175 results about "Failure causes" patented technology

The embodiment of the invention provides an early failure test method for flash memory particles, a controller and a storage medium, and the method comprises the steps: placing the flash memory particles in a test space, and adjusting the space temperature of the test space to a first test temperature; performing multiple rounds of testing on the flash memory particles according to different block states, target modes and target read-write behaviors at the first test temperature, and writing test data into a test result; reducing the space temperature from the first test temperature to a second test temperature; performing multiple rounds of testing on the flash memory particles according to different block states, target modes and target read-write behaviors at a second test temperature, and writing test data into a test result; and writing the test result into a bad block table, wherein the bad block table is used for recording the position information, the failure reason and the reliability level of the failure storage block. According to the embodiment of the invention, the blocks with poor performance are screened out by means of multiple rounds of experiments in different scenes, different modes and different read-write behaviors, so that the quality reliability of products is improved.

An estimation system includes, a memory having a machine learning model and, a processor coupled to the memory and configured to, analyze a log related to a failure to determine a failure classification of a failure content, cause the machine learning model to extract, from a predetermined technical document, a corresponding sentence corresponding to the determined failure classification, cause the machine learning model to infer a first failure cause based on the corresponding sentence extracted by the machine learning model, and output the first failure cause.

In an implementation of a computer-implemented method: to create extracted data records, an extract filter is instructed to extract relevant data records from log messages of two runs of a software pipeline. To create diff records using the extracted data records, a diff filter is instructed to compare and identify differences in messages between the two runs, where the diff records are amended with labeled data status information of a software pipeline run the extracted data records have been taken from. A recommendation engine is instructed to execute a machine-learning model training with the diff records. The recommendation engine is called to analyze the diff records for a failure-indicator. A determination is made that a failure causing the failure-indicator has been corrected in a later run of the software pipeline. A change is identified in a configuration or version of a software application associated with a correction. A failure-indicator-solution combination is generated.

The invention relates to the technical field of fault early warning of power plant equipment, in particular to a method for generating a fault early warning model of power plant equipment. The method comprises the following steps: acquiring power plant equipment operation data, extracting operation coordination relation data, and constructing a power plant equipment operation simulation model; identifying the coupling interference increase condition of the power plant equipment based on the operation data, and detecting the dynamic suppression load increase condition of the equipment by using the operation simulation model; on the basis, the power plant multi-equipment linkage amplification effect is recognized, and the abnormal fault risk is detected; carrying out extension chain analysis, point location tracing and cause identification on the abnormal fault to form a fault correlation structure chain; constructing a fault early warning model based on fault causes, point locations and extension chain data; according to the invention, the fault early warning model of the power plant equipment is constructed, so that the power plant equipment fault identification is more accurate.

The invention discloses an API calling method and device and a readable storage medium. The method comprises the following steps: receiving a first request for calling a first API sent by user equipment; a parameter checking model is determined according to parameter information extracted from a first API code corresponding to the stored first API, first parameter information included in the first request is checked according to the parameter checking model, and the parameter information comprises at least one parameter name and a parameter type corresponding to each parameter name; a parameter format and one or more of a parameter range; and under the condition that the first parameter information is abnormal, sending a first error response indicating that the specific parameter is wrong to the user equipment. Through the process, the parameters in the request can be checked in time, and specific error information is returned to the user, so that the user equipment modifies the parameters in time, the situation of API calling failure caused by parameter errors can be avoided, and the accuracy and efficiency of API calling are improved.

The invention provides a fault cause determination method, an electronic device, a storage medium and a program product, relates to the technical field of computers, and is used for determining an inspection sequence of a target fault problem based on historical fault data and a scene category to which the target fault problem belongs so as to remarkably improve the accuracy and processing efficiency of a fault diagnosis process. The method comprises the steps of determining a target scene category corresponding to a target fault problem in response to a received target query request; determining a plurality of target check points matched with the target scene category in the plurality of check points; each check point corresponds to one fault reason and is used for judging whether the fault problem is caused based on the fault reason corresponding to the check point; for each target check point, determining the number of times of existence of a target fault reason corresponding to the target check point in the historical fault data set; and according to a sequence of the weights from high to low, fault reason judgment is carried out based on each target check point in sequence, and a fault reason corresponding to the target fault problem is obtained.

The invention relates to the technical field of complex system fault positioning, in particular to a distributed architecture-based positioning fault removal system, which comprises a fault identification module, a fault analysis module, a diffusion suppression module and a fusing module, and is characterized in that the fault identification module, the fault analysis module, the diffusion suppression module and the fusing module are arranged, so that the fault removal efficiency is improved. According to the method, a plurality of types of abnormal data are monitored, corresponding suspected fault information is identified, and the information flow direction of the suspected fault information is confirmed to determine a fault source and a fault influence range when a fault occurs finally, so that each related distributed device having the fault is identified effectively, and the fault detection efficiency is improved. And the problem of troubleshooting failure caused by the fact that the equipment which fails before is not processed is effectively reduced.

The invention provides an exception handling method and device, a storage medium, electronic equipment and a product. The exception handling method is applied to a credit investigation system corresponding to a credit investigation mechanism, and comprises the following steps: receiving a data query request for target data sent by a data demand side, and querying the target data from a data provider according to the data query request; processing the target data returned by the data provider to obtain a processing result; if the data processing result is successful, credit investigation data obtained after the target data is processed is returned to the data demander; if the data processing result is failure, determining a failure type causing data processing failure based on an abnormal state code carried in the data processing result, and triggering an exception processing flow matched with the failure type; wherein different abnormal state codes correspond to different failure types, and the failure types comprise service side failures caused by inconformity with service rules and system side failures caused by abnormity of the credit investigation system.

The invention discloses a log analysis method and device, equipment, a medium and a program product, and relates to the technical field of software testing, and the method comprises the steps: obtaining failure log data of a failure test case, and success log data of a success test case corresponding to the failure test case; extracting target content related to the test failure in the failure log data through a preset large language model; performing semantic comparison on log data corresponding to the test steps in the failure log data and the success log data through a preset large language model to obtain difference information; analyzing the failure log data based on a target cue word through a preset large language model to obtain a failure reason of the failed test case, the target cue word being obtained by combining a first cue word and a second cue word, and generating the first cue word by embedding a target content into a first cue word template; and embedding the difference information into a second cue word template to generate a second cue word. The log analysis efficiency is improved.

The invention discloses a commutation failure detection method and device, equipment and a medium, and the method comprises the steps: carrying out the derivation of the current waveform of each converter valve, and obtaining the curvature of the current waveform of each converter valve; according to the curvature of the current waveform of each converter valve and a preset curvature threshold, determining a corresponding time vector when commutation failure occurs in each commutation condition; combining the corresponding time vectors when all commutation conditions fail, and generating a commutation failure moment matrix; and based on the commutation failure moment matrix, determining the converter valve of the converter with the commutation failure for the first time and the commutation failure moment. According to the method, the converter valve with the first commutation failure of the converter and the commutation failure time are determined through the current curvature of each converter valve, so that the commutation failure position is accurately positioned, subsequent fault processing and maintenance work is facilitated, faults in a larger range caused by the commutation failure are reduced, and the stability of a high-voltage direct-current power transmission system is improved.

The invention discloses a cable fault identification system and method based on parameter jump information, and the method comprises the steps: obtaining fault parameter data at a cable fault moment under the condition that a cable fault is detected; comparing the fault parameter data with historical fault parameter data to determine an initial fault reason; acquiring other parameter data except the fault parameter data in the preset range of the fault moment, and detecting whether a jump point exists in the other parameter data or not; under the condition that the jump point exists, whether the jump point meets the adjustment condition of the cable fault reason or not is judged; if the jump point meets the adjustment condition of the cable fault reason, determining the cable fault reason based on the jump point and the initial fault reason, and if the jump point does not meet the adjustment condition of the cable fault reason, determining that the initial fault reason is the cable fault reason; and under the condition that the jump point does not exist, determining that the initial fault reason is the cable fault reason. According to the technical scheme, the accuracy of fault diagnosis is improved.

To provide a spring device capable of preventing failure due to overload with a simple structure.SOLUTION: A spring device comprises: a case 3 with a shaft body 2 inside; and a spiral spring 4 in which a terminal 5a of an inside end part 5 is engaged with the shaft body 2 and a terminal 6a of an outside end part 6 is in a free state, and which is arranged between the shaft body 2 and the case 3. The outside end part 6 of the spiral spring 4 is wound so as to be in contact with the entire surface of the inner surface of the case, with a length of at least one revolution of the circumference of the inner surface of the case 3.SELECTED DRAWING: Figure 1

The invention relates to a method for determining the cause of a failure in a machine line for filling and packaging food and / or beverages. The machine line comprises a plurality of machines. The method is used to detect operating states for each of the machines and store same as a data set. After an operating standstill of a machine is detected, the period of time of the data set is requested in order to determine the cause of the failure, and said period of time is used as the basis for an input for a spatial-temporal relational graph convolution network. For each machine of the machine line, the stRGCN specifies the probability that the corresponding machine is the cause of the operating standstill.

An object is to estimate a location where a communication failure occurs while reducing a load on an apparatus included in an upper layer in an optical communication system. Terminal stations communicate via an optical transmission line constituting an optical network and include one or more transponders. Failure cause estimation apparatuses monitors states of the transponders provided in each of the terminal stations and estimates a failure probability for each location where an occurrence of a failure is suspected. A failure analysis apparatus estimates a location where there is a risk of failure occurrence and a failure probability at the location where there is the risk of failure occurrence based on failure cause estimation results of the failure cause estimation apparatuses provided in the terminal stations.

The invention discloses a large language model agent system and method and related equipment. The large language model agent system comprises an input analyzer module, a strategy generation module, an execution controller module, a task result evaluation module, an reflection module and a strategy rewriting module, and a self-adaptive optimization closed loop for task execution is formed through the reflection module and the strategy rewriting module. Wherein the reflection module can generate a report containing failure reasons, and the problem of failure diagnosis is solved; the strategy rewriting module optimizes a plan according to a report, adjusts tool calling, and realizes self-learning and strategy reconstruction; the closed-loop design forms a complete cognitive process, and an input analyzer guarantees the stability of prompt. According to the system, the task completion rate, the execution stability and the scene adaptability are remarkably improved, the robustness and the error tolerance in a multi-step complex task are particularly enhanced, and the key blank of an existing language model agent system in the aspects of self-reflection and self-optimization is filled.

The invention discloses a multi-source information driven self-adaptive interface test script generation method. The method comprises the steps that S1, multi-source input fusion is carried out, one or more kinds of test information are obtained from multiple data sources, cross validation and intention alignment are carried out on the basis of semantic understanding, and multi-source test information is generated; s2, unified protocol conversion: converting the multi-source test information into framework-independent standardized intermediate representation through a general protocol conversion layer, and dynamically generating executable scripts of different test frameworks; s3, intelligent scheduling and execution: executing in a local or distributed cluster according to the task scale intelligent scheduling script, and collecting an execution data set; and S4, performing exception attribution and feedback, analyzing an execution result, performing three-dimensional analysis through a multi-source fusion exception attribution engine if the execution result fails, accurately judging that a failure reason is interface update or system Bug, and triggering a corresponding closed-loop response. According to the invention, intelligent generation, cross-framework multiplexing and adaptive maintenance of the test script are realized.

The present application discloses a data integration method, device and computer-readable storage medium, the method comprising: executing a first data integration request sent by a target system to obtain a data integration result; if the data integration result is a failure, counting the number of integration failures of the first business data and recording the cause of the failure; after determining that a first preset condition is satisfied, executing the first data integration request again. By means of the above method, when the data integration request processing fails, that is, when the data integration fails, the request can be automatically reprocessed at a scheduled time or after the cause of the failure is eliminated, or the request can be reprocessed based on user operations, without waiting for technical personnel to check and repair one by one, thereby improving the processing efficiency when data integration errors occur, improving the integration efficiency of the business data of the target system, and thereby improving the data consistency between the target system and the data.

The invention provides an operation and maintenance failure analysis and diagnosis method and device, electronic equipment and a storage medium, and relates to the technical field of computers.The method comprises the steps that related texts of operation and maintenance failures are obtained, and the related texts comprise log texts and / or question texts input by a user and related to the operation and maintenance failures; matching the related text with a pre-constructed knowledge graph, and determining at least one recommended question text corresponding to the related text from the knowledge graph; and on the basis of each recommended question text, diagnosing the cause of the operation and maintenance failure. Through the related text of the operation and maintenance failure and the pre-constructed knowledge graph, accurate diagnosis and analysis of the operation and maintenance failure reason are realized, the accuracy and efficiency of diagnosis of the operation and maintenance failure reason are improved, and meanwhile, the solving efficiency of user problems and the user experience are improved.

Embodiments include methods for a user equipment (UE) configured to communicate with a wireless network via a master cell group (MCG) and a secondary cell group (SCG). Such methods include detecting a failure in the SCG and selecting a failure cause. The failure cause is selected from the following: a first set of causes associated with an earlier version of communication functionality, and a second set of causes associated with a later version of communication functionality. Such methods include sending a failure information message to a network node that provides the MCG, wherein the failure information message indicates whether the failure cause is one of the first set or one of the second set. Other embodiments include complementary methods for a network node that provides the MCG, as well as UEs and network nodes configured to perform such methods.

The invention discloses a fault analysis method and device, electronic equipment and a computer program product. The method comprises the steps of obtaining a to-be-detected operation and maintenance field sequence of a service platform under the condition that the service platform has a target fault; analyzing a plurality of to-be-detected fields in the to-be-detected operation and maintenance field sequence by using a preset prediction model to obtain at least one pre-estimated fault reason causing the target fault and a pre-estimated fault score of each pre-estimated fault reason, according to the target fault, at least one pre-estimated fault reason, at least one associated fault of the target fault, an associated fault reason of each associated fault and an associated fault score of each associated fault reason, obtaining a predicted fault score corresponding to each pre-estimated fault reason; and determining the estimated fault reason with the highest predicted fault score as a target fault reason, and generating a target disposal opinion for the target fault reason. The technical problem that traditional fault analysis is poor in accuracy is solved.

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.

The present application relates to a battery failure analysis method, device, equipment, storage medium and program product. The method includes: obtaining a failure mode and a first failure feature of a target battery; wherein, the failure feature is used to characterize observable failure phenomena; determining a target failure analysis tree according to the failure mode, and performing factor matching processing in the target failure analysis tree according to the first failure feature to obtain a failure factor set; wherein, the failure factor set includes at least one first failure factor, the failure analysis tree is pre-constructed based on a plurality of second failure factors and a plurality of second failure features, and the failure factor is used to characterize the failure cause; collecting production process data according to the failure factor set; performing statistical processing on the production process data to determine the failure cause of the target battery. Using the present application can improve the failure analysis speed and the failure cause location efficiency.

The invention relates to the technical field of logistics large models, and discloses a testing method and system based on the context of a large model in the logistics field, and the method comprises the steps: 1, preparing a single-round successful testing record of an entity and an intention which need to be generated, guaranteeing that the corresponding entity or intention is inherited and switched for assembly when a plurality of rounds of use cases are generated, the prepared single-round successful test records form a basic data set; step 2, determining parameters required for generating multiple rounds of use cases; 3, filtering and classifying single-round test records; step 4, generating a multi-round use case; 5, converting the multi-round use cases into executable tasks, and calculating a model success rate; and step 6, counting failure distribution and feeding back. The test method and system can accurately capture the performance of the model in complex interactions such as intention inheritance and switching, assist in rapidly improving the capture and understanding ability of the logistics large model for context information, and reduce intelligent dialogue errors caused by context faults.

The invention discloses a test report enhancement method and device based on historical test data and a medium, and the method comprises the steps: executing each test case corresponding to a test script to obtain an execution result, and storing the execution result in a preset execution result record; after the test task is executed every time, the number of continuous failures of the test script in the preset test period is determined; if the number of continuous failures exceeds a preset threshold value, triggering a historical failure reason identification mechanism for the test script, and generating a historical failure reason list corresponding to the test script based on the historical failure reason identification mechanism; and adding a historical failure record block in the test report configuration file, screening out a specified test script meeting a preset failure condition, and filling a historical failure reason list corresponding to the specified test script into the historical failure record block so as to jointly display the historical failure reason list and the execution result.

Embodiments of the present disclosure relate to reporting preconfigured uplink transmission failures. According to embodiments of the present disclosure, a terminal device records failures and failure causes associated with transmissions on preconfigured resources. The terminal device transmits this recorded information to a network device. In this way, the network device is informed of the occurrence and cause of the failure. The network device can use this information more efficiently to configure uplink resources, and the resources can be efficiently allocated for other purposes or other terminal devices.

The present invention addresses the problem in that when AI training is performed on the basis of the work record of a low-skilled worker, erroneous inference results are obtained for a failure cause and a countermeasure plan.　A representative failure cause analysis device according to the present invention comprises: a work record storage unit that stores work records including a failure event that has occurred, a failure cause, and information about a countermeasure work for the failure event; a work record selection unit that selects, from the work records stored in the work record storage unit, a work record to be used for training a generative AI on the basis of a predetermined condition; and an inference unit that trains the generative AI for a newly occurred failure event on the basis of the work record selected by the work record selection unit, and infers a failure cause and a countermeasure work for the newly occurred failure event using the trained generative AI.

The present invention provides a calibration failure repair method, device, equipment and readable storage medium. The calibration failure repair method includes: when the air suspension detects that the height sensor calibration fails, identifying the cause of the calibration failure; transmitting the cause of the calibration failure to the calibration equipment; the calibration equipment obtaining the vehicle identification code and transmitting the vehicle identification code and the cause of the calibration failure to the repair equipment; the repair equipment matching a repair method according to the cause of the calibration failure; when the terminal scans the vehicle identification code, the repair equipment displays the cause of the calibration failure and the repair method. Through the present invention, the air suspension detects and identifies the cause of the height sensor calibration failure, further transmits the cause of the calibration failure to the calibration equipment and the repair station equipment, and matches the repair method. By scanning the vehicle identification code, the cause of the calibration failure and the repair method are displayed and provided to the repair personnel, so that the repair personnel can quickly know the cause of the calibration failure and can quickly perform repairs according to the repair method.

The invention belongs to the technical field of automatic compiling, and particularly discloses a multi-agent-based multi-language automatic compiling method and system, and the method comprises the steps: carrying out the project analysis and information extraction of a to-be-compiled project, and obtaining project meta-information; calling a multi-language construction knowledge base based on the project meta-information, and dynamically generating a construction command sequence adaptive to the current environment; executing construction commands in the construction command sequence, capturing standard output, standard errors and exit codes in real time, and outputting a construction result; and performing multi-dimensional verification on the construction result to obtain a comprehensive verification score, obtaining a judgment result based on the comprehensive verification score, and outputting a visual construction report based on the judgment result. According to the method and the device, the problem of construction task failure caused by environment difference, low efficiency of error diagnosis and insufficient product verification can be solved, and the success rate and the accuracy of the construction task are improved.

The invention discloses a trusted tool calling guarding closed-loop method, and belongs to the technical field of penetration testing, the trusted tool calling guarding closed-loop method helps a tool calling model to generate a more reasonable initial instruction through similarity matching, the accuracy and applicability of instruction generation are improved, an interactive instruction approval step can prevent error instruction execution from the source, and the accuracy and applicability of instruction generation are improved. According to the method, the safety and the stability of the tool execution process are guaranteed, penetration test faults caused by wrong instructions are effectively avoided, traceability and interpretability of the execution process are achieved through the instruction chain, subsequent analysis and troubleshooting of the penetration test process are facilitated, the preference instruction storage step is further set, and the method is easy to implement. The model can continuously learn expert experience, progressive optimization of parameter configuration and decision consistency enhancement are achieved, the accuracy of subsequent instruction generation is improved, on the whole, the stability, safety and reliability of a penetration system are comprehensively improved, and it is ensured that penetration testing can be efficiently and smoothly carried out.

The invention discloses a dynamic equipment fault early warning method and device for a cryogenic helium extraction production line. The method comprises the steps of obtaining a current operation data set corresponding to target moving equipment, wherein the current operation data set comprises multiple pieces of current operation data corresponding to each target parameter; inputting the plurality of current operation data corresponding to each target parameter into an early warning model to obtain an early warning result corresponding to the target moving equipment; when the early warning result is the predicted fault type corresponding to the target moving equipment, determining a predicted fault reason and a fault solution corresponding to the target moving equipment according to the predicted fault type; and outputting and displaying the predicted fault type, the predicted fault reason and the fault solution corresponding to the target moving equipment.