performance. This method considers the heat exchange between the high-temperature fuel gas and the ambient atmosphere and the gas turbine itself, improving the accuracy of the gas turbine startup performance simulation. The method can provide a simulation testing tool for the design and optimization of gas turbine startup control laws.

The invention provides a vehicle-mounted system simulation platform, and relates to the technical field of simulation testing, and the simulation platform comprises an interception layer, a simulation layer, a communication layer and a vehicle-mounted intermediate layer service. The interception layer is used for intercepting interface calling of a vehicle-mounted intermediate layer service and forwarding calling parameters to the simulation layer; the simulation layer is used for abstracting a hardware opponent component corresponding to the calling parameter into a virtual control and generating an analog signal based on the virtual control; the communication layer is used for performing data synchronization between the simulation layer and the interception layer; and the vehicle-mounted intermediate layer service is used for carrying out simulation debugging according to the analog signal, and is used for realizing simulation debugging without depending on entity hardware equipment.

The invention discloses a whole vehicle seat controller load simulation method and system, and belongs to the technical field of controller load simulation, and the method comprises the steps: responding to a load simulation instruction, and obtaining simulation control data, the simulation control data at least comprises motor module simulation control data, ventilation module simulation control data, heating module simulation control data and seat motor module simulation control data; based on the simulation control data, a control instruction of a corresponding module is obtained and sent to an upper computer; and obtaining output data sent by the corresponding module, and obtaining a test result based on the output data. According to the invention, comprehensive verification of the control logic of each core module of the seat controller is realized in a stage without an entity module, and the development period of the controller is remarkably shortened; meanwhile, through systematic simulation testing, the potential function matching problem is exposed and solved in advance, and the development efficiency and the reliability of the controller are effectively improved.

The invention provides an intelligent driving scene reconstruction method and system and a storage medium, and the method comprises the steps: obtaining an OpenStretMap map file based on the real vehicle GPS data, and carrying out the lane-level road network matching based on the OpenStretMap map file; the OpenStreetMap map file obtained after matching of the lane level road network is converted into an OpenDR IVE map file; based on real vehicle GPS data, generating a main vehicle track by using a FastDTW algorithm; based on the environment vehicle information, generating a dynamic interaction object track through a Hungary matching algorithm; and fusing the OpenDRIVE map file, the main vehicle track and the dynamic interaction object track, and reconstructing a scene file in an OpenSCENARIO format in preset simulation software. According to the method, automatic reconstruction is carried out by utilizing the real vehicle data, the real vehicle data can be automatically stored as a universal OpenSCENARIO scene file, simulation testing can be carried out in different types of automatic driving simulation software, a real driving scene can be accurately simulated, and a reliable simulation environment is provided for development, testing and verification of an intelligent driving algorithm.

The invention discloses a safety valve performance testing device with an environmental condition simulation function, and relates to the technical field of safety valve performance tests.The testing device is used for detecting a safety valve and comprises a supporting device, a temperature control device, a flow guide device and a booster pump, and the supporting device is used for fixing the safety valve; the temperature control device is connected with the supporting device, the temperature control device and the booster pump are used for simulating environment working conditions of the safety valve, the booster pump is communicated with a safety valve pipeline through the flow guide device, the flow guide device is fixedly connected with the supporting device, and the flow guide device is attached to the inner wall of an inlet of the safety valve. Medium fluids of different temperatures and types are supplied through the temperature control device, pressurization is carried out through the booster pump, so that environment working condition simulation detection is carried out, flow guiding is carried out on the fluids through the flow guiding device, meanwhile, the safety valve is supported and sealed in an auxiliary mode, and the sealing performance is further improved by attaching the flow guiding device to the inner wall of an inlet of the safety valve and increasing the contact area.

The invention discloses a machine learning prediction method for mechanical properties of a metal dot matrix, and belongs to the technical field of metal materials. The method comprises the following steps: S1, finite element modeling and simulation testing; s2, data collection and preprocessing; s3, performing feature analysis; s4, training and evaluating a machine learning model; s5, carrying out interpretability analysis; and S6, performing performance prediction. According to the machine learning prediction method for the mechanical properties of the metal dot matrix, the research and development cost of the mechanical properties of the metal three-dimensional dot matrix is greatly reduced, the research and development efficiency is improved, the prediction precision is high, the blank of special configuration performance prediction is filled, the influence of parameters on the performance can be clarified, and a reliable basis is provided for structural optimization.

The invention provides a control system for simulating real-time propeller blade attitude motion, which comprises a test bench, an electric control cabinet and a control board which are interconnected through a CAN (Controller Area Network) bus, the test bench comprises a power motor, a variable pitch motor, a position encoder, a tension sensor and a proximity switch; the electric control cabinet comprises a PLC (Programmable Logic Controller); a power supply and a motor driver; the console comprises a control handle, a control switch, a buzzer, an indicating lamp and a PC terminal display interface. According to the invention, through dual-mode cooperative control of the power motor and the variable pitch motor, dominant control variables can be switched according to a test scene, the strong coupling problem of torque-rotating speed-pitch angle in a dynamic simulation test of the propeller is solved, and a solution is provided for real-time dynamic simulation of the variable pitch propeller.

The invention relates to the technical field of PLC (Programmable Logic Controller) control parameter setting, and discloses a PID (Proportion Integration Differentiation) parameter intelligent setting method and system based on a PLC control system. According to the method, a process variable signal, a set value signal and an actuator output signal are collected in real time through a PLC communication protocol, feature quantities are extracted after smooth filtering and noise elimination processing, and a standardized control data set is formed; querying matched setting strategy entries by using the set, calculating complexity indexes, evaluating parameter configuration compliance conditions, and generating setting state judgment of a single control loop; detecting common entities among the loops and calculating an interaction strength index by combining a plurality of standardized control data sets, and generating a multi-loop interaction relation graph; and based on the map fusion setting state judgment, calculating the overall quality score and forming a setting recommendation scheme, and after field verification and closed-loop control simulation test, outputting a final PID parameter setting instruction.

Systems, computer program products, and methods are described herein for data block analysis prioritization and routing via quantum machine learning. The present disclosure includes retrieving distributed ledger transactions, retrieving a stream of telemetry data of computer hardware, clustering, based on the transaction metadata, the distributed ledger transactions using a clustering engine, generating, using a machine learning model, a predetermined number of transaction placement schemas of the computer hardware, determining, from a probability output by parallel simulation testing via a quantum computer, a prime schema and a configuration of the prime computer hardware, and routing, based on the prime schema, a transaction cluster to the prime computer hardware.

The invention relates to the technical field of motor testing, and discloses a new energy automobile motor testing device which comprises a base, an equipment box is installed on the base, performance testing equipment is arranged in the equipment box, the performance testing equipment is connected with an input shaft, the new energy automobile motor testing device further comprises a testing table, and a connecting frame is installed on one side of the testing table; a connecting cylinder is rotationally arranged in the connecting frame; according to the invention, the power of the output shaft of the motor can be stably transmitted to the input shaft of the performance test equipment through the self-adaptive transmission assembly, so that the power transmission between the motor and the input shaft is not affected by the bumping of the motor, and the performance test equipment can carry out precise test in the motor bumping simulation test process. In addition, in the process that the jolting assembly drives the motor on the test board to jolt up and down, the jolting assembly can test the performance parameters of the output shaft of the motor when the load exists through the weight of structures such as the test board and the like.

A hybrid power system health management capability verification and assessment method belongs to the field of health management system verification and system evaluation. The platform can collect data from different sensors and information systems in real time, such as operating status, temperature, vibration, etc., and process and analyze them immediately. This real-time performance helps to quickly identify signs of failure, take preventive measures in a timely manner, and reduce the risk of failure and maintenance costs. Simulation testing can not only reduce development and verification costs, but also avoid damage to equipment and improve the safety of overall testing. Not only can verification be performed during the system design phase, but the health status of equipment can also be continuously monitored during the production, operation and maintenance phases to predict and diagnose faults. By combining historical data with real-time data, the platform can provide effective support for the management of the entire life cycle of equipment, extend the service life of the system, and optimize operation and maintenance decisions.

The invention belongs to the technical field of automatic driving, and particularly relates to an automatic driving path planning test system and test method based on digital twinning. The problems that an existing physical test is high in cost and large in simulation test error are solved. Comprising the following steps: S1, carrying out data acquisition and modeling; s2, loading the URDF model to a Gazebo simulation environment or an RViz simulation tool of an ROS platform, constructing a virtual simulation environment highly matched with a real environment, and synchronously generating virtual sensor data; s3, path planning and optimization are carried out; s4, performing consistency verification; and executing the same path planning task in a physical test environment, comparing the path coincidence degree, the obstacle avoidance success rate and the response time of simulation and physical test, and when the path coincidence degree is greater than or equal to 90% and the obstacle avoidance success rate is greater than or equal to 95%, judging that algorithm verification is passed.

The invention discloses a chip testing method and device, computer equipment and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining the coding information of each to-be-tested module in a plurality of to-be-tested modules corresponding to a to-be-tested chip in a target scene; based on the coding information and association information between the to-be-tested modules, coding the to-be-tested modules to obtain an initial population; updating the initial population based on the fitness score of each primary individual in the initial population to obtain a target population; generating test excitation according to the constraint information of the target population on the original test platform, and obtaining a current test result of the to-be-tested chip based on the test excitation; and if the current test result and the original test result of the test excitation on the original test platform conform to expectations, generating problem positioning information of the to-be-tested chip in the target test scene. The problem of low problem positioning efficiency during chip simulation testing is solved, and the technical effect of improving the problem positioning efficiency is achieved.

The invention relates to the technical field of intelligent network connection vehicles, and discloses an automatic V2X large-scale fusion scene test system based on an HIL rack, and the system comprises an upper computer, a real-time machine, a communication comprehensive test instrument, a satellite signal simulator, and a tested OBU. The upper computer is used for deploying nodes and realizing scene file downloading, analysis and 2D simulation test; and forwarding the V2X message output in real time to the communication comprehensive test instrument, and forwarding the GNSS signal to the satellite signal simulator. And running a V2X scene in real time, generating a V2X message, dynamically generating a virtual GNSS signal, and synchronously outputting the virtual GNSS signal to an upper computer. And the communication comprehensive test instrument receives the V2X message and sends a standardized signal to the OBU. And the satellite signal simulator generates a navigation constellation radio frequency signal according to the GNSS data and simulates a dynamic trajectory. And the detected OBU receives the V2X message and the GNSS signal, executes fusion positioning and scene perception, generates an early warning message and returns the early warning message to the upper computer. According to the invention, the test efficiency, coverage and repeatability can be improved, and support is provided for research, development and verification of the V2X technology.

The invention relates to the technical field of porous material preparation process optimization, in particular to a porous material preparation process optimization method. The method comprises the steps of obtaining microscopic pore distribution characteristic data to generate preliminary design parameters, constructing a microstructure model to optimize pore sizes, adjusting key element distribution to generate an improved scheme, determining an optimal process parameter combination through simulation testing, detecting pore uniformity in real time and dynamically adjusting parameters. And monitoring the element utilization rate to generate a dynamic adjustment scheme and verifying the performance index to generate an optimization record. Intelligent control over preparation of the porous material can be achieved, the surface area, the pore uniformity and the key element utilization rate are remarkably increased, and reliable technical support is provided for application in the fields of catalysis, environmental protection and the like.

The invention discloses a wind turbine generator state monitoring and fault tracing method and system, and relates to the technical field of wind turbine generator state monitoring and fault tracing. According to working condition information of a target wind turbine generator, simulation testing is carried out on core components of the target wind turbine generator; analyzing to obtain a vector cloud picture and a scalar cloud picture of each physical quantity of the target wind turbine generator set under each working condition and a conduction characteristic value of each scalar cloud picture, and monitoring working condition information of the target wind turbine generator set and data of each physical quantity corresponding to each core component in the working process of the target wind turbine generator set; and analyzing whether the working state of each core component of the target wind turbine generator is abnormal or not, thereby performing fault traceability analysis on the target wind turbine generator. According to the invention, the accuracy of state monitoring of the wind turbine generator is effectively improved, the time cost of fault tracing is reduced, and a foundation is laid for fault maintenance of the wind turbine generator.

The invention discloses an integrated circuit automatic generation method and system based on circuit topological structure perception, a server and a storage medium. The method comprises the steps that an integrated circuit population to be subjected to simulation testing is determined; performing performance simulation on individuals in the integrated circuit population; judging whether a termination condition is met or not according to the performance evaluation result; if yes, outputting an individual with an optimal performance evaluation result as a circuit parameter configuration scheme; if not, individuals with the performance superior to the specified standard are screened out from the integrated circuit population to serve as parent individuals; segmenting the coding vectors of the parent individuals according to drive stage division, and selecting corresponding drive stage coding segments of different parent individuals for exchange to generate cross progenies; determining an adjustment priority of each component in the coding vector of the cross progeny, and adjusting the coding components with different priorities according to a preset rule of matching the priorities to generate a variation progeny; and performing performance simulation by taking the variation offspring as a new generation of integrated circuit population.

The invention relates to the field of aviation electrical engineering and real-time simulation testing, and provides a multi-level collaborative verification method and platform for an aircraft power generation system control strategy and a storage medium, and the method comprises the steps: an offline simulation stage: carrying out the preliminary design and verification of the control strategy; in the real-time simulation stage, closed-loop real-time verification and parameter optimization are carried out on the control strategy; in the rapid prototyping stage, optimized control strategy codes are deployed to a rapid prototyping controller and are connected with real or high-precision simulated power generation system hardware, and hardware-in-loop-entity hybrid verification is carried out; wherein a unified performance reference and error feedback chain penetrating three stages of off-line simulation, real-time simulation and rapid prototyping is established, a verification result of each stage is used as an expected reference of the next stage, and error monitoring and backtracking correction are carried out. According to the method, through offline-real-time-prototype three-layer progressive verification and a model precision progressive calibration mechanism, the confidence coefficient and the one-time success rate of final physical verification are greatly improved.

The invention relates to the technical field of road condition simulation, in particular to a high-speed multi-scene vehicle-road cooperative driving simulation system, which comprises a scene simulation and data acquisition module, a vehicle-road cooperative driving simulation module, a vehicle-road cooperative driving simulation module and a vehicle-road cooperative driving simulation module, wherein the scene simulation and data acquisition module is used for acquiring point cloud data around a simulated vehicle in real time through a virtual simulation scene; the noise analysis module is used for analyzing local and global outlier characteristics of all point cloud data in each voxel and calculating the noise interference prominence of each point cloud data; the point cloud filtering module is used for identifying and eliminating abnormal point clouds based on noise interference prominence; voxel filtering processing is carried out on the remaining point cloud data; and the vehicle-road collaborative module is used for updating the three-dimensional point cloud map of the simulated vehicle by using the filtered point cloud data so as to realize a vehicle-road collaborative simulation test. The invention aims to improve the filtering processing effect of the voxel filtering algorithm on the point cloud data, so that the quality of updating the three-dimensional point cloud map in real time is ensured.

This invention belongs to the field of structural design and simulation testing technology for renewable energy equipment in the marine sector. It discloses a synchronous similarity design method and system for scaled-down towers. This method introduces an innovative composite penalty fitness function to drive a genetic algorithm for automatic optimization, thereby completing the segmented parameter design of the scaled-down tower in a single, high-precision manner. It synchronously ensures a high degree of similarity between the model and the actual model in key dynamic characteristics (first-order natural frequency) and accurate reproduction in three-dimensional geometry, while strictly complying with all engineering manufacturing constraints. This invention significantly improves optimization efficiency, achieves excellent design accuracy and completeness, and has strong engineering applicability.

The invention relates to the technical field of motor performance test equipment, in particular to performance simulation and test equipment and method for a dual-redundancy motor, and the performance simulation and test equipment for the dual-redundancy motor comprises a base, a mounting frame, a vibration ring, a torque detection unit and a connection socket. The connection socket is fixedly connected with a buckle, the connection socket is provided with a connection interface which is in circuit connection with a detected motor, and the torque detection unit is connected with a rotor of the detected motor and detects the output torque of the detected motor; vibration generated by the radial vibration motor and the axial vibration motor on the vibration ring is transmitted to the mounting ring and the dual-redundancy motor, the vibration of the dual-redundancy motor in the running process when the dual-redundancy motor is mounted on an automobile is simulated, and the position and angle of the vibration transmitted to the dual-redundancy motor are changed by rotating the transmission rod. Therefore, the performance simulation test effect of the invention is improved.

The invention discloses a period precise simulator design method for a combinable core particle network, and relates to the technical field of core simulation testing, and the method comprises the steps: designing a simulation frame of a combinable core particle network simulator; wherein the simulation framework comprises a two-stage core particle network configuration unit and a multi-thread parallel simulation framework; carrying out combinable topology modeling, modular routing mechanism modeling and heterogeneous router micro-architecture modeling on the combinable core particle network; performing protocol layer protocol conversion modeling, protocol layer flow control mechanism modeling, adaptation layer retransmission mechanism modeling and physical layer electrical behavior modeling on the core particle interconnection protocol interface; based on the above design, the period precision simulator for the combinable core particle network is constructed. By designing the simulation framework, more accurate actual core particle network behaviors can be obtained; a higher simulation speed is realized through a multi-thread parallel simulation framework, multi-thread parallel accelerated simulation under a large-scale network is supported, and the simulation test efficiency is improved.

This application discloses a method, apparatus, equipment, and medium for verifying train control functions, relating to the field of train simulation technology. The subsystem simulation system is equipped with a communication interface and establishes a communication connection with the main simulation system through this interface. By monitoring control commands from the main simulation system, when a control command indicating the start of simulation is received, subsystem simulation data is collected; a combined data packet containing the subsystem simulation data is generated based on the subsystem's input / output configuration; and the combined data packet is sent to the main simulation system for updating the current values ​​of corresponding variables. This scheme, by setting up a communication interface in the subsystem simulation system, enables remote access of the subsystem simulation system to the main simulation system; based on this, under the control of the main simulation system, the subsystem simulation data is sent to the main simulation system, realizing remote collaborative simulation testing with the train overall control function simulation platform, thus improving the efficiency of integrated testing and verification of the overall train control function.

This invention discloses a simulation testing system for integrated circuits, belonging to the field of integrated circuit testing technology. It includes a simulation execution module, a data acquisition module, a fault diagnosis module, a parameter correction module, a control module, a visualization module, and an alarm module. The simulation execution module runs a digital twin model of the integrated circuit and outputs simulation parameters, such as temperature, voltage, and timing margin, providing simulation benchmark data for subsequent deviation quantification. This invention overcomes the limitations of traditional single-parameter monitoring by combining multi-parameter comprehensive deviation quantification and dynamic weight allocation with a conditional probability model to accurately diagnose faults and generate a priority list. The hierarchical digital twin model interacts with real-time data streams to achieve accurate simulation of physical behavior, providing a high-precision benchmark for deviation quantification. The model adaptively optimizes, and with iterative control closed-loop, it improves fault identification accuracy and enhances system robustness and practicality.