391 results about "Fault injection" patented technology

The invention discloses a hydropower station unit state online monitoring system, relates to the technical field of hydropower station unit monitoring control, and adopts a hybrid digital twin modeling technology combining a physical mechanism main model and a liquid neural network residual compensation model to construct a high-fidelity unit operation state model. The system comprises a data acquisition module, a digital twin modeling module, a fault evolution prediction module, a multi-target optimization module and an adaptive control generation module. Multi-source heterogeneous data fusion is realized through a space-time adaptive weight distribution algorithm, and residual compensation modeling is performed by using dynamic time constant characteristics of a liquid neural network. Virtual fault injection and fault evolution trajectory prediction are realized, and passive fault response is converted into active fault prediction. A two-stage optimization strategy is adopted to realize'safety-efficiency-life 'three-dimensional target collaborative optimization, and a continuous and smooth adaptive control parameter trajectory is generated by controlling a liquid neural network. The modeling precision is improved, and the fault early warning time is advanced.

A method and system for analyzing fault data features of an active distribution network. The method comprises: analyzing a voltage variation after a fault in an active distribution network and analyzing a single-phase ground fault (S1); acquiring distribution network fault data by means of analog simulation (S2); and establishing a fault location prediction model to analyze fault data features and realize fault localization (S3). In the method, a voltage variation after a fault in an active distribution network is analyzed, the voltage variation is equivalently represented using an injected current, a single-phase ground fault is analyzed, and the localization of a fault point is realized. By simulating a current variation during an actual fault injection process by means of an injected current function, a model can more closely reflect an actual operating state, thereby enhancing the authenticity of fault simulation and the accuracy of prediction. A complex relationship between a current variation and node impedance is deeply analyzed by means of a complex information filtering function, and more refined fault features are extracted, thereby optimizing the precision of fault localization, and enhancing the adaptability of the model to different fault scenarios.

The invention provides a full-link dynamic monitoring and anomaly simulation test system and method. The system comprises a cross-level I / O load simulation engine module, a multi-level collaborative fault injection module, a full-link dynamic monitoring module and an intelligent root cause analysis module. The cross-level I / O load simulation engine module is used for simulating business pressure fluctuation, the multi-level collaborative fault injection module is used for synchronously injecting configurable anomalies and realizing cross-level fault conduction, and the full-link dynamic monitoring module realizes request-level end-to-end tracking and acquires monitoring data through a distributed probe. And the intelligent root cause analysis module positions a fault root and generates a repair suggestion in combination with LSTM time sequence prediction and Bayesian causal reasoning. According to the invention, the overall performance and fault response capability of the system can be comprehensively evaluated, and the accuracy and efficiency of system testing are improved.

The invention relates to the technical field of micro-service operation and maintenance, and discloses a full-link intelligent fault simulation and assessment defense method in a micro-service scene. The method comprises the following steps: constructing a dynamic dependency graph based on a service registration center and real-time communication traffic; performing matching backtracking on historical faults according to the atlas, and generating a fault injection point list and a propagation path set sensed by the atlas; in the isolated environment, driving the programmable agent to perform multi-dimensional fault injection, and synchronously acquiring full-amount system response signals; performing multi-dimensional deviation calculation on the signal and the base line to form an observation record containing deviation intensity and propagation rate; and training a graph neural network model with time sequence dependence understanding capability based on the record, and carrying out fault mode identification and evolution prediction on an online real-time link, and outputting a risk assessment report. According to the method, the authenticity of fault simulation and the initiative of risk prediction are improved.

The invention discloses an unmanned aerial vehicle automatic test method, which comprises the steps of building a high-fidelity semi-physical simulation platform which comprises an unmanned aerial vehicle motion simulator, a three-dimensional environment simulator, a flight control module and a ground control station, and loading a complete machine fault model and a dynamic environment model; designing an intelligent multi-fault injection scheme, and defining a single fault scene, a combined fault scene and a fault evolution scheme; configuring a dynamic environment simulation scene including static environment parameters, dynamic environment elements and environment, and a fault interaction scene; executing a self-adaptive test process, automatically generating a test case, intelligently scheduling a test sequence and dynamically adjusting test parameters; and performing multi-source data intelligent analysis and evaluation, collecting test data, performing fusion analysis on fault influence, and generating an evaluation report. By constructing a whole machine fault and dynamic environment model, the scene authenticity is improved by 40%, and for example, the motor fault yaw deviation under strong wind is closer to a real machine compared with a traditional method.

The invention discloses an aircraft braking system evaluation and prediction method based on fault simulation and geometric features, and belongs to the technical field of electric data processing. The method comprises the following steps: constructing a simulation model of an aircraft brake system, and injecting faults into the simulation model according to different degrees of fault injection control parameters to generate a degradation monitoring data set of the whole life cycle of the system; dividing the degradation monitoring data set into a training data set and a test data set; training the GoogLeNet model by using the training data set to obtain a health assessment model; evaluating the health degree of the aircraft brake system by using the test data set; constructing a topological graph according to the multi-rack operation data and the health degree of the aircraft braking system; nodes in the topological graph are clustered and divided into K clusters; establishing a residual life prediction model for each cluster; and performing similarity matching on the sample and the K clusters, and selecting the best matched residual life prediction model to perform residual life prediction on the system. The method can accurately predict the remaining life of the aircraft brake system.

The invention provides a communication network operation accident simulation drilling method and device, and solves the problem that a standardized simulation drilling process with automatic deduction and objective quantitative evaluation capabilities is difficult to construct in the prior art. The communication network operation accident simulation drilling method comprises the following steps: acquiring historical operation data of a communication network, and generating at least one scene element data set according to the historical operation data; the scene element data set comprises disposal evaluation data; determining a scene element data set corresponding to the target accident scene, and constructing an analog simulation environment of a communication network operation accident; determining a preset timeline according to the fault injection parameter, and driving a simulation environment to evolve; and acquiring drill process data, and generating a drill evaluation result by combining with analysis of the disposal evaluation data. The invention further provides a device corresponding to the method. According to the method, historical data is converted into a structured drilling process, and measurable, reproducible and continuous optimization of the emergency capability is realized.

The invention belongs to the technical field of cloud computing and software testing, and particularly discloses an automatic fault injection and recovery testing method based on cloud native, which comprises the following steps: acquiring test basic data of a to-be-tested cloud native system; constructing a fault test execution model according to the test basic data; according to the fault test execution model, executing an automatic fault injection operation; generating an abnormal alarm log according to the system running state after the fault injection operation, and synchronously recording a fault injection operation log; according to the abnormal alarm log, executing automatic fault recovery operation; and generating a fault test report according to the fault injection operation log, the system monitoring data and the recovery operation process log. The invention aims to solve the problems of low automation degree, narrow scene coverage, weak monitoring evaluation and passive recovery in cloud native system fault test in the prior art, and provides a comprehensive, automatic, monitorable and evaluable fault injection and recovery test scheme.

The invention relates to the field of industrial automation testing, discloses a multifunctional testing tool and method for an EUROMAP interface of an injection molding machine, and achieves the crossing from single function verification to system-level compliance evaluation. A test network is constructed through a controller, and deep compliance verification, coverage data interaction, exception handling and cross-layer response consistency are realized. The test tool integrates the functions of protocol analysis, signal simulation, fault injection and the like, supports dynamic generation of boundary value test scenes and abnormal injection of signal delay, CRC errors and the like, and verifies the time sequence / logic consistency of a protocol instruction and an execution mechanism response through a hardware-level timestamp alignment technology. According to the method, an evaluation report including compliance rating, fault diagnosis and optimization suggestions is automatically generated, the problems of single coverage dimension, insufficient abnormal simulation, cross-layer verification deficiency and the like of a traditional test are solved, the intelligence and standardization level of the injection molding machine interface test is remarkably improved, and the equipment interconnection and intercommunication performance is guaranteed.

The invention relates to an intelligent equipment function reliability verification method and device, equipment and a storage medium, and the method comprises the steps: obtaining operation environment parameters and equipment state data of intelligent equipment, and carrying out the construction evaluation of a redundancy verification architecture, and obtaining an initial verification reference; acquiring real-time operation data of the intelligent equipment, and performing function association analysis on the real-time operation data and the initial verification reference to obtain function abnormality features; acquiring state information of associated equipment of the intelligent equipment, performing cross validation on the state information of the associated equipment according to the function abnormality characteristics, and performing fault analysis on the state information of the associated equipment and the function abnormality characteristics to obtain an evolution fault injection scheme; and carrying out abnormal behavior identification on the real-time operation data to obtain an equipment repair requirement, and carrying out feasibility evaluation on the equipment repair requirement based on the function abnormal characteristics to obtain a dynamic repair strategy. According to the invention, a comprehensive guarantee mechanism can be provided for reliable operation of the intelligent equipment.

The invention discloses an equipment anomaly tracing method and system based on a digital twinborn and graph neural network, and belongs to the technical field of industrial intelligent operation and maintenance and fault diagnosis. The invention provides an innovative solution integrating digital twin high-fidelity simulation and a graph structure deep learning algorithm, aiming at the technical bottlenecks that the generalization performance of an existing data driving method is insufficient under the conditions of fault sample scarcity and category imbalance and the traceability accuracy of unknown and composite faults is poor. The method comprises the following steps: constructing a high-fidelity digital twin integrating multi-dimensional physical attributes and a system topology structure; based on a fault mode, influence and harmfulness analysis method system, constructing a fault mode library comprising a plurality of single fault modes and composite fault modes, and generating an enhanced training data set with accurate labels through an automatic fault injection mechanism; training a graph neural network model with a multi-level attention mechanism by using the data set so as to learn a propagation rule of a fault in a complex system topology; and finally deploying the model to carry out abnormity traceability analysis on real-time industrial Internet of Things monitoring data. According to the method, the fault diagnosis generalization ability and the positioning precision under the sample imbalance condition are remarkably improved.

The invention provides a mixed reality industrial simulation training system which is composed of a space fusion perception unit, a multi-physics field simulation unit, a cooperative training management unit and a self-adaptive teaching engine. The space fusion sensing unit is composed of a real-time environment modeling and positioning subsystem and a physical interaction detection algorithm, and the real-time environment modeling and positioning subsystem dynamically constructs a three-dimensional space coordinate system of a real industrial scene through a visual sensor array and a radio frequency scanning device; generating a pose matrix of the virtual equipment model in the perspective display interface; the physical interaction detection algorithm realizes contact force feedback between virtual and real objects based on dynamic solution of collision volume, and when an operator triggers a virtual switch through a handheld controller, a real equipment control signal is synchronously driven; the multi-physics field simulation unit comprises a physical engine core module and a fault injection interface.

A code analyzer implements machine learning to detect vulnerabilities in computer code. The code analyzer trains a machine learning model using training vectors that characterize vulnerable programming patterns. The code analyzer evaluates a topological representation of the computer code using the machine learning model to identify a potential vulnerability. The potential vulnerability corresponds to a portion of the computer code where an attack can be used to bypass a security procedure. The code analyzer tests the potential vulnerability by emulating a fault injection during execution of the portion of the computer code. Upon confirming that the potential vulnerability can be exploited via a fault injection, the code analyzer generates a training vector that characterizes a vulnerable programming pattern associated with the portion of the computer code. The training vector can be used to further train the machine learning model.

The invention discloses an intelligent fault injection and performance quantification system and method for a helicopter engineering simulator, and belongs to the technical field of flight simulation and testing, and the system comprises a hierarchical combinable fault model library module which is used for the flexible construction from a part level to a system level to a composite fault; the intelligent fault injection management module is used for realizing an intelligent fault injection strategy; the multi-dimensional performance index quantification module is used for collecting data before and after fault injection in real time and setting a performance evaluation index system; the automatic test and visual analysis module is used for comparing various quantitative indexes of different control laws or different parameters of the same control law in the same fault scene to generate a comprehensive evaluation report; according to the intelligent fault injection and performance quantification system and method for the helicopter engineering simulator, efficient, objective and deep testing of robustness, stability and efficiency of an advanced flight control law in a special condition state is realized through a hierarchical fault model, an intelligent injection strategy and automatic quantitative evaluation.

A computer-implemented method, according to one embodiment, includes causing a first fault injection configuration to be injected into a first node of a first edge site of a cloud environment, where the first edge site includes a plurality of nodes, and the cloud environment includes a second edge site. The method further includes computing a first minimum cost maximum flow value for the first fault injection configuration, and causing a second fault injection configuration to be injected into a second node of the second edge site for causing a second fault injection. A second minimum cost maximum flow value is computed for the second fault injection configuration. In response to a determination that a difference of the minimum cost maximum flow values is less than a predetermined threshold, one of the fault injection configurations is retained and the other fault injection configuration is discarded.

The invention discloses a fault injection and detection method based on RTL, and relates to the technical field of aerospace fault-tolerant calculation, the fault injection and detection method is compatible with three single-particle fault types of SEU, SET and SEL, the injection bit number, duration and position can be customized by a user, and based on random number file configuration, the problems of single fault type and parameter solidification of an existing tool are solved; a bypass injection mechanism controlled by a timer is adopted, and a fault data flow is switched in a specified clock period, so that a trunk data flow is not influenced, and the occupation of system resources is reduced; a forward detection module is designed based on (13, 8) extended Hamming codes, a receiving end quickly locates the fault type and position through a syndrome look-up table, original data does not need to be transmitted back, and detection delay is effectively controlled; a streamlined design is adopted, check bit generation, fault injection, syndrome generation and fault information output are executed in parallel, and hardware resource overhead is obviously optimized.

The invention discloses an automatic driving hardware-in-the-loop (HIL) test fault injection system and method, and relates to the technical field of vehicle testing, the system combines a precise trigger mechanism of a fault injection module and time sequence-causal correlation analysis of an influence tracking module through the graphical flexible configuration capability of a dynamic configuration module, and the fault injection module is used for performing fault injection on a vehicle. According to the method, the test scene coverage is remarkably improved, the dynamic probabilistic parameter setting can simulate a non-deterministic fault mode in the real world, the fault combination rule setting can verify the fault-tolerant capability of the system under a composite fault, and the requirement of a high-safety standard for a multi-fault superposition test is met; and meanwhile, a timestamp matching engine is used for eliminating misjudgment caused by clock asynchronization through high-precision alignment of faults and response signals, the influence weight of the faults on ECU decision can be quantified through a causal confidence coefficient algorithm, defect roots are accurately positioned, and the detection efficiency and accuracy of the automatic driving system are remarkably improved.

The invention provides a model-based reusable vehicle fault joint simulation method, which comprises the following steps of: (1) creating fault mode information according to the composition and connection relationship of a system simulation model, and summarizing to form a fault mode information set associated with the model; (2) analyzing a logic causal relationship between fault events, and establishing a system-level fault mode library based on fault mode information; (3) aiming at a joint simulation requirement, screening out a fault mode needing to be injected from the fault mode library, establishing a relationship between fault mode information and a simulation model through a model grammar rule, and generating a fault model; and (4) according to the requirements of fault combination, fault time and fault injection probability in the simulation of the reusable vehicle, completing fault simulation setting, and carrying out fault joint analog simulation. According to the method, automatic mapping and injection of fault information based on the model are realized, and the analogue simulation requirements of the reusable vehicle under large-scale, cross-system and cross-linking coupling faults are met.

The invention provides a protocol security fuzzy test system and method based on a speed reduction bridge, the speed reduction bridge is integrated on an FPGA board card, and the speed reduction bridge comprises a protocol fuzzy test processing module, a clock domain crossing buffer and flow control module and a programmable time sequence fault injection circuit. The protocol-based fuzzy test processing module is used for detecting feature information and state information of a data stream flowing through the speed reduction bridge and outputting an action instruction; and based on different action instruction types, driving different modules to inject different types of abnormities into the data stream, and realizing fuzzy testing based on the abnormal data stream. The fuzzy test processing module is embedded in the FPGA logic, different rules can be matched according to the feature information of the data flow, different abnormal injection of the data flow is achieved, the abnormal injection opportunity is determined according to the link state information, the speed reduction bridge has the dual functions of normal protocol relaying and active abnormal injection at the same time, and the reliability of the speed reduction bridge is improved. The test of various abnormities of the equipment to be tested can be realized.

The invention relates to a fault simulation method suitable for engineering simulation of an electric vertical take-off and landing aircraft. The method comprises the following steps: injecting a target fault into a target simulation model of a to-be-tested electric vertical take-off and landing aircraft; controlling a target fault signal to carry out cross-system transmission on a plurality of target airborne systems of the to-be-tested electric vertical take-off and landing aircraft; wherein the target fault signal is a signal triggered based on a target fault; injection data of the target faults and operation data in the cross-system transmission process are obtained so as to be used for evaluating fault responses of the multiple target airborne systems. Through the method and the device, high-fidelity matching of fault injection and an actual fault response scene is realized, and the consistency of fault responses of a plurality of target airborne systems is optimized, so that the authenticity of fault simulation and the effectiveness of fault response evaluation of an electric vertical take-off and landing aircraft jig machine are improved, and the high-fidelity requirement of semi-physical simulation is met.

A process to train a machine learning model to predict fault location in a system includes generating a data set for training the machine learning model. The generating includes injecting, at a selected location of the system, a test fault into a simulation of the system using a workload, and recording a respective error syndrome generated by the simulation. Further, the generating includes repeating the injecting, at other selected location(s) of the system, of other test fault(s) into the simulation of the system, and the recording of respective, generated error syndromes. In addition, the process includes training, using the data set, the machine learning model, and providing the trained machine learning model for use in debugging the system, where the debugging includes predicting, using the trained machine learning model, a fault location within the system based on an error syndrome generated by the system due to the fault.

The invention discloses a hardware-in-the-loop automatic test method and system, and the method comprises the steps: receiving a technical specification document and a historical failure case library of a tested device, analyzing a technical specification through a natural language processing model to extract key test parameters, carrying out the correlation analysis of the key test parameters and a fault mode in the historical failure case library, and obtaining a fault mode of the tested device; generating a structured test demand table, wherein the structured test demand table comprises test target priorities, constraint conditions and boundary value definitions; based on the structured test demand table and equipment working condition data acquired in real time, generating a plurality of test cases covering boundary conditions and extreme working conditions by using a genetic algorithm; the test cases covering the boundary conditions and the extreme working conditions are screened out from the multiple test cases to obtain a test case sequence, and each case in the test case sequence comprises a fault injection parameter, an expected response threshold value and an execution priority label. According to the method and system, the test coverage rate and efficiency are improved, and manual intervention is reduced.

The invention provides an ESC controller fault injection test system. The system comprises a programmable power supply, a fault simulation development board, a probe, an upper computer, a CAN tester and a to-be-tested ESC controller. Wherein the upper computer is used for controlling the programmable power supply to provide a current signal and a voltage signal to the fault simulation development board through the first communication line; the upper computer is also used for sending a fault simulation instruction to the CAN tester through the second communication line; the CAN tester is used for converting the fault simulation instruction into a CAN instruction and providing the CAN instruction to the fault simulation development board through a third communication line; the fault simulation development board is connected with the ESC controller to be tested through a probe, and the fault simulation development board provides a power supply environment and a fault environment for the ESC controller to be tested based on the CAN instruction; the ESC controller to be tested is used for determining a fault code according to the power supply environment and the fault environment and feeding back the fault code to the CAN tester, and the CAN tester converts the fault code into fault information and feeds back the fault information to the upper computer. And the fault injection test can be automatically realized.

The invention relates to an automatic test system for an energy storage system. The system comprises a test management module, a fault injection module, an automatic configuration module, a strategy verification module and a test report module. The test management module is used for creating a test task for the energy storage system; the fault injection module is used for simulating a preset fault scene corresponding to the test task and generating a fault test instruction corresponding to the preset fault scene; the automatic configuration module is used for performing parameter configuration on a target device associated with the test task in the energy storage system according to a preset system parameter configuration file, and generating a target configuration parameter of the target device; the strategy verification module is used for collecting actual response data of the energy storage system in the test process of the fault test instruction, and performing feature matching on the actual response data and expected response data in a preset strategy library to generate a strategy matching result; and the test report module is used for generating a test report of the test task according to the parameters. The efficiency and accuracy of the energy storage system test can be improved.

The invention provides an HIL test system and method based on an IBC controller and a medium. The system comprises a software platform, a hardware platform, the IBC controller and an IBC actuator. Wherein the software platform comprises a whole vehicle dynamics model, the hardware platform comprises an actuator virtual model, the IBC controller and the IBC actuator are in intrusive hard wire connection through a fault injection board card, and the actuator virtual model is used for simulating the working characteristics of the IBC actuator. Interventional hardwire connection between the IBC controller and the IBC actuator is established through the fault injection board card, and the HIL test system can control functions needing to be tested in a mode of remotely controlling a fault injection mode. Meanwhile, the actuator virtual model can specifically simulate the working characteristics of the IBC actuator, so that the limitation of traditional hardware is eliminated, the whole test method can be completed through a pure model, and the conventional function test requirements can be effectively met.

The invention discloses a chaotic engineering fault drilling method and device, a storage medium and electronic equipment, and relates to the field of chaotic engineering, and the method comprises the steps: injecting an nth fault factor into a to-be-tested system, and obtaining an nth fault response result of the to-be-tested system under the action of the nth fault factor, and determining the current operation state of the to-be-tested system according to the target dimension and the nth fault response result, adjusting the nth fault factor into the (n + 1) th fault factor based on the fault adjustment rule and the nth fault response result when the current operation state is a normal state, and then injecting the (n + 1) th fault factor into the to-be-tested system. And circularly executing the steps to realize the chaotic engineering fault drilling of the to-be-tested system. Through the method and the device, the problem of low accuracy of a drilling result of chaotic engineering fault drilling caused by performing chaotic engineering fault drilling through a static fault injection strategy in related technologies is solved.

The invention discloses an alarm function test method and device, electronic equipment and a storage medium, and relates to the technical field of computers, because an alarm process is triggered by adopting a mode of modifying a threshold register in a software level, a PSU does not need to be physically transformed or extra hardware is externally connected to inject a fault, and the fault injection efficiency is improved. And a PSU physical fault risk caused by improper hardware operation is avoided. And meanwhile, the target test case is automatically called, the status word is quickly analyzed, and the manual intervention link is reduced. Therefore, the problems that the PSU may have physical faults, the test cost is relatively high and the test efficiency is relatively low due to a mode of performing fault injection on the PSU in related technologies can be solved, and the technical effects of reducing the risk of PSU hardware damage in the test process, reducing the test cost and improving the alarm function test efficiency are achieved.

The invention discloses an intelligent system failure analysis method based on fault recognition, and relates to the technical field of intelligent system reliability analysis, and the analysis method comprises the specific steps: employing Modelica to construct a multi-physical domain digital twinborn model, combing historical data, and building a structured fault mode library; developing a fault injection algorithm to acquire data to form a standardized data set; preprocessing data to construct a causal link and a probability flow network; carding task scenes to construct a reliability evaluation model and training the reliability evaluation model; inputting actual parameters to trace faults, generating an optimization plan, and outputting an analysis report and a plan after verification; according to the method, the problem of insufficient fault correlation analysis caused by modeling scale splitting in a traditional method is solved by constructing a multi-physical domain digital twinborn model covering microcosmic, mesoscopic and macroscopic and establishing a structured fault mode library of a standardized feature description system containing three types of faults of hardware, software and environment interaction.

The invention discloses a high-concurrency scene-oriented government affair system automation performance test method and system, and the method comprises the steps: deploying test nodes in a government affair system, and constructing a distributed pressure test cluster; constructing a system flow model of a mixed load mode containing an instantaneous peak value and continuous pressure; collecting a resource index set and an application performance index set of the tested system in real time; according to the dynamic capacity expansion and contraction test, comparing the real-time monitoring index data with the system flow model data in the test process, and automatically triggering a horizontal expansion test scene; injecting three types of abnormal events into the system, and recording the self-healing time and the abnormal propagation path of the system; and constructing an intelligent analysis model, identifying a performance inflection point based on an anomaly detection algorithm of a time sequence, and generating a test result. The method has the advantages that the hybrid load model is constructed through the historical business data, the fault injection and intelligent analysis model is combined, real-time monitoring and dynamic capacity expansion and contraction testing are carried out, and the performance of the government affair system in a high-concurrency scene is comprehensively evaluated.

The invention provides an exception handling method and device, electronic equipment, a computer readable storage medium and a computer program product. The method comprises the steps of performing first fault injection on a first module of a database system based on a plurality of first scripts, wherein the first scripts are in one-to-one correspondence with first types of database system faults; performing a first test on the first module subjected to the first fault injection to obtain a first test result of the database system corresponding to each first type; determining an alarm triggering condition of each first type based on the first test result of each corresponding database system; and if the performance index of the database system meets the alarm triggering condition of the first type, determining a fault processing strategy of the database system corresponding to the first type according to the first type. According to the invention, the equipment fault can be automatically identified and repaired.