886 results about "System testing" patented technology

The invention discloses a smart power grid fault early warning and diagnosis system, and relates to the technical field of smart power grids. Comprising a multi-modal data acquisition and fusion module, a deep reinforcement learning early warning module, a fault diagnosis module based on a graph neural network, an adaptive diagnosis module integrated with multi-task learning, an edge calculation and cloud collaboration module and a system test and verification module, and comprises the following steps: step 1, acquiring multi-source data through a power sensor, an intelligent electric meter and a meteorological station; dimension reduction and feature fusion are carried out on the data by using a depth auto-encoder model; 2, importing the collected data into a deep reinforcement learning early warning module, and dynamically adjusting an early warning strategy through interaction with a power grid operation environment; 3, a fault diagnosis module based on the graph neural network analyzes the topological structure of the power grid and identifies a fault position; 4, learning a model and processing a fault type; 5, edge calculation and cloud cooperative work are combined; and 6, testing, verifying and optimizing the model by the system testing and verifying module.

The invention relates to the technical field of autonomous navigation and intelligent control of an ocean unmanned system, in particular to a dynamic obstacle avoidance system in unmanned ship path planning, which comprises a multi-source sensing module, a global path planning module, a remote obstacle avoidance decision module, a short-range dynamic obstacle avoidance module and a multi-stage cooperative control unit, and is also provided with a semi-physical verification module. The multi-source sensing module fuses multi-source data to construct a layered map; the global path planning module generates and optimizes a path by adopting an improved algorithm; the long-range and short-range obstacle avoidance modules cope with far and near obstacles based on different algorithms; the multi-stage cooperative control unit coordinates the output of each module; the functions of all the modules are achieved through specific algorithms and formulas, and the semi-physical verification module simulates a real environment to conduct system testing. According to the invention, the environment can be sensed in all directions, intelligent path planning and multi-stage obstacle avoidance decision are realized, an optimal instruction is output through cooperative control, the reliability is improved by combining virtual verification, and safe and efficient navigation of the unmanned ship in a complex water area is effectively ensured.

The invention discloses an automatic test case generation method based on a large model and a particle swarm algorithm, and the method comprises the steps: designing a large language model demand analysis module, carrying out the semantic analysis of a demand document or code annotation of a software system through a large model, and generating a preliminary test case template; designing a particle swarm optimization module, and globally optimizing an input parameter combination and an execution path of the test case through a particle swarm optimization so as to improve the test coverage rate and the defect detection capability; and an automatic test execution and feedback module is designed, the particle swarm optimization evaluates the effectiveness of the test case according to the fitness function, a strategy is iteratively optimized and generated, and the test case is adjusted through a feedback mechanism. According to the method, efficient test cases can be effectively generated, various functions and boundary conditions of the system are covered, dynamic optimization of the test cases is achieved through a feedback mechanism, and comprehensiveness and reliability of system testing are ensured.

The invention discloses an unmanned aerial vehicle system testing method and system based on a model, and relates to the technical field of unmanned aerial vehicle system testing, and the method comprises the steps: collecting the operation data of an unmanned aerial vehicle, preprocessing the data, and carrying out the labeling classification of the preprocessed data; inputting the labeled data into a generative adversarial network model, training a generator, and generating a simulated flight scene data set; carrying out transfer learning model pre-training based on the simulated flight scene data set; deploying the unmanned aerial vehicle in an actual test, collecting incremental data from a real environment, and performing fine tuning on the pre-trained transfer learning model; a flight mission plan is generated, and simulation evaluation is completed in combination with the simulated flight scene data set. By generating the high-quality flight data and continuously updating the model, the test and task planning capability of the unmanned aerial vehicle system in a complex environment is effectively improved, the test cost is reduced, and the coping capability of the model in different flight scenes and the stability of the model in actual operation are enhanced.

Systems and methods are disclosed that relate to applications and platforms for performing in-system testing for autonomous or semi-autonomous systems and applications. In some embodiments, resources of a computing system may be grouped into one or more subsets of system elements (e.g., “a chiplet”) and may be configured to be controlled via an associated local controller, which may enable and / or disable the chiplet as targeted. In embodiments, the local controllers may receive instructions from a central controller and, via the enabling and / or disabling of the chiplets, may maintain a number of resources consumed during system testing within a threshold. As a result, the system may be configured to perform system testing without additional resources and / or without redirecting resources that may be intended for other operations.

The invention relates to the technical field of power system testing, in particular to a transformer simulation test current optimization method based on dynamic impedance matching, which comprises the following steps: performing low-power scanning on a tested transformer to establish a nonlinear model capable of predicting harmonic waves; actively synthesizing the virtual impedance of the target power grid; and a feed-forward compensation current is generated by using a harmonic prediction model and is injected into the transformer after being superposed with a fundamental wave instruction. According to the method, accurate identification modeling is carried out on nonlinear characteristics of a tested unit, active synthesis of virtual impedance of a target power grid is combined, and harmonic compensation current is generated in real time by utilizing a feedforward control thought so as to optimize finally injected test current. According to the method, the problems of inaccurate power grid simulation and insufficient nonlinear response coupling of the transformer in a traditional test are solved, high-fidelity current injection is realized, real electrical behaviors of the transformer under various complex power grid working conditions can be accurately simulated, and the flexibility, accuracy and safety of the test are remarkably improved.

The invention provides a molten pool level online monitoring system and method, and the system comprises a data collection module, a data preprocessing module, a model training and optimizing module, an angle detection and compensation module, a nonlinear data processing module, a system testing and optimizing module, a display module, a communication module, and a control module. The online real-time monitoring of the molten pool level can be realized, the production automation level is improved, when the data acquisition module reaches a detection position, the control system triggers a signal through the coil, the camera is started to capture the images of the liquid level of the slag surface and the liquid level of the copper solution surface of the current molten pool, the online real-time monitoring function of the molten pool level is realized, and the production efficiency is improved. Compared with a traditional manual measurement or intermittent monitoring method, the method has the advantages that the detection efficiency can be greatly improved, the dependence on manual operation is reduced, and the automation level of the production process is improved.

Embodiments of the current disclosure provide for a mobile system interface device that translates between agnostic mobile system data and adapted mobile system data. Embodiments of the current disclosure also provide for remote active diagnostics of a mobile system using the mobile system interface device. Embodiments of the current disclosure also provide for testing of mobile systems using the mobile system interface device.

The invention relates to the technical field of electric power system control, and discloses an emergency control coordination method for power angle stability of an electric power system and related equipment, and by obtaining time domain simulation data of a system test fault and constructing a power angle stability margin, early warning can be performed before the power angle of the system is unstable. The early warning mechanism is helpful for taking measures in advance and preventing the system from entering an unstable state. And when the power angle of the system is indeed unstable, the effects of different control measures can be quickly predicted through the constructed power angle stable sample set and the trained convolutional neural network model, so that quick response is realized, and measures are taken. By constructing the emergency control optimization model considering the control sensitivity, the effects and the sensitivity of various control measures can be comprehensively considered, so that the optimal emergency control strategy is determined, and the control on the system stability is effectively improved according to the optimal emergency control strategy.

The invention relates to an inter-satellite link communication simulation system and method based on a satellite constellation. The system comprises a satellite orbit simulation module, a satellite attitude simulation module, an inter-satellite communication link simulation module, a visualization and interaction technology module and a data interaction and system test module. The satellite orbit simulation module is used for calculating a movement track of a satellite in an earth gravitational field; the satellite attitude simulation module is used for accurately simulating a satellite attitude; the inter-satellite communication link simulation module is used for evaluating inter-satellite communication quality; the visualization and interaction technology module is used for presenting real-time states of satellite orbits, attitudes and inter-satellite links; and the data interaction and system test module is used for smoothly exchanging data, and comprehensively testing and checking the correctness and performance of satellite orbits, attitudes and communication functions. The method has the beneficial effects that the real-time states of the satellite orbit, the attitude and the inter-satellite link are efficiently presented, so that a user can easily monitor and control the simulation process.

A system comprises a plurality of regions, wherein ones of the plurality of regions are partitioned from others of the plurality of regions and at least one of the plurality of regions is a region under test. The system comprises at least one noise generator configured to generate noise in at least the region under test, and at least one noise monitor configured to monitor one or more effects of the noise generated in the region under test. The system comprises a test controller configured to: cause the at least one noise generator to generate the noise in at least the region under test; receive information from the at least one noise monitor indicative of the one or more effects of the noise generated in the region under test; and determine one or more conditions based on at least a portion of the received information.

The invention relates to a simulation test platform for a 1553B bus of a spacecraft, which is suitable for stand-alone test and system test of a 1553B bus interface of a satellite model, and comprises an application layer, a communication layer and a data interface connected with the application layer and the communication layer, the application layer comprises a main control module, a database module and a user interaction module; the communication layer comprises a non-periodic data communication module and a periodic data communication module. The method can be suitable for ground tests of multiple satellite models at the same time, the research and development cost is saved, great convenience is brought to the satellite ground tests, and therefore the development progress of the satellite models is effectively guaranteed.

The invention discloses a power system time synchronization tester detection management method, and relates to the technical field of power system testing and monitoring, and the method comprises the steps: S1, connecting each time synchronization tester to a central management platform, and starting initial time synchronization; s2, generating a synchronous correction instruction based on the time deviation data reported by each tester; s3, sending a synchronous correction instruction to each tester, and performing time deviation correction; s4, monitoring the time deviation of each tester in real time, and ensuring the synchronization precision after correction; s5, when it is detected that the time deviation exceeds a preset threshold value, triggering a re-correction process; according to the power system time synchronization tester detection management method, the problem of synchronization coordination caused by inconsistent time deviation correction in a multi-device synchronization process in the prior art is solved.

The invention relates to the technical field of digital simulation, and discloses a hardware-in-the-loop simulation test method for a control and protection system of an energy storage power station. The method comprises the following steps: acquiring operation data of an energy storage power station, and establishing an SOC-power coupling constraint mechanism by adopting a state space decomposition algorithm; establishing a current-voltage-SOC three-dimensional protection criterion based on the battery state parameters; calculating power balance distribution of the multiple energy storage power stations by adopting a distributed coordination control algorithm; configuring a hardware interface signal synchronization protocol to establish a test platform; and loading a multi-scene fault working condition to execute automatic verification and outputting a performance evaluation result. The technical problem that the energy storage power station control and protection system lacks a high-precision, multi-scene and hardware-in-the-loop integrated simulation test verification method is solved, and the precision, efficiency and safety of test verification of the energy storage power station control and protection system are improved.

The invention provides a system performance testing method and system based on user behavior simulation, and relates to the technical field of system testing, and the method comprises the steps: obtaining service nodes of a tested system and service logic describing jump paths between the service nodes; generating a user behavior sequence for describing a sequence of accessing each service node by a user by combining a random walk algorithm with heuristic weight and random disturbance on the basis of service logic; generating a dynamic flow peak curve conforming to the natural behavior of the user by taking the maximum bearing flow of the tested system as a constraint; scheduling a user behavior sequence according to the dynamic flow peak curve to carry out pressure tests of multiple test types on the tested system; collecting performance data in the test process; abrupt data in the performance data are extracted through a sliding window; and outputting the performance data and the corresponding mutation data as a performance test result of the tested system. Accurate and efficient system testing can be carried out through data conforming to actual behaviors of a user under the condition that historical data does not exist.

An autonomous driving system test method, comprising: sampling scenario data of a plurality of scenarios (S10), and sending the scenario data of the plurality of scenarios to a plurality of simulation emulators (200) for distributed testing, so as to obtain test result data of the plurality of scenarios, the plurality of simulation emulators (200) being each integrated with an autonomous driving domain controller; and determining a dangerous scenario boundary for an autonomous driving system on the basis of the test result data of the plurality of scenarios (S20). The method is an improvement on the a scenario-based simulation test technology for autonomous driving systems, and using a server and a plurality of simulation emulators integrated with autonomous driving system domain controllers to perform joint testing can greatly improve the simulation test efficiency and the test effect for autonomous driving systems.

The embodiment of the invention belongs to the field of system testing, and relates to an interface test display method, which comprises the following steps: in response to at least one linkage operation of a user on a to-be-tested system in a project management area, establishing a test task for the to-be-tested system; acquiring a test case set of a to-be-tested interface of the to-be-tested system according to the test task; and obtaining at least one test plan having a mapping relationship with the test case set, switching different test environments according to the test plan to execute the test cases in the test case set, and outputting a test result and displaying the test result in a scheduling management area. According to the method and the device, the efficiency of quickly responding to the demand change in an agile development mode is greatly improved.

The invention provides a distributed data storage and access software development method based on cloud computing, and aims to construct an efficient, safe and extensible data storage system. The method comprises seven key steps of demand analysis and system design, cloud resource configuration and initialization, distributed data storage algorithm development, data processing layer construction, access control layer development, user interface and interaction design and system test and optimization. By accurately calculating storage resource requirements, optimizing cloud resource configuration and designing a consistent Hash data fragmentation algorithm and a data redundancy strategy, high availability and fault tolerance of data are ensured. Meanwhile, the AES-256 encryption technology and the LZ4 compression technology are adopted to guarantee the data security and the transmission efficiency. According to the method disclosed by the invention, a high-performance, extensible, safe and reliable distributed data storage and access system can be constructed, so that the increasing data storage and access requirements are met, and the user experience is improved.

The invention relates to the technical field of embedded system testing, in particular to a method for testing functionality and stability of a core board service component, which comprises the following steps of: initializing a core board testing environment, ensuring that software and hardware parameters are consistent in a testing process, and aiming at the service component on a core board, testing the service component on the core board; the method comprises the following steps of: analyzing and generating a dependency relationship graph among components by utilizing a dependency graph model, optimizing a key dependency relationship through a deep learning model, performing functional testing on the components according to a priority based on the optimized dependency relationship graph, and testing the stability of a core board during high-concurrency and multi-task operation through multi-thread scheduling and concurrent task simulation. Abnormal, resource competition and deadlock problems are detected; and finally, in combination with an actual application scene, carrying out component hot plug, network abnormity, power-off recovery and other scene tests, and analyzing test data to generate a comprehensive test report. According to the method, the test coverage rate and efficiency are improved, and stable operation of the system under complex conditions is ensured.

The invention discloses a test case generation system based on multi-protocol fusion, and the system comprises a demand analysis module which is used for collecting specification and function description in a demand document, and the specification and function description comprises components, services and interaction relationships among the components and the services; the protocol identification module is used for identifying and extracting protocol information in the system; the test case generation module is used for generating test cases for different protocols according to the information provided by the demand analysis module and the protocol types determined by the protocol identification module; the interactive simulation module is used for simulating interaction between different protocols; the coverage rate evaluation module is used for evaluating the coverage rate of the generated test case to the system; and the automatic execution module is used for automatically executing the generated test cases and collecting test results for analysis and reporting. The method has the advantages of integration, automation, flexibility, accuracy, reliability, high efficiency and the like, the quality and efficiency of system testing can be effectively improved, and the testing cost is reduced.

The invention belongs to the field of automatic testing, and particularly relates to an automatic testing system and method for aviation fly-by-wire flight control equipment, and the system comprises a system self-inspection unit, a system resource unit, a system interface adaption unit, and a system testing control unit. And the system self-checking unit controls the automatic test system to execute a self-checking function through operation software. The test efficiency and the test coverage rate can be remarkably improved, the problem of function test omission can be effectively solved, the fault of the tested airborne avionics equipment is analyzed by adding the YMECA fault analysis module and combining the definition event and the structure function of the fault tree, qualitative analysis is carried out on the fault, a professional basis is provided for fault diagnosis, the maintenance difficulty is reduced, and the test efficiency is improved. The aircraft maintenance guarantee efficiency is improved, and joint test of a plurality of airborne avionics devices and parallel test of a plurality of airborne avionics devices of the same model in a fly-by-wire flight control system of a certain type of fighter can be realized.

The invention discloses an unmanned driving extreme case generation and verification method based on a simulation engine. The method comprises the following steps: S1, constructing a high-fidelity virtual simulation environment; s2, initializing a parameterized model generated by an extreme driving case; s3, generating an initial extreme driving case population based on a genetic algorithm; s4, collecting test result data of the unmanned driving system; s5, quantifying the test effect of each extreme driving case; s6, based on a fitness evaluation result, performing selection, crossover and mutation operation through a genetic algorithm; and S7, the extreme driving case population generated by evolution is subjected to unmanned driving system testing again in the simulation environment, S4 to S6 are executed repeatedly until a preset termination condition is reached, and the termination condition comprises that the scene diversity reaches a target value or the fitness is converged. According to the invention, the generation efficiency and coverage range of the extreme driving scene are improved.

The invention relates to the technical field of energy storage system testing, and discloses an AI camera and AI analysis-based energy storage system testing method and system, and the method comprises the steps: injecting a group of mutually orthogonal exploration excitation signals into an energy storage system, and collecting the global space-time response data of the system; comparing the global space-time response data with a preset health baseline model to identify a suspicious area with abnormal response; for the suspicious region, adaptively generating a resonance excitation signal capable of amplifying the fault characteristics to the maximum extent through an optimization algorithm, and injecting the resonance excitation signal; and collecting amplification response data of the suspicious region, and inputting the amplification response data into the deep learning model to diagnose a specific fault type. The system comprises a distributed excitation network, a global space-time sensing array and an AI analysis processing module. Targeted amplification is carried out on latent fault features by actively generating resonance excitation, the problem that early weak faults are difficult to find in a traditional method is solved, and the fault detection accuracy is improved.

The invention discloses a system testing method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: determining a fault mode corresponding to a fault injection element; determining a fault root cause according to the fault mode and the fault injection element; constructing a virtual environment according to the fault root cause and the fault injection element, and executing fault injection in the virtual environment; according to the method and the device, the response data for fault injection in the virtual environment is acquired, and the fault test result of the to-be-tested system is generated according to the response data, so that the accuracy of fault injection is improved, and the accuracy of system test is improved.

The invention belongs to the technical field of aircraft flight control system testing, and discloses an aircraft flight control system comprehensive testing platform which comprises a hardware platform and a software platform. The hardware platform comprises a comprehensive control test system cabinet, a flight control subsystem 1 control cabinet, a flight control subsystem 2 control cabinet, a flight control subsystem 3 control cabinet, a flight control subsystem 4 control cabinet, a tested product installation operation table and a control operation table. Through the arrangement of the hardware platform and the software platform, a worker only needs to connect the tested piece with the resource boxes in the test cabinet one by one according to the cable identifier, and all test contents required by the tested piece can be completed through the guidance of a software test interface; the whole test process is completely carried out according to the existing test work order of an aircraft repair factory, so that the learning and operation pressure of users is greatly reduced, and the test efficiency is greatly improved.

Testing methods and systems provide a Diagnostic Testing Service as well as an attack simulation service, for a perimeter security system, in a non-disruptive manner, so that the production targets can be tested while normally functioning, and do not have to be brought down for testing. The testing methods can be implemented, such that they are vendor and device type neutral, considering the overall strategy utilized to prevent perimeter security system attacks.

The invention discloses a complex software system test method based on fault propagation path coverage, which realizes accurate simulation and capture of a dynamic propagation process of a defect between modules by introducing a fault propagation path model and combining static slicing and dynamic slicing technologies, comprehensively covers propagation paths possibly existing in a complex software system, and improves the test efficiency of the complex software system. And the limitation of the traditional method in the aspect of dynamic defect detection is overcome. Meanwhile, through a seed defect injection strategy, potential defects can be excited at key propagation nodes, associated defects between modules are further mined, and the detection problem caused by module interactivity is solved. In addition, according to the method, test case expansion and fault propagation path analysis are achieved through an automatic process, manual intervention is remarkably reduced, the time cost and resource consumption in the test process are reduced, the test coverage rate and defect detection capacity of a complex software system are comprehensively improved, and an important guarantee is provided for reliability and safety of the system.

The invention discloses a vehicle-mounted diagnosis system based on CAN communication and an adjustable power supply and a method thereof, and relates to the technical field of vehicle electronic diagnosis. Comprising the following steps: a CAN communication acquisition module is used for acquiring a multi-channel CAN message containing a timestamp; the data processing module is used for identifying a signal field in the message and generating a structured signal value; the signal semantic recognition module is used for matching the structured signal with the reference state data and determining a semantic tag of the structured signal; the anomaly detection module identifies structural anomaly, time anomaly and behavior anomaly based on rule judgment and time sequence prediction; the control instruction generation module is used for generating a power supply control instruction according to the abnormal level; and the adjustable power supply equipment module adjusts output voltage and current parameters according to the control instruction and feeds back a power supply state. According to the method, a closed-loop diagnosis process from CAN data acquisition, signal behavior modeling to power supply response control is constructed, and the method is suitable for application scenes such as function verification, anomaly recognition and system testing of the vehicle-mounted electronic control unit.

The invention discloses an assembly line publishing method and system supporting multiple deployment modes based on agile development, the system comprises a basic software installation and deployment module, an application configuration module and an assembly line execution module, the basic software installation and deployment module is used for installation of Gitlab, Jenkins, Jenkins plug-ins, docker, kubectl and continuous delivery micro-applications; the application configuration module is used for continuously delivering configuration of related applications, assembly lines, servers, K8S clusters, mirror image warehouses and characteristic branches in the micro-applications; the assembly line execution module is used for submitting and releasing characteristic branches in the continuous delivery micro-application and operating an assembly line; the user does not need to concern about different deployment packages or mirror images caused by difference of operating environments such as system testing and production and the complexity of manual compiling, deployment and release, so that the operation risk is reduced, the deployment time is shortened, the workload of operation and maintenance personnel is reduced, the release efficiency of system update deployment is improved, and the time and labor cost is reduced.

The invention discloses a system testing method for UFS equipment, a testing host, equipment and a medium, and relates to the technical field of UFS testing. The method comprises the following steps: generating a plurality of different types of operation commands; determining a first queue depth according to a preset command sending mode, asynchronously sending an operation command of the first queue depth to the UFS equipment so as to enable the UFS equipment to process the operation command according to a queue sequence, and returning a response when each operation command is completed; receiving a response returned by the UFS equipment; determining a second queue depth according to a preset command sending mode and the number of statistical responses; and the operation command of the second queue depth is sent to the UFS equipment, the UFS equipment continues to process the operation commands according to the queue sequence until all the operation commands are sent and executed, and system testing of the UFS equipment is completed. The test period of system testing on the UFS equipment can be shortened, and the test efficiency is improved.