28 results about "Failure type" patented technology

The invention discloses a vehicle failure control method and device, and belongs to the technical field of automobiles. Acquiring vehicle data in the driving process; failure types and associated failure conditions are obtained, the failure types comprise at least one of sensing system failure, control system failure, execution system failure and front hatch cover system failure, the sensing system failure comprises visual sensing failure and radar sensing failure, and the control system failure comprises decision planning failure and control execution failure; the execution system failure comprises brake system failure, steering system failure and power system failure, and the front hatch cover system failure comprises front hatch cover locking failure; determining a target failure type according to a failure condition met by the vehicle data; and determining a control mode according to the target failure type. According to the method, the failure condition is preset for each failure type, matching and judgment are performed according to the vehicle data, the fault source is accurately positioned, the appropriate control mode is dynamically determined according to different target failure types, and differentiated intelligent decisions are realized.

The invention discloses a configuration item repair-oriented Linux kernel boot test and configuration consistency intelligent repair method. The method comprises the following steps: collecting a compiling log, a boot log and a running state; performing segmentation, pattern matching and field extraction on the log, normalizing error information into structured error entries, and distinguishing a dependency missing class, a mutual exclusion conflict class and other compiling failure classes; performing preprocessing and grammar analysis on the Kconfig file, extracting configuration item attributes and constraint relationships, constructing a unified dependency graph and generating a configuration item metadata table; classifying and marking the configuration items based on the metadata, and calculating a key score; generating a repair action according to the structured error entry, the unified dependency graph and the key score, performing iteration execution, and performing recompilation and restart verification after each iteration until a reparated configuration file which can be compiled and started is obtained or a preset iteration upper limit is reached; according to the invention, the cross-version adaptation and problem closed-loop efficiency is improved.

This application relates to an SMT (Surface Mount Technology) material delivery scheduling method and system. It includes: executing a material delivery task; when reading the identification code of a material tray fails, identifying the failure type as optical overexposure, and reporting the failure information to a central scheduling system; the central scheduling system updates the execution history information of the material delivery task based on the failure information; when the central scheduling system needs to allocate an automated guided vehicle (AGV) to the material delivery task, it queries the execution history information of the material delivery task; if the query results indicate that the material delivery task has failed, it identifies the type of AGV that caused the failure in the execution history information, excludes the AGV type that caused the failure from the available AGVs, and selects AGVs with different physical configurations for allocation. This solves the problem of code reading failure caused by optical overexposure of high-gloss material trays in the SMT production environment.

Described are systems and methods for memory failure analysis based on bitline threshold voltage distributions. An example method of implementing a failure type prediction model includes: receiving, by a processing device, a first failure-related dataset reflecting a first bitline threshold voltage distribution associated with a first memory device; determining, based on the first failure-related dataset, a first failure type distribution for the first memory device; creating a training dataset comprising the first failure-related dataset and the first failure type distribution; and training, using the training dataset, a failure type prediction model to determine, for a second memory device, a second failure type distribution based on a second failure-related dataset comprising second bitline threshold voltage data associated with a second memory device.

The present disclosure provides a fan control method, a fan control device, an electronic device and a storage medium. The method comprises: determining a plurality of first target fans that have failed according to the operating parameters of each fan in a multi-fan device; determining the failure type corresponding to each first target fan according to the failure duration and / or the cumulative number of failures of each first target fan; determining the recovery strategy corresponding to each first target fan according to the failure type corresponding to each first target fan; and executing the recovery strategy corresponding to each first target fan according to the recovery priority of each first target fan; wherein the recovery priority represents the degree of influence of each fan on the operation of the multi-fan device. The present disclosure can realize differentiated recovery processing of multiple failed fans, effectively adapt to the actual needs of different failure scenarios, and improve the overall operation reliability and failure recovery efficiency of the device.

This application discloses a method and apparatus for quantitatively evaluating the failure risk of oil and gas gathering and transportation pipelines, relating to the field of data processing. The method includes: dividing the pipeline under test into multiple first pipe segments; classifying multiple typical failure types into internal corrosion failure and other failures; for each first pipe segment, determining the basic risk values ​​for internal corrosion failure and other failures based on a preset risk scoring table, obtaining a first basic risk value and a second basic risk value; correcting the first basic risk value based on a risk correction factor, obtaining a corrected risk value; the risk correction factor is dynamically determined based on the risk of slug flow occurring in the pipe segment; determining the comprehensive risk value of the pipe segment based on the corrected risk value and the second basic risk value; and obtaining the failure risk assessment result of the pipeline under test based on the comprehensive risk value of each first pipe segment. The scheme provided by this application can improve the accuracy and reliability of the assessment results and enhance the generalization ability of the assessment system.

The invention provides a fault protection device for a reduction gearbox of an electric automobile, and belongs to the field of automobiles, the fault protection device comprises a monitoring unit and a strategy unit, the monitoring unit is used for obtaining state data of a gear shifting motor, the reduction gearbox and an electric drive assembly controller and judging whether a fault occurs or not; the strategy unit outputs control strategies of the gear shifting motor and the reduction gearbox to the electric drive assembly controller according to fault information of the monitoring unit and fault types, according to different faults of the gear shifting motor and the reduction gearbox in the reduction gearbox and different protection actions on the reduction gearbox, power is not cut off blindly, speed limiting is not conducted blindly, and the influence on drivability is reduced.

The present disclosure relates to a failure cause analysis method, device and equipment of a target detection algorithm, and belongs to the technical field of target detection. The method comprises: training and / or testing the target detection algorithm through a data set, and obtaining failure data of the target detection algorithm in the training and / or testing process, each piece of failure data comprising a failure type and measurement values of a plurality of failure influence factors; performing causal reasoning on the failure process of the target detection algorithm based on the failure data to obtain failure causal relationships of the target detection algorithm under at least one failure type, the failure causal relationships comprising causal relationships between the plurality of failure influence factors; and iteratively calculating failure weight values of the plurality of failure influence factors based on the failure causal relationships corresponding to each failure type in the at least one failure type. The present disclosure can qualitatively and quantitatively analyze the failure causes of the target detection algorithm.

The invention discloses a multi-channel non-Lambert surface FPP-PS fusion depth measurement method guided by a failure typing module, and aims to solve the problems that a failure region under a single failure type is generally judged on the basis of a fixed threshold value or an empirical rule in the conventional method, a real mixed failure form is difficult to accurately establish, and the effectiveness of a subsequent repair or fusion algorithm is limited. According to the invention, after the obtained multi-source physical features are used to construct a multi-source joint feature model, the multi-source joint feature model is processed by a failure feature encoder to respectively form prototype vectors; multi-source joint feature data of an actual to-be-detected object and each prototype vector are substituted into the failure weight calculation model to obtain weights of corresponding repair channels, and finally a calculation result of a repair phase is output for each repair channel in a weighted fusion mode; the overall process of the method comprises four stages of multi-source physical feature construction, failure feature coding and prototype modeling, failure weight calculation and multi-channel phase repair fusion, and all the stages are cooperatively completed in the same calculation framework.

The application provides a chip failure type test system, comprising: a detection device configured to output a detection signal to a chip under test; a processing device in communication with the detection device and in electrical communication with the chip under test, the processing device configured to control at least a test frequency and a test power of the detection signal to test the chip under test, and determine whether the chip under test fails and determine a failure type in the case of failure according to an output signal of the chip under test during the test. The system connects the processing device with the detection device, controls at least the test frequency and the test power of the detection signal by the processing device to test the chip under test, and determines whether the chip under test fails and determines a failure type in the case of failure according to an output signal of the chip under test during the test, realizes automatic control of chip testing, and further solves the problem that chip failure types cannot be automatically identified and distinguished in the prior art.

The invention relates to a method and a device for determining a failure type of a storage unit and computer equipment. The method comprises the following steps: acquiring test data corresponding to a failure storage unit in a memory; wherein the test data comprises a logic address of the invalid storage unit in the memory; mapping the logic address into a physical address of the invalid storage unit in the memory layout; according to a preset layout structure rule and a physical address, classifying the failure storage units, and determining a failure type; wherein the layout structure rule comprises an incidence relation between a common physical structure and a physical address of the memory layout. By adopting the method, failure classification errors of the storage units can be reduced, and the accuracy of failure classification is improved.

The application provides a gimbal failure inspection and replacement method based on neighboring machine cooperation and related equipment, and relates to the technical field of general control or regulation systems. The method comprises the following steps: first, determining the digital twin model of each gimbal in the target area to determine whether the target gimbal is failed; combining the digital twin model and the failure type to determine the gap area corresponding to the preset position of the failed gimbal, and dividing the gap area into multiple gap sub-areas with gap risk value labels; then, matching candidate neighboring machines for each gap sub-area and determining the optimal takeover gimbal; combining the digital twin model to generate an inspection execution task sequence containing a replacement task; controlling the optimal takeover gimbal to replace according to the sequence; after the failed gimbal returns to normal, triggering the takeover exit process and restoring the original inspection plan of the optimal takeover gimbal. The method can dynamically and intelligently schedule optimal resources to compensate for the monitoring blind area, minimize the interference with normal inspection tasks, and improve the robustness and reliability of the entire monitoring system.

This invention discloses a data classification method, apparatus, storage medium, and terminal for chip failure types. The method includes acquiring design information of the chip under test (DUT), and based on the design information, acquiring the DUT's size information, logical location-to-physical location correspondence information, and failure type information; acquiring test data of the DUT, and converting the test data into test physical location information based on the size information and logical location-to-physical location correspondence information; clustering the failure positions of the DUT using an optimized clustering algorithm based on the test physical location information to obtain failure clustering results; and classifying the failure positions of the DUT based on the failure type information and the failure clustering results to obtain failure classification results for the DUT. This method improves the efficiency of clustering operations by optimizing the clustering algorithm, saves memory occupied by the operation, and greatly improves the efficiency of chip failure type acquisition; it also improves data reading and saving efficiency and saves storage space.

The embodiment of the invention relates to the technical field of artificial intelligence, and provides a transfer transaction failure compensation method and device, and the method comprises the steps: responding to a transfer transaction failure record, obtaining a transaction log, extracting a transaction feature vector according to the transaction log, inputting the transaction feature vector into a first classification model, and obtaining a first transaction failure type; if the first transaction failure type belongs to the preset classification set, processing according to a preset compensation mechanism; if not, using the word vector model to perform word meaning feature vector extraction and inputting the word meaning feature vector into a second classification model to obtain a second transaction failure type; if the second transaction failure type belongs to the preset classification set, processing according to a preset compensation mechanism; and if not, generating error information and sending the error information to operation and maintenance personnel. Through the embodiment of the invention, the transaction failure type identification accuracy can be improved, so that the transfer failure processing efficiency is improved, and the manual intervention cost is reduced.

There may provide a device and method for controlling an inverter, and a steering system using the same. The device for controlling the inverter may include a failure determiner configured to determine, in response to an occurrence of a failure in an inverter circuit connected to a motor, whether the failure corresponds to a predetermined failure type based on a braking torque of the motor, and a controller configured to control, if the failure corresponds to the failure type, a switching operation of the inverter circuit so as to reduce the braking torque of the motor based on the failure type.

The invention discloses an automatic diagnosis method and device for a fault type of a transmission chain bearing of a wind generating set. The method comprises the following steps: acquiring related file data; performing multi-angle preprocessing to obtain n pieces of CMS reconstruction vibration data; extracting a multi-dimensional characteristic value, and determining a corresponding fault level after normalization weighting; m optimal resonance bands of each piece of CMS reconstruction vibration data are determined; determining n vibration characteristic indexes and m fault diagnosis spectrum sets, wherein each fault diagnosis spectrum set comprises n fault diagnosis spectrums; for each optimal resonance band, n1 effective maps are screened from the corresponding n fault diagnosis spectrums, the occurrence probability of each fault type in each effective map is determined, and the bearing fault type with the maximum occurrence probability is taken as the corresponding bearing fault type; and combining the m bearing fault types, the corresponding final fault maps and the fault levels to form a fault type diagnosis result, and outputting the fault type diagnosis result. According to the invention, the fault type and the fault degree can be accurately diagnosed, and meanwhile, the diagnosis precision is improved.

The present disclosure provides a distributed job system control method, device, equipment, medium and program product, relates to the technical field of computer application, and particularly relates to the technical field of distributed job. The specific implementation scheme is: for a first container carrying a first process, in response to detecting that the first process is triggered to terminate based on the first container failing, determining a current failure type of the first container; if the current failure type is consistent with a target failure type, rebuilding the first container, and restarting the first process based on the rebuilt first container. The present disclosure can rebuild the container for the failure type that can successfully rebuild the container, and does not rebuild the container for the failure type that cannot successfully rebuild the container, so as to save the system operation cost and meet the job demand.

Provided in the present disclosure are an information processing method and apparatus for a conditional handover, and a terminal and a device. The method comprises: sending failure information of a conditional handover candidate secondary cell group to a network side device, wherein the failure information is used for determining a failure type of the conditional handover candidate secondary cell group.

Described are systems and methods for memory failure analysis based on bitline threshold voltage distributions. An example method of implementing a failure type prediction model includes: receiving, by a processing device, a first failure-related dataset reflecting a first bitline threshold voltage distribution associated with a first memory device; determining, based on the first failure-related dataset, a first failure type distribution for the first memory device; creating a training dataset comprising the first failure-related dataset and the first failure type distribution; and training, using the training dataset, a failure type prediction model to determine, for a second memory device, a second failure type distribution based on a second failure-related dataset comprising second bitline threshold voltage data associated with a second memory device.

The invention relates to the technical field of batteries, and discloses a PCB failure rate estimation method and device based on a safety target, equipment and a medium. The method comprises the following steps: determining a safety target parameter and a failure rate threshold value of a preset PCB, and obtaining a PCB layout drawing; screening related function modules in the drawing according to the safety target parameters, and deleting unrelated components to obtain an updated PCB layout drawing; extracting design characteristic parameters in the drawing, and calculating the basic failure rate of each functional module in combination with the preset use environment of the whole vehicle; based on the failure mode classification, the distribution proportion, the safety mechanism and the diagnosis coverage rate corresponding to the safety target parameters, correcting the basic failure rate to obtain residual and potential failure failure rates; and calculating a corresponding random hardware failure probability measure, a single-point fault measure and a latent fault measure by using the failure rate, and comparing with a failure rate threshold to verify the conformity. The problems that an existing method is not associated with ASIL levels, failure types are not distinguished, and dynamic working conditions are difficult to adapt are solved, the BMS function safety compliance requirements are met, and estimation pertinence and accuracy are improved.

The present application belongs to the technical field of automated system testing, and discloses an automated penetration testing method, system, device and medium based on failure attribution driven task local re-planning, to solve the problems that the prior art cannot distinguish failure causes, lacks failure propagation blocking, and global re-planning destroys achievements. The method comprises: constructing a task graph, the task graph comprising nodes and edges representing dependency relationships; selecting a node satisfying a dependency condition to execute a test task; when the node fails to execute, generating a failure attribution code for distinguishing failure types; performing local pruning and path regeneration according to the attribution code: after pruning the failure branch, taking the execution results of the branch root node and the effective nodes as inputs, generating a new task node satisfying the connection constraint and connecting the task graph; performing consistency checking on the updated task graph, and continuing to execute the test. The method effectively improves the stability, traceability and execution efficiency of automated penetration testing.

The invention discloses a giant tire screening method for reducing the abnormal failure ratio of giant tires for strip mines, and relates to the technical field of tires. According to the method, by integrating multi-dimensional key parameters such as the freight distance, the speed, the load, the gradient, the failure type, the environmental condition and the special vehicle type / scene, an I-V-level perfect mine level system is constructed, particularly, customized V-level scenes such as multi-scene combination, the special vehicle type and the extreme environment are covered, and comprehensive and accurate definition of complex mine working conditions is achieved. The corresponding pattern type, pattern depth and pattern saturation of the giant tire are matched based on the grading system, the limitation of traditional empirical type selection is broken, the adaptation of the giant tire product and the mine scene is more targeted, and the abnormal failure risk caused by improper adaptation is reduced from the source.

The invention provides a condition switching information processing method and device, a terminal and equipment. The method comprises the step of sending failure information of conditional switching of a conditional candidate secondary cell group to network side equipment, wherein the failure information is used for determining a failure type of conditional switching of the conditional candidate secondary cell group. In the present application, for the conditional switching of the conditional candidate secondary cell group, the terminal reports the failure information of the conditional switching to the network side device, so that the network side device can determine the failure type of the conditional switching of the conditional candidate secondary cell group based on the failure information, thereby performing corresponding mobility configuration for the determined failure type. The more accurate MRO is realized, the switching success rate is improved, and the network index is improved.

The invention discloses a UI automatic testing method and testing tool of an application program and a storage medium. The test method can be applied to the test of the published Flutter desktop end application program. The testing method comprises the following steps: executing a first operation on a target UI element positioned in a Flutter desktop end application program based on a Flutter special interaction strategy; wherein the Flutter special interaction strategy sends a hardware simulation event or a bottom layer system level input event which can be identified as a high priority by a desktop operating system by calling a native bottom layer input interface of the desktop operating system, and transmits the hardware simulation event or the bottom layer system level input event to a Flutter desktop end application program; and if the target UI element fails to be triggered, analyzing a failure type and executing a proper recovery operation. By adopting the scheme, the compatibility problem of an API (Application Program Interface) in the existing automatic test scheme of the Flutter desktop end application program can be avoided, and a set of multi-level error recovery mechanism is constructed, so that the response success rate of the Flutter desktop end application program during automatic test is further improved.

This application discloses a chip failure type testing method and test circuit. The testing method includes: performing column mode testing on the chip with multiple different test voltages and obtaining a first test result containing failure bit information; activating a first auxiliary module and performing column mode testing on the chip with multiple different test voltages, obtaining a second test result containing failure bit information; wherein, when testing the chip with a test voltage greater than or equal to the chip's operating voltage, if a failure point that was disabled under the first auxiliary module is effective when the first auxiliary module is activated, then the failure point belongs to a soft failure. The chip failure type testing method and test circuit of this application, with the auxiliary module activated or disabled, performs column mode testing on the chip at different test voltages and classifies soft and hard failures based on the output results.

The present disclosure relates to a method, device, equipment and storage medium for processing latent failure, comprising: receiving at least one piece of latent failure information sent by at least one vehicle within a period of time, wherein the latent failure information comprises a vehicle identifier and a failure type; for the vehicle identifier, counting a first number of pieces of latent failure information of each failure type sent by each vehicle identifier; comparing the first number with a first preset number, determining a failure type corresponding to the first number greater than or equal to the first preset number as a first failure type, and determining a vehicle corresponding to a vehicle identifier in the vehicle identifier sending a piece of latent failure information of the first failure type with a number greater than or equal to the first preset number as a target vehicle; and generating prompt information based on the first failure type. The present disclosure can meet the user's vehicle demand by receiving the latent failure information, determining that the target vehicle sends the information of the first failure type multiple times, and prompting to replace the spare parts.

The present application provides a processing method and apparatus, as well as a carrier. The method includes the steps of: determining a first procedure phase in which a failure occurs in an over-the-air (OTA) technology update process; determining a first failure type from among multiple OTA failure types based on the first procedure phase; and determining at least one processing strategy based on the first failure type. The method enables accurate evaluation of the cause of the OTA update failure in the OTA update process, assessing the impact of the OTA update failure, and providing corresponding processing strategies and suggestions.

Embodiments of the present disclosure provide a power failure detection method and device. The method comprises: obtaining power failure entity information; wherein the power failure entity information comprises any two of a power failure device, a component of the power failure device, a failure type of the component, and a failure handling strategy; inputting the power failure entity information into a target power failure detection model, outputting a target failure path corresponding to the power failure entity information and a confidence degree of the target failure path; and performing power failure detection according to the target failure path. According to the embodiments of the present disclosure, the power failure entity information is input into the target power failure detection model, the target failure path corresponding to the power failure entity information and the confidence degree of the target failure path are output, and power failure detection is performed according to the target failure path. In this way, the accuracy of failure detection and the interpretability of failure detection can be improved.