60 results about "Repair - action" patented technology

The invention relates to the technical field of application state diagnosis, in particular to an application state dynamic diagnosis and automatic repair method and system.The method comprises the steps that multi-source heterogeneous logs are collected and standardized in real time, key fields are extracted, context information is injected, and structured log data are generated; inputting the structured log data into a dynamic anomaly detection model, constructing a dual-path detection mechanism based on LSTM time sequence analysis and a graph neural network, identifying an abnormal mode and positioning a fault root cause; according to the output of the anomaly detection model, a repair action is triggered in a grading manner through an intelligent repair strategy engine; in the repairing process, system state changes are stored and recorded through a pre-writing type redundancy log, automatic rollback during abnormity is achieved on the basis of check point information, and data consistency and system stability are guaranteed. The problem of service interruption or data inconsistency possibly caused by traditional automatic repair is avoided, and the reliability of automatic operation and maintenance is improved.

The invention provides a micro-service performance problem diagnosis and repair method and system, and the method comprises the steps: obtaining various data of the operation of a micro-service system, carrying out the preprocessing of the obtained data, extracting features, and carrying out the preliminary anomaly detection; using the trained large model to identify the root cause of the micro-service performance problem, and converting each item of data into a state representation which can be understood by an intelligent agent in reinforcement learning; triggering a reinforcement learning process according to a preliminary anomaly detection result, representing a repair action adopted by a decision according to a current state, and in a decision process, guiding an intelligent agent to learn a strategy capable of effectively repairing a problem and minimizing negative effects by a target bit of a reward function; and converting the repair action obtained by the decision into actual operation, obtaining various data of operation of the micro-service system after the actual operation, calculating a reward value of the action according to the reward function, and performing large model optimization. According to the invention, the availability of the micro-service system and the stable operation of services can be guaranteed.

The invention discloses a server repairing method and electronic equipment, and relates to the technical field of computers, and the server repairing method comprises the following steps: inputting hardware monitoring data and software monitoring data into a preset fault prediction model to obtain a fault time point, under the condition that a hardware event determined by the hardware monitoring data and a software event determined by the software monitoring data meet a preset association condition, a fault source event is positioned according to the hardware event and the software event based on a preset fault knowledge graph; and determining a repair action from a preset self-healing strategy library according to the fault time point and the fault root event, generating an execution signal according to the repair action under the condition that the repair action passes sandbox verification, executing the repair action based on the execution signal, and sending a feedback result after the repair action is executed to a preset terminal. The problems that a server monitoring mode is single in monitoring dimension, lagged in fault response and insufficient in communication coverage are solved, and the operation and maintenance efficiency and reliability of the server are remarkably improved.

The invention discloses an abnormality diagnosis and repair method and device for an automatic process of a robot and a medium, and relates to the technical field of artificial intelligence. The anomaly diagnosis and repair method for the automatic process of the robot comprises the following steps: acquiring RPA anomaly processing data; matching the RPA exception processing data with a target causal knowledge base to obtain an exception scene repair action; and according to the abnormal scene repair action and the large language model, generating a process repair script, and according to the process repair script, performing abnormal scene process repair. According to the technical scheme provided by the embodiment of the invention, the handling effect of the PRA in the exception handling scene can be greatly improved on the premise of low maintenance cost.

The invention discloses a dynamic monitoring alarm system for a distributed storage system, and the system comprises a data collection layer which is used for obtaining the monitoring data of each node, and adjusting the collection frequency and granularity according to the first characteristic of the monitoring data; the data transmission and storage layer is used for determining a corresponding independent storage database according to the IP information of the monitoring acquisition equipment; the intelligent analysis layer is used for performing threshold prediction on the preprocessed storage time sequence data to generate an alarm threshold; the method comprises the following steps: receiving monitoring time sequence data, generating an index association graph, when any received monitoring time sequence data exceeds a corresponding alarm threshold value, sending alarm event information, and inhibiting alarm information sent by other monitoring data of the monitoring time sequence in the association graph; judging and suppressing the same alarm event; and the alarm self-healing layer is used for querying whether a corresponding repair action instruction exists in a repair strategy library according to the sent alarm event, and if yes, executing the repair action instruction. Through the system, the alarm accuracy is improved, and the alarm storm is avoided.

The invention relates to the field of artificial intelligence, and particularly discloses a system repair and risk control dynamic balance method, which comprises the following steps: when a preset data acquisition condition is met, acquiring system operation state information, risk state information and repair historical data of a computer system, and vectorizing the information to obtain a state feature vector; defining a repair action space set comprising a plurality of repair actions; constructing a reward function; inputting the state feature vector into a reinforcement learning model, and outputting an optimal repair action; acquiring a real-time system operation state index of the computer system, and comparing the real-time system operation state index with a preset business red line threshold value; if the real-time system operation state index does not exceed the business red line threshold value, the optimal repair action is executed; if any real-time system operation state index exceeds a business red line threshold value, a replacement repair action is executed; and updating the state feature vector and the reward value of the computer system, and updating the parameters of the reinforcement learning model.

Systems and techniques are disclosed for automated damage reporting and repair assessment for automated teller machines (ATMs). An example technique may include detecting damage to an ATM using a sensor. Based on the detected damage, the example technique may include performing a damage assessment and generating a damage report including at least one of a level of damage, a type of damage, a recommended repair action, or an indication to dispatch a technician. The example technique may include outputting the damage report.

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.

The embodiment of the invention provides a data transmission method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining target transmission data of a transaction party, judging whether abnormal data exists in the target transmission data or not according to a preset semantic rule set, and if the abnormal data exists, sending the abnormal data to the transaction party; if the abnormal data is the repairable data, identifying whether the abnormal data is the repairable data according to a repair rule, and if the abnormal data is the repairable data, repairing the repairable data according to a preset repair action indicated in the repair rule to obtain the repaired transmission data, and transmitting the repaired transmission data and qualified data except the abnormal data in the target transmission data to a receiver.

A repair device and method for repairing damage around the leading edge of a wind turbine blade (20) are provided. The repair device includes a robotic maintenance device (40) and an unmanned aerial vehicle (UAV) (62) that can move the maintenance device (40) between a storage position and an operation position, the former being mounted on a blade (20) of the wind turbine (10). The UAV (62) hovers and remains connected to the maintenance device (40) during operations at the blade (20) to minimize a total operational downtime needed to conduct the repair actions. The UAV (62) is secured to the maintenance device (40) by at least one support line (68) that carries the weight load of the maintenance device (40) and at least two control lines (72) that prevent undesired rotations of the maintenance device (40), thereby improving precision and accuracy of UAV-driven movements of the maintenance device (40). A transport container (24) may also be provided to define the storage position, the transport container (24) including an elongated slot (70) for guiding movement of the lines (68, 72) and the maintenance device (40) during movements into and out of a storage space within the container (24).

The invention discloses a local adjustment method and system for electric transmission line tower arrangement, belongs to the technical field of electric transmission line design, and aims to solve the problems of local violation, high global optimization cost, lack of a self-adaptive repair strategy and dependence on experience decision in traditional manual arrangement. The method comprises the following steps: firstly, carrying out conductor sag fitting and comprehensive checking of sag, ground clearance, crossing and windage yaw on a tower arrangement scheme; recognizing a violation tower position according to a result, and determining a local repair section; then generating candidate repairing actions such as tower moving, tower height increasing and tower inserting; then constructing a multi-objective optimization model, quantifying the repair cost and sequencing the actions; and finally, executing the action according to the priority, and iteratively checking until the hard constraint is met. The method focuses on local repair, reduces the cost, improves the efficiency, adapts to multiple voltage grades and complex terrains, and provides intelligent support for pole tower arrangement design.

An inspection system and method of operation may include receiving sensor data for a component of a powered system, and determining an expected failure time of the component at which the component is expected to fail based at least in part on the sensor data. The expected failure time occurring on a timeline. A window start time may be determined on the timeline that is after a current time but is prior to the expected failure time. The window start time and the expected failure time may define a window time range that extends between the window start time and the expected failure time on the timeline. One or both of a repair action or a maintenance action of the powered system may be scheduled at a scheduled time occurring during the window time range and at a time prior to the expected failure time on the timeline.

This invention discloses a real-time diagnostic system for a professional stage lighting control system, belonging to the field of stage lighting technology. It includes a health monitoring module for assessing the health status of the equipment; a behavior verification module for verifying the equipment's execution behavior; an output verification module for verifying the actual output results of the equipment; a fault tracing module for determining the fault type and identifying upstream anomalies; and a feedback repair module for generating feedback based on the fault type and sending repair action commands to equipment that meets repairability conditions. This invention achieves stable operation and rapid response of the lighting control system in a stage performance environment through full-process variable tracking, dimensional normalization, and the introduction of explanatory factors.

Aspects of the disclosure mitigate effects of damage to neural networks (NNs) onboard a platform using a primary NN trained to perform a primary task and a repair agent trained to repair the primary NN. The repair agent performs the steps of detecting a degradation of the primary NN's ability to perform the primary task and performing a repair action to repair the primary NN. The primary task is then performed by the repaired primary NN.

The invention discloses an automatic repair type frequency source and an implementation method thereof, and belongs to the technical field of radar communication and frequency synthesis. In order to solve the problems that after a traditional frequency source breaks down, the maintenance efficiency is low, and the shutdown loss of a system is large, a double-backup hardware architecture of two sets of phase-locked loops and two sets of radio frequency signal conditioning circuits is adopted, intelligent management of power supply and signal paths is achieved through a radio frequency switch network, and the working state of each assembly is collected in real time through a monitoring module; and the FPGA control unit executes an automatic repair action based on a locking detection signal and a level signal fed back by the monitoring module, so as to realize instant diagnosis and seamless switching of a fault. According to the invention, the fault repair time is shortened from several days in the prior art to milliseconds, the zero-shutdown operation of the system is realized, the economic loss of hundreds of thousands of yuan is effectively avoided by increasing the hardware cost of thousands of yuan, and the usability and maintainability of the high-reliability electronic system are remarkably improved.

Disclosed herein are system, method, and computer program product embodiments for proactive equipment machine health monitoring and self-healing using sensors & AI, comprising: applying a machine learning model to a first sensor reading, wherein the first sensor reading comprises a condition associated with a beverage system; predicting a repair action based on applying the machine learning model, wherein the repair action comprises a step to address the condition at the beverage system; executing the repair action at the beverage system; and generating an output by applying the machine learning model to a second sensor reading.

Techniques for predictive system repair are disclosed. Based on attributes associated with application of one or more system selected repair actions to one or more problematic system behaviors in a system (e.g., a database system), the system determines a predicted effectiveness of the repair actions to one or more future applications of a particular problematic system behavior up to one or more future times. The system determines that the predicted effectiveness of one or more future applications of the repair action is positive, but does not meet performance criteria. In response to determining that the predicted effectiveness is positive but does not meet the performance criteria, the system generates a notification that the predicted effectiveness does not meet the performance criteria. The system applies a repair action to a particular problematic system behavior, although it has been determined that the predicted effectiveness does not meet one or more performance criteria.

The invention discloses a power transmission line dynamic first-aid repair scheduling and path planning method and system under disasters, and relates to the technical field of power emergency first-aid repair, and the method comprises the steps: sensing the topological dynamic change of a power transmission line under the disasters in real time, fusing the geographic position priority of important users and the distribution information of first-aid repair resources, and carrying out the first-aid repair scheduling and path planning. Constructing a dynamic resource scheduling model under various constraint conditions; and generating a first-aid repair path based on a fastest path algorithm, establishing a recoverability evaluation system including dimensions such as resource matching degree and topological connectivity, and triggering a first-aid repair action when an evaluation value reaches 80% or above. According to the method, the problems that the traditional emergency repair scheduling response is lagged, the path planning is separated from the disaster real-time scene, and the resource configuration and the recovery demand are not matched are solved, the accuracy, the dynamic property and the high efficiency of the emergency repair of the power transmission line under the disaster condition are realized, and the post-disaster recovery efficiency of the power grid is remarkably improved.

The present application relates to the technical field of metal plate intelligent repair, and specifically discloses a stainless steel cathode plate self-adaptive repair method and system simulating manual operation. The method comprises: obtaining current three-dimensional topography data of the cathode plate to be repaired; inputting the data into a first machine learning model trained based on multi-modal expert data to generate an initial repair action sequence; controlling a repair execution unit to execute the sequence, and online obtaining intermediate three-dimensional topography of the cathode plate as a state during the repair process; driving a reinforcement learning algorithm based on the difference between the state and a target state to dynamically adjust subsequent repair actions; and data of successful cases will be used to update a training database and retrain the first machine learning model. The method can solidify expert experience through imitation learning, and realize online adaptive decision-making in combination with reinforcement learning, thereby achieving individualized high-precision repair of various complex deformations, and the flatness after repair can reach below 0.5 mm, and the system has continuous optimization capability.

The invention provides a method for autonomously repairing and controlling instability of a bogie and a railway vehicle. Wheel out-of-roundness problems such as wheel equivalent taper, radial run-out and wheel high-order polygon are autonomously repaired by detecting the wheel equivalent taper, the radial run-out and the wheel high-order polygon and grinding a wheel tread; releasing wheel equivalent taper, radial run-out and wheel high-order polygon alarms, automatically repairing high-pressure intermittence, low-pressure intermittence and low-pressure continuity through the wheel equivalent taper and radial run-out, and comparing a high-pressure continuity mode with a non-grinding sub-mode to obtain the relationship between the repairing action mileage and the wheel tread modification efficiency; the method is used for restraining rapid growth of wheel out-of-roundness problems such as wheel equivalent conicity, radial run-out and wheel high-order polygons. The relation between the millstone different-mode mileage and the wheel equivalent conicity radial run-out growth rate is obtained.

The invention discloses a restoration method and device based on dynamic call ticket abnormity and electronic equipment, and the method comprises the steps: firstly obtaining original call ticket data, then carrying out the preprocessing of the original call ticket data, obtaining structured data, carrying out the data fusion based on the structured data, obtaining multi-source data, carrying out the abnormity detection of the multi-source data through a first preset mode, and obtaining a dynamic call ticket abnormity result. The method comprises the steps of obtaining first abnormal information, classifying the first abnormal information through a first preset model to obtain a classification result, processing the classification result based on a first preset strategy to obtain a content-level repair scheme, and finally processing the content-level repair scheme based on a second preset model to obtain a repair action sequence. And the abnormal ticket is automatically repaired based on the repairing action sequence, so that waste of human resources is avoided.

An apparatus includes memory to store computer-readable program code for a knowledge-based system including an inference engine and a knowledge base, and processing circuitry configured to access the memory, and execute the code. The apparatus is caused to at least receive a time series of measurements of operating conditions of a machine recorded during an operation of the machine. The apparatus is also caused to cluster the time series of measurements into one or more respective clusters and identify a pattern across the clusters. The apparatus is also caused to define a current state of the machine that includes the pattern across the clusters, access and search a knowledge base for a historical case describing a respective solution to a historical problem state similar to the current state, the respective solution including a repair action, and generate an output display indicating the repair action to address the current state.

System and methods for automated responses to M-Plane fault management in a Radio Access Network.

This application relates to a throttle control method, a vehicle, and a storage medium. The method includes: acquiring throttle jamming determination parameters; and sending a shutdown request to a power controller when the jamming determination parameters exceed a preset parameter threshold and the duration exceeds a preset time. The power controller responds to the shutdown request by controlling the engine to shut down, and after the engine shuts down, it performs a throttle repair action. By performing the throttle repair action while the engine is shut down, the repair drive action is decoupled from the engine's real-time operating conditions, eliminating the conflict between the repair drive action and the engine's torque demand at the source, avoiding safety hazards caused by torque mismatch, effectively relieving temporary throttle jamming and quickly restoring normal control, significantly improving the overall vehicle driving experience and ride smoothness.

The GPU graphics processor fault repair method and system provided in this application first determines the connectivity fault tolerance threshold based on the node communication topology of the currently running training service. This threshold represents the actual node communication dependencies of the training service. Then, it enters the fault batch division stage. Using the connectivity fault tolerance threshold as a constraint, the batch division is completed in combination with the error information reported by the faulty nodes. This ensures that the repair scale of each batch does not exceed the safety limit that the service can bear, avoiding the risk of service communication interruption and training task crash caused by repair actions. At the same time, it can maximize the number of repaired nodes in a single batch within the safety boundary. This solves the problems of extremely low efficiency of single-node rolling repair and lack of safety guarantee of experience-based batch repair in the existing technology. Batch fault repair can be completed without interrupting the training task during the GPU repair process.

The aim is to improve the convenience of remote device repair. [Solution] The network device in the system of the present invention includes means for transmitting operational information to a device management system, means for executing a remote repair process in response to instructions from the device management system, means for receiving information on candidate automatic repair actions from the device management system, and means for executing processing for automatic repair based on the information on candidate automatic repair actions without executing the remote repair process, with the user's consent.

The invention belongs to the field of memory control, and provides a memory control method and a storage device.The method comprises the steps that a maintenance strategy setting command from a host system is received, and the command is used for configuring maintenance strategy data for a specified logic area; updating a maintenance record in a key data maintenance table according to the command, wherein the maintenance record comprises maintenance strategy data and dynamic metadata of a logic region; dynamically selecting a target logic area from the logic areas associated with the key data maintenance table, and executing background health examination on the target logic area; and according to a health examination result, triggering a grading repair action on the target logic region. According to the method, the reliability strategy is flexibly defined by the host, closed-loop management of health monitoring and hierarchical repair is autonomously executed by the storage device, the data degradation trend can be actively found and processed, and the reliability and maintainability of the storage device are effectively improved.

The invention discloses a computer intelligent service management system and method based on network big data, and belongs to the technical field of operation and maintenance management. Comprising a data stream generation module used for forming a context-aware data stream carrying a management intention; the knowledge network generation module is used for forming a knowledge network for business intention query; the candidate set generation module is used for generating a root cause candidate set with priority; and the action execution module is used for executing corresponding automatic repair actions. According to the method, the technical effects of intelligent association analysis of operation and maintenance data, accurate root cause positioning and system self-healing capability are achieved by constructing the context sensing data flow injected with service semantics, establishing a multi-dimensional context index knowledge network and realizing an automatic repair mechanism based on priority evaluation; the problems of weak operation and maintenance data relevance, low fault positioning efficiency and low manual response speed in the prior art are solved.

Disclosed herein are system, method, and computer program product embodiments for proactive equipment machine health monitoring and self-healing using sensors & AI, comprising: applying a machine learning model to a first sensor reading, wherein the first sensor reading comprises a condition associated with a beverage system; predicting a repair action based on applying the machine learning model, wherein the repair action comprises a step to address the condition at the beverage system; executing the repair action at the beverage system; and generating an output by applying the machine learning model to a second sensor reading.

The invention discloses a fault repairing system and method for protective film winding equipment, and relates to the technical field of protective film automatic winding equipment, the fault repairing system comprises a control unit, a plurality of first sensors and a plurality of driving units; each first sensor is used for acquiring real-time position information of the execution mechanism connected with the first sensor; the control unit is used for receiving the real-time position information, sent by the first sensors, of the execution mechanisms; according to the real-time position information of all the execution mechanisms, a target execution mechanism is determined, a control signal for the target execution mechanism is generated, the control signal is sent to a driving unit connected with the target execution mechanism, and the target execution mechanism is the execution mechanism which breaks down; and each driving unit is used for driving the target execution mechanism connected with the driving unit to execute the repair action when receiving the control signal. When the protective film winding equipment breaks down and shuts down, automatic repair can be achieved, and the maintenance efficiency and reliability are improved.