425 results about "Simulation testing" patented technology

The invention discloses an e-government affair platform management method and system based on cloud data, and relates to the technical field of data processing, and the method comprises the steps: collecting multi-source data, carrying out the preprocessing, extracting keywords, carrying out the multi-scale time coding and multi-scale space coding of the data, and storing the data in a database; constructing a government affair knowledge graph based on the database, mining association relationships of department services and analyzing affair handling habits of users; generating a government affair examination and approval path based on the knowledge graph, optimizing the government affair examination and approval path through reinforcement learning, dynamically adjusting the examination and approval process, performing a simulation test by using a digital twinning technology, and verifying the user satisfaction after the examination and approval process is optimized; and storing the government affair data in a database and performing authority management. According to the method, the electronic government affair data processing capability can be improved, the examination and approval efficiency is improved, the verifiability of an optimization strategy is enhanced, and technical support is provided for digital and intelligent transformation of government affair services.

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 provides a low-altitude typical scene-oriented aircraft cockpit simulation method, system and device and a storage medium, and the method comprises the steps: constructing a dynamic extensible low-altitude scene library through fusing mixed reality (MR) and a high-precision digital twin model; in combination with a man-machine in-the-loop multimode interaction technology (eye movement-gesture-voice cooperation), the operation naturalness is improved; and an intelligent optimization algorithm driven by reinforcement learning is introduced, adaptive adjustment of flight control parameters is realized, and finally a'perception-decision-evaluation 'closed-loop training system is formed. According to the invention, digital twinning, mixed reality (MR), multi-modal sensing and adaptive control technologies are fused, pilot low-altitude flight skill training, man-machine work efficiency evaluation and intelligent aircraft control system verification are carried out, and the method can be expanded to UAM operator training and unmanned aircraft simulation testing. The technical barrier of low-altitude flight skill training at present is solved, and the technical blank of low-altitude dynamic scene simulation is filled up.

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, which relates to the technical field of equipment simulation testing, discloses a simulation evaluation method for automatic testing equipment of an in-vehicle infotainment system, and the method comprises the steps: collecting operation test data, carrying out the recognition processing through a deep convolutional neural network model, obtaining test task data, constructing a test action sequence, mapping the test action sequence into a control instruction, and carrying out the simulation evaluation of the in-vehicle infotainment system. The control instruction is optimized and adjusted according to a preset action rule base; driving the in-vehicle automatic test equipment to execute the control instruction to complete the test operation, recording the operation response time and interface state change data in the test process, calculating a movement track deviation value, calculating a test accuracy score, and when the test accuracy score is smaller than a preset threshold value, starting the in-vehicle automatic test equipment; and if not, supplementing the optimization parameters to the preset action rule base and triggering a new test. According to the invention, accurate control of the test equipment is realized by adopting the TCP / IP communication protocol, and the test strategy is continuously optimized by dynamically updating the preset action rule base, so that the automatic test efficiency of the vehicle machine is improved.

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.

The invention provides a vehicle simulation test device and a vehicle simulation test method. The device comprises a first base, a second base and four dynamometers, the dynamometer comprises a lifting assembly, and a steering assembly, a roll assembly and a roller assembly which are arranged on the lifting assembly. The lifting assembly is used for lifting the steering assembly, the steering assembly is used for rotating the roll assembly, and the roll assembly is used for the roll roller assembly. Through the lifting assemblies which are arranged on the left side and the right side of the tested vehicle and have different heights and the side inclination angles of the side inclination assemblies which are adaptively adjusted according to the angles of the lifting assemblies on the left side and the right side of the tested vehicle, the driving conditions of the vehicle at the transverse gradient and wheel side inclination are simulated. Through the lifting assemblies which are arranged at the front end and the rear end of the tested vehicle and have different heights, the driving condition of the vehicle at the longitudinal slope is simulated; the roller assembly is driven through the steering assembly, and the driving condition of vehicle steering is simulated.

The invention relates to the technical field of frequency converter detection, in particular to a quality test board for frequency converter production and processing and a test method, an interface management module automatically identifies and manages interface connection, the problem of inaccurate data caused by misplug or misconnection is avoided, and the test safety is enhanced at the same time. The test execution module covers multiple aspects of performance test, protection function test, communication test, load simulation test and the like. The data acquisition module acquires key parameters in real time and provides detailed data support for subsequent analysis. And the data analysis module quickly identifies abnormal conditions and generates a test report through preprocessing, anomaly detection and performance evaluation. The fault diagnosis module can quickly identify fault types, accurately position fault positions, provide repair suggestions and shorten maintenance time. Therefore, the problem of inaccurate detection data of the frequency converter caused by misplug or misconnection when a tester repeatedly executes interface plugging operation is solved.

The embodiment of the invention provides a vehicle positioning method and device, electronic equipment and a storage medium, and the method is applied to a simulation system, and comprises the steps: collecting the current coordinates and vehicle pose data of a simulation vehicle on a target map in a process of controlling the simulation vehicle to operate in an intelligent driving simulation scene; converting the current coordinate based on the projection mode of the target map to obtain a target coordinate, the target coordinate being a coordinate corresponding to the coordinate type required by the domain controller; the target coordinates and the vehicle pose data are coupled to obtain coupling data, the coupling data are sent to a domain controller, and the coupling data are applied to vehicle positioning of the auxiliary domain controller. According to the invention, the technical problem that the precision is low when a simulation test is used for vehicle positioning in the prior art is solved.

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.

The invention provides an automobile hub bearing environment simulation testing machine, which comprises a frame body, a temperature adjusting assembly, a muddy water assembly, a dust raising assembly and a driving assembly, and is characterized in that the frame body comprises a test box which is arranged in a sealed manner, and the driving assembly comprises a plurality of driving shafts; the front end of the driving shaft extends into the test box and can be used for mounting a bearing to be tested, the temperature adjusting assembly is arranged adjacent to the test box and is provided with a temperature adjusting pipeline communicated with the inner side of the test box, the muddy water assembly comprises a muddy water pipeline communicated with the test box, and the muddy water pipeline can be used for enabling muddy water to enter the test box. The dust raising assembly comprises a dust raising box and an air pipe, the air pipe is connected to the dust raising box, and the dust raising box can be communicated with the test box. Aiming at the defects in the prior art, the invention provides the environment simulation testing machine for the automobile hub bearing, which can better simulate an external complex environment.

The invention belongs to the technical field of software testing, and discloses a test case generation method and platform for aircraft performance testing. The method comprises the following steps: determining a first input parameter set, and generating a first test case by utilizing global random search; using the first test case to drive the flight management module to perform simulation test, and receiving first flight state data output after the flight management module performs the simulation test; determining a second input parameter set based on the first flight state information, and generating a second test case by using local random search; driving the flight management module to perform a simulation test by using the second test case, and receiving second flight state data output by the flight management module after the simulation test; an out-of-control input parameter is determined based on the second flight state data. Generation and execution of the test cases are optimized through an intelligent algorithm, the generation efficiency of the test cases is improved, the test cost is reduced, meanwhile, the more comprehensive test coverage rate is ensured, and the test reliability is improved.

The invention provides a chip simulation waveform automatic analysis and analysis method and system, and belongs to the technical field of chip simulation testing. The method comprises the following steps: generating a waveform file for chip testing through a simulation tool, and preprocessing the obtained waveform file; building a deep learning model, training the deep learning model by using the waveform data, the deep learning model being a hybrid deep learning model, combining a deep convolutional neural network and a graph neural network, and introducing an attention mechanism; analyzing the waveform file by using the trained deep learning model, and extracting a digital logic state and a time sequence feature; and comparing the extracted features with a preset test expectation, and generating a comparison result by judging whether the waveform accords with the expectation. By introducing the deep learning model, automatic analysis and analysis of the waveform file are realized, and the test efficiency is remarkably improved.

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 quadruped robot motion control method and system based on reinforcement learning, and belongs to the technical field of motion control. The method comprises the following steps: establishing a simulation environment, constructing a quadruped robot model and a motion simulation environment thereof by utilizing Isaac Gym, constructing a CVaR-PPO algorithm based on the simulation environment, and training an optimal control strategy for keeping the robot stable in a complex terrain through strategy optimization. In the training process, a risk sensitivity factor is introduced into the CVaR-PPO algorithm to assess risks of different terrains, and a control strategy is adjusted in a self-adaptive mode. After simulation testing and strategy verification, the optimal strategy is deployed in the actual quadruped robot, and gait autonomous generation and posture adjustment of the robot under various terrains are achieved, so that the environment adaptability and the motion performance of the robot are improved. According to the method, the goals of autonomous gait generation and posture adjustment are achieved, so that the motion control of the quadruped robot in an unknown complex terrain is more robust and accurate.

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 provides a channel reconfigurable SAR echo simulator and method, and relates to the technical field of spaceborne SAR and airborne SAR echo simulation testing, the simulator comprises a radio frequency down-conversion part, an ADC acquisition channel, a signal selection module, a baseband echo modulation channel, a signal convergence module, a DAC playing channel, a radio frequency up-conversion part and a parameter resolving part, the signal selection module and the signal convergence module can carry out transmission connection topology flexible configuration, so that a baseband echo modulation channel carries out echo generation of a corresponding mode according to the multi-channel requirement of SAR echo simulation, and the requirements of three modes are realized through a set of hardware, fixed computing resources and software configuration. Therefore, the technical problem that the echo simulation channel of the existing SAR echo simulator is relatively independent and can only meet the single application requirement can be solved.

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 provides a method and a device for testing a control function of a lubricating pump of a generator of a wind turbine generator, and relates to the field of simulation testing. After a main control module determines that a wind turbine generator is in a power generation state or a generator simulation rotating speed of the wind turbine generator is greater than a lubricating pump starting rotating speed threshold value according to grid-connected power generation simulation parameters generated by simulation of a test module, time delay is performed for N seconds; if it is detected that the output control signal of the generator lubricating pump in the main control module is in a normal state and the generator lubricating pump in the test module operates normally, generating an abnormal triggering condition of the generator lubricating pump under the abnormal control logic based on the test module; if a generator lubrication pump output control signal in the main control module is converted into an abnormal state based on an abnormal triggering condition and triggers a corresponding alarm, a generator lubrication pump operation stopping instruction is sent to the test module based on the main control module; and alarm resetting is carried out after the generator lubrication pump stops running in the test module.