275 results about "Fault injection" patented technology

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 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 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.

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.

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.

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 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 relates to a closed-loop virtual test flight pre-evaluation method and a medium, and relates to the field of flight tests. The method comprises the steps of constructing a digital twin module which comprises a pneumatic sub-model, a flight control sub-model, a power sub-model and a structure sub-model, defining a tilt transition specific high-risk subject and generating a test case, executing parallel Monte Carlo simulation and hardware-in-the-loop test, performing flight safety risk identification and envelope boundary quantification, and determining a tilt transition specific high-risk subject according to the tilt transition specific high-risk subject. And generating a risk assessment report and optimizing a real aircraft test flight outline. Wherein the aerodynamic sub-model adopts a dynamic vortex grid correction method based on CFD offline calibration and online query; the flight control sub-model comprises a configurable fault injection module based on a script engine, and the configurable fault injection module is used for defining a coupling fault sequence of sequential logic and a condition triggering relation. Compared with the prior art, the accuracy and the applicability of the pre-evaluation of the virtual test flight are improved.

The invention relates to the technical field of state monitoring and fault diagnosis of wind power generation equipment, and discloses a fault diagnosis system and method for a vertical axis wind power generator based on digital twinning, and the system comprises a physical sensing unit, a digital twinning body, an intelligent diagnosis engine, and a predictive maintenance platform. The physical sensing unit deploys a multi-source sensor to collect real-time data; the digital twin body is a high-fidelity virtual model fusing high-precision geometry, multi-physics field simulation and a data-driven degradation model; and the intelligent diagnosis engine realizes fault identification, positioning and mechanism traceability by comparing measured data with simulation data and combining fault mode library matching and virtual fault injection simulation. According to the method, the digital twin which dynamically interacts with the physical entity in real time and is continuously evolved and updated is constructed, the conversion from threshold alarm to mechanism simulation prediction is realized, and the technical problems that in the prior art, multi-source data is isolated, a diagnosis model lacks physical mechanism support, and dynamic simulation and predictive maintenance cannot be carried out are solved.

The invention belongs to the technical field of computers, and particularly relates to a system fault response method, a system fault response device and electronic equipment. The method comprises the following steps: acquiring a fault injection event; mapping the fault injection event according to the fault injection model to obtain a fault score corresponding to the fault injection event; mapping the fault injection event according to a strategy matching model to obtain a target response strategy and a strategy matching score corresponding to the target response strategy; updating model parameters of the fault injection model or the strategy matching model according to a numerical relationship between the fault score and the strategy matching score; and generating a response strategy for a real system fault detected by the transaction management system according to the strategy matching model after the model parameters are updated. According to the invention, system fault response intelligence and automation can be realized.

The invention provides a Pod fault injection method and system based on kubemark in a kubernetes cluster, and the method comprises the steps: firstly providing a fault collection tool which is used for collecting Pod fault information in a real cluster; meanwhile, using modified Kubemark in a simulation cluster to create a virtual node with the same specification as a real cluster node, and deploying a CRI-Proxy (a container runtime interface agent) component to execute fault injection and container life cycle management; a fault scene is simulated through a'fault recording-fault broadcasting 'mode, and Pod and container life cycle abnormity are simulated through fault injection, so that the stability and the recovery capability of the system are tested, valuable performance test data and system optimization guidance are provided for a real cluster, resources are saved, the test efficiency is improved, and the test cost is reduced. And meanwhile, problems can be reproduced, potential defects can be found, and various risks can be avoided in advance.

The invention discloses a fault injection system, method and device, computer equipment and a storage medium, and relates to the technical field of system testing, and the system comprises a fault sequence acquisition module and a signal adjustment module; the server mainboard sends a fault injection command to a fault injection system and controls the fault injection system to perform fault injection operation; a fault sequence acquisition module of the fault injection system acquires a fault sequence; and a signal adjustment module of the fault injection system obtains the data transmission signal from the server mainboard, adjusts the data transmission signal by using the fault sequence to obtain a target signal containing the first fault information, and transmits the target signal to the to-be-tested device to complete fault injection. The problems that fault injection depends on an external control panel, the system architecture is complex, and the accuracy and the real-time performance of fault injection are poor can be solved. The system does not need to be externally connected with a control panel and an additional power supply, is simple in system architecture, does not need to additionally develop firmware, and supports the real-time adjustment of the fault injection process.

The application provides a kubemark-based Pod fault injection method and system in a kubernetes cluster, which firstly provides a fault collection tool for collecting Pod fault information in a real cluster; meanwhile, virtual nodes with the same specifications as the nodes of the real cluster are created in a simulation cluster by using a modified Kubemark, and a CRI-Proxy (container runtime interface proxy) component is deployed to perform fault injection and container lifecycle management; a fault scene is simulated through a mode of "fault recording-fault broadcasting", and the stability and recovery capability of the system are tested by simulating Pod and container lifecycle abnormalities through fault injection, so that valuable performance test data and system optimization guidance are provided for the real cluster, resources are saved, test efficiency is improved, problems can be reproduced, potential defects can be found, and various risks can be avoided in advance.

This invention relates to the field of industrial equipment fault diagnosis, and provides a self-supervised multi-sensor fault diagnosis method and system based on semantic embedding. The method preprocesses raw normal operating condition monitoring data, generates a fault window through single-channel fault injection using temporal semantic embedding, and generates a supervision signal for the fault window. Features are extracted from the training sample window composed of the pure normal operating condition window and the fault window using long-term Transformer branches and short-term CNN branches. The extracted long-term and short-term features are concatenated and mapped to a shared fault feature representation. A fault attribute matrix is ​​constructed, a semantic prototype library is generated, and semantic similarity is calculated. Based on the shared fault feature representation and semantic similarity, a multi-task prediction head is constructed. Based on the multi-task prediction head and the supervision signal, a multi-task loss function is designed to train an end-to-end fault diagnosis model. Post-processing optimization is combined to correct easily misjudged fault results. Online fault diagnosis results are output.

This invention discloses an online editing and parallel execution method and system for vehicle network test cases, relating to the field of vehicle network testing technology. It establishes an online editing environment via a web interface, enabling automatic generation of protocol code and providing testers with a convenient and efficient development experience. Regarding test case execution, it accurately analyzes the dependencies of test cases, uses a topology sorting algorithm to construct a reasonable execution plan, and adaptively switches between sequential and parallel execution modes. Combined with containerization isolation technology, it allocates an independent execution container for each test case, ensuring the isolation and stability of the testing environment. Simultaneously, it initializes a unified test execution context for each test case and establishes a communication connection with the vehicle network bus simulation engine through a standardized interface, achieving standardization and normalization of operations such as message sending and receiving, fault injection, and assertion verification. In variable management, it adopts a copy-on-write mechanism to achieve isolated sharing of project variables, avoiding data crosstalk.

The invention discloses a chaos test method based on a no-service system and a related device, and relates to the technical field of software engineering.The method comprises the steps that firstly, a chaos test instruction initiated by a client is received, and a plurality of function links to be tested are contained in the chaos test instruction; and extracting initial function characteristics of the fault injection function and a system state of the no-service system, sending the initial function characteristics and the system state to the cold start probability model, and scoring the cold start risk of each function link. And sorting according to the cold start risk scores to form a function link test sequence. And collecting communication metadata among the functions, generating a calling event and constructing a function topological graph. A topological graph is refreshed through a dynamic attenuation mechanism, and a key function link and a common function link are divided according to the topological graph. And adjusting the fault intensity according to the real-time load state, and injecting corresponding fault modes into the key function link and the common function link in sequence according to the function link test sequence. And target function features after fault injection are collected, and a test conclusion is obtained through feature comparison, so that a chaos test result better conforms to an actual operation condition.

The invention provides a dual-redundancy R-EPS steering system electronic power unit performance detection device, and relates to the technical field of steering system testing. The control unit is in communication connection with the upper computer; the actuating mechanism comprises a programmable load motor, the control end of the actuating mechanism is connected with the control unit, and the output end of the actuating mechanism is connected with a motor output shaft of the tested electronic power unit; the sensing feedback module comprises a plurality of sensors used for collecting operation parameters of the tested electronic power unit, and each sensor is connected with the control unit; the fault simulation module is integrated in the control unit, and the output end of the fault simulation module is used for connecting a fault injection node of the tested electronic power unit; wherein the programmable load motor, the sensing feedback module and the fault simulation module form an integrated test system for performing dynamic load test and active fault injection test on the tested electronic power unit under the coordination of the control unit. High integration and automation of the detection process can be realized, and the test efficiency and consistency are improved.

A fault injection evaluation method and system, and a computer program product and a medium. The fault injection evaluation method comprises: configuring a target number of cycles for a circuit under test (101), wherein the target number of cycles is the number of cycles during which said circuit operates after being reset; injecting a fault into said circuit (102); outputting a reset signal to said circuit, and acquiring a fault output result that is output by said circuit after the fault is injected (103); and on the basis of the fault output result and a reference output result, performing a comparison to acquire a fault evaluation result (104). By means of the method, it is not necessary to additionally provide a reference circuit, so that the structural complexity of the fault injection evaluation system can be reduced, and the consumption of resources required during evaluation can be reduced.

The invention discloses a GPU program soft error elasticity prediction method based on an error propagation knowledge graph. The method comprises the steps that static and dynamic information of a program is acquired; single-particle bit flipping fault injection is carried out at the register or memory level, and the occurrence rate of different types of error results after bit flipping occurs at each fault point of the program is obtained; preprocessing data obtained by fault injection, and encoding heuristic features; the method comprises the following steps: pre-training a Word2Vec model based on a program SASS assembly code, and mining semantic knowledge of an instruction to obtain a semantic embedding feature of the instruction; constructing an error propagation knowledge graph by combining the execution condition and the data dependency relationship between the program instructions; and fusing the two heterogeneous feature representations as input, and designing a GPU program soft error elasticity prediction model based on the graph convolutional network. According to the method, heterogeneous feature mining and error propagation relation modeling are carried out on the program, the soft error elasticity of the GPU program fault point can be identified more accurately, and the method has higher soft error prediction rate and lower space-time overhead.

The present application relates to the technical field of power distribution network resilience evaluation, and discloses a power distribution network resilience evaluation verification method, system, device and medium based on multi-dimensional fault injection, which comprises the following steps: constructing a multi-dimensional fault model library; based on a preset test target, selecting a target fault scene from the model library and generating a fault injection strategy; executing the strategy on a hardware-in-the-loop simulation platform, and collecting system operation data in real time; calculating a performance index curve representing the overall power supply level of the power distribution network over time, and quantitatively calculating a plurality of resilience evaluation indexes; based on the resilience evaluation indexes, performing comparative analysis, identifying key scenes that significantly affect the resilience of the power distribution network, and adjusting the fault injection strategy in subsequent tests to realize closed-loop evaluation and verification of the resilience of the power distribution network. The present application not only evaluates the degree of performance loss, but also focuses on recovery speed and recovery efficiency to identify weak links affecting recovery and provide a scientific basis for formulating resilience improvement measures.

A system associated with an enterprise computing environment infrastructure may include a chaos testing tool data store that contains a plurality of electronic records, each record including a chaos engineering fault parameter. A computer processor of a chaos testing tool may receive, from a chaos testing user, injection information associated with an element of the enterprise computing environment infrastructure. The chaos testing tool may then access the chaos engineering fault parameter from the chaos testing tool data store and automatically arrange to inject a chaos engineering fault into operation of the element of the enterprise computing environment infrastructure in accordance with the injection information and the chaos fault parameter. A response of the element of the enterprise computing environment infrastructure may then be measured subsequent to said injection, and the system may output an indication of the measured response to the chaos testing user.

The application provides a path-aware fault processing method for a cloud computing environment, and relates to the technical fields of cloud computing, computer network security and system reliability. The method comprises the following steps: obtaining a real end-to-end network path of target service traffic in a network communication system for cloud computing, and representing the real end-to-end network path as an ordered path sequence; determining a fault type of a target fault to be injected and a target path node corresponding to the target fault in the ordered path sequence based on a preset fault model and the real end-to-end network path, generating a fault specification based on the fault type, the position of the target path node and the fault parameters of the target fault, and controlling the target path node to inject a fault injection primitive corresponding to the target fault; and in the case of injecting the fault injection primitive, performing correlation analysis on running data and the fault injection primitive to generate an influence analysis result of the target fault. The technical scheme of the application improves the accuracy of fault influence analysis.

The invention discloses a BMS HIL test system and test method, and relates to the technical field of BMS HIL test. The system comprises an upper computer module, a fault injection module and a BMS module. The upper computer controls the fault injection module to send a fault to the BMS module by sending a fault instruction; the fault injection module is located between the upper computer and the BMS and injects a communication fault or an interlocking signal fault according to a fault instruction; and the BMS module receives the fault instruction. Thus, through automatic fault instruction sending and injection execution, the test gets rid of manual dependence, and operation errors of manual wiring can be avoided, so that the fault simulation accuracy is ensured, and the equipment damage risk is reduced; and meanwhile, manual line adjustment is not needed, so that the test period is shortened, the batch test efficiency is improved, and the effects of improving the test efficiency, guaranteeing the accuracy and expanding the test coverage are achieved.