160 results about "System recovery" patented technology

The invention relates to the field of traffic engineering, and discloses an urban road network toughness management platform and evaluation method based on dynamic cascade failure, and the platform comprises a disturbance scene simulation and random capacity degradation module, a dynamic cascade failure process simulation module, and a multi-dimensional toughness index calculation and uncertainty evaluation module. A toughness three-dimensional vector is formed by integrating system robustness, restorability and performance accumulated loss, and a time-varying dynamic traffic distribution model considering road network structure change is used for depicting a cascade failure dynamic process; a random variable is introduced into a damaged road section capacity index, and a new evaluation method is provided for solving the defect that the existing toughness evaluation method is difficult to comprehensively quantify the robustness and the restorability of a road network. A failure diffusion mechanism in an abnormal scene is truly restored, and an effective method is provided for overcoming the double defects that a traditional model is insufficient in quantification of travel behavior dynamics and a system recovery process.

The invention discloses a power load prediction method, and the method comprises the steps: firstly solving an extreme event data sparsity problem through a generative adversarial network, and constructing an event time sequence library through a time sequence anomaly detection algorithm; then analyzing the causal relationship between the event and the load by applying a causal discovery algorithm, and converting prediction output into probability distribution by adopting a Bayesian neural network to quantify uncertainty; constructing a prediction model triggered by an event, and generating a multi-time scale probability prediction interval; and finally, generating a multi-scene prediction result through Monte Carlo simulation, quantifying the system recovery capability in combination with a toughness index, and integrating the system recovery capability to a decision support system to generate a risk response scheme. According to the method, the accuracy and robustness of load prediction under the extreme climate are remarkably improved, full-chain risk insight from early warning to recovery is realized, and prospective decision support is provided for safe operation of a power system.

The invention discloses a system recovery method and system. The method comprises the following steps: configuring an environment variable partition; network rescue server parameters are pre-stored in the environment variable partition, a first-stage starting command, a second-stage starting command, a third-stage starting command, a network rescue command and a main starting command are defined, and the main starting command initially points to the first-stage starting command; starting for the first time, reading and executing a first-stage starting command from the environment variable partition by the universal boot loader; after execution of the first-stage starting command fails and a system is triggered to be restarted, the universal boot loader reads the updated main starting command from the environment variable partition, and the second-stage starting command and the third-stage starting command are executed in sequence; and when the third-stage starting command fails, the universal boot loader executes the network rescue command, downloads a recovery file from the network rescue server and repairs the system.

The invention discloses a BMC firmware starting method and device, equipment, a medium and a program product, and relates to the technical field of server management.The BMC firmware starting method comprises the steps that when a main mirror image file is damaged, BMC firmware is restarted on the basis of a standby mirror image file, if starting fails, the BMC firmware is restarted on the basis of a latest mirror image file of a remote server, and if starting fails, the BMC firmware is restarted on the basis of the latest mirror image file of the remote server; if the BMC firmware is started abnormally, the BMC firmware is restarted based on the local minimum mirror image file, so that the problem that a double-mirror image backup mechanism still faces system paralysis can be solved, a multi-stage mirror image file recovery mechanism is constructed through the multiple pre-deployed mirror image files, when the BMC firmware is started abnormally, the system is recovered step by step according to the multi-stage mirror image file recovery mechanism, and the system recovery efficiency is improved. The technical effects of ensuring the minimum availability of the system and improving the reliability and safety of the system are achieved.

The invention discloses a restart control method and device of a server processor, a storage medium and electronic equipment, and relates to the field of servers, and the method comprises the following steps: detecting the running state of the server processor, and storing a recovery file for the server processor according to the running state of the server processor, then the server processor is controlled to recognize the first controller as an external storage medium, and then the server processor is controlled to restart the external storage medium as a starting item which is preferentially executed in the starting process, so that the server processor can directly obtain a recovery file from the first controller when needing to be restarted; the executive program contained in the recovery file can guide the temporary operating system after the server processor is restarted, and the temporary operating system can provide an operating environment required by system recovery for the server processor, so that the technical problems of poor restarting reliability and the like of the server processor are solved; the technical effect of improving the restart reliability of the server processor is achieved.

The invention discloses a system quick recovery method and system based on system mirror image management, and the method comprises the steps: initializing a boot partition of a functional blade in a heterogeneous cluster system and a boot flag bit of the boot partition, the boot flag bit being used for BIOS reading to select a corresponding boot partition when the functional blade is started; the method comprises the following steps: triggering a job operating system or a boot operating system of a target function blade to restart through a soft shutdown interface, and modifying a start boot flag bit in a BMC (Baseboard Management Controller) of the target function blade, so that the target function blade is sequentially restarted and switched into the boot operating system from the job operating system; and executing system quick recovery or backup for the target system partition under the boot operating system, and then restarting and switching to run under the specified job operating system so as to complete system quick recovery or backup. According to the method, the characteristics of the heterogeneous cluster system are combined, and automatic and flexible system mirror image fast rollback recovery is achieved when the heterogeneous cluster system has a serious fault.

The invention discloses an intelligent early warning and decision making system and method based on large model driving. The intelligent early warning and decision making system comprises a server log data layer which is responsible for collecting various log data generated in the operation process of a server; the filtering layer is used for undertaking a task of quickly screening abnormal log information; the retrieval layer is used for matching similar or relevant information in a risk library for each abnormal log; the Agent analysis and decision-making layer is used for carrying out deep analysis on abnormal conditions by utilizing natural language processing and knowledge reasoning capability of an intelligent deep large model so as to identify attack types and formulate personalized defense schemes; the defense layer is responsible for calling a built-in defense tool library to execute a defense scheme; the execution layer is used for converting an instruction of the defense layer into a specific operation automatically executed through a script; the monitoring layer is used for monitoring results in and after scheme execution in real time; the inspection layer is used for automatically inspecting the production line after monitoring is normal; and the analysis layer is used for carrying out automatic chart analysis on attack or risk data. According to the invention, automatic processing from attack detection to system recovery is realized, and the response efficiency is improved.

The invention relates to the technical field of heat supply system recovery, and discloses a heat supply system heat transfer intelligent recovery method based on an LSTM neural network. The method comprises the following steps: firstly, collecting thermodynamic parameter time sequences of water supply temperature, water return temperature, pipe section flow, environment temperature and the like of each monitoring node of the heat supply pipe network; performing standardization processing on the time sequences, eliminating influence of different physical quantity lines, and generating a standardized thermodynamic time sequence; then, the heat supply pipe network is divided into a plurality of functional areas according to the topological structure and the thermal characteristics, and each area comprises a plurality of associated monitoring nodes; the LSTM neural network is used for deeply analyzing processed data and divided areas, intelligent heat transfer recovery of the heat supply system is achieved, the dynamic change rule of parameters can be accurately captured, the method adapts to complex working conditions, heat transfer recovery is more targeted and reasonable, heat energy waste is reduced, and the operation efficiency of the heat supply system is improved.

The invention discloses a low-voltage-crossing adaptive control method and device of a wind turbine generator, electronic equipment and a medium, and aims to solve the problems of slow system recovery, voltage overshoot and current out-of-limit in the current low-voltage-crossing control technology. The method comprises the following steps: acquiring running state data of a wind turbine generator at a grid-connected point in a low-voltage period in real time, and calculating a system short-circuit ratio according to the running state data; considering a power adjustment coefficient, and constructing a current feedback controller based on the operation state data; introducing an adaptive weighting strategy of a system short-circuit ratio, and combining a power adjustment coefficient to construct a multi-objective optimization function; the multi-objective optimization function is subjected to parameter optimization solution combined with system short-circuit ratio self-adaptive correction, and an optimized power adjustment coefficient is obtained; and substituting the optimized power adjustment coefficient into a current feedback controller, solving a control current value, and performing current control on the wind turbine generator based on the control current value.

The invention belongs to the technical field of power system recovery control, and discloses a power coordination control method of a hybrid energy storage auxiliary black-start system and a related device.According to the method, the total active power requirement of the black-start system is obtained and decomposed into three time scale components of fundamental waves, intermediate frequencies and high frequencies; the power is dynamically distributed to the lithium battery and the super capacitor, the distributed power is corrected based on the temperature, the operation time and the rated parameters, and finally the frequency change rate and the direct-current voltage change rate are calculated according to the actual power instruction and the system parameters so that the controller can output the control quantity. By adopting the method, the contradiction between the energy and the power density of a single power supply is overcome, the response speed and the continuous power supply capability are synergistically improved, the voltage frequency instability risk caused by load input is effectively inhibited, and the reliability and the high efficiency of black start are remarkably improved by perfecting hybrid energy storage coordination control.

The invention relates to the technical field of power system operation and control, in particular to a power system recovery capability evaluation method, device and equipment considering unconventional risks and a medium, and the method comprises the steps: determining parameters for calculating the occurrence probability of earthquake disasters of different earthquake magnitudes; calculating intensity distribution by using an earthquake intensity diffusion model; calculating transmission tower and transmission line fault probabilities to obtain a fault line set; according to the operation power flow and the maximum allowable power flow, the cascading failure situation is divided into high risk and low risk; aiming at the two conditions, respectively enumerating a first-order fault state set and a second-order fault state set to obtain a system recovery capability initial value; the value serves as input, a convergence threshold value is set, a ULBI-IISE algorithm is adopted for iterative calculation, when the difference value of the upper cut set and the lower complementary set is smaller than the threshold value, the recovery capacity and the interval are output, and the method reduces high-order fault complete enumeration and the calculation amount while guaranteeing the precision, and is suitable for rapid evaluation of emergency scenes such as earthquakes.

The invention discloses a server hardware link diagnosis method and a server hardware link diagnosis system, relates to the technical field of computer system fault diagnosis, and discloses the server hardware link diagnosis method and the server hardware link diagnosis system. Through the steps of obtaining a diagnosis rule configuration file, collecting software and hardware state data, carrying out matching analysis to generate a diagnosis path, executing diagnosis processing, carrying out correlation analysis, generating a fault report and the like, the problems of software and hardware diagnosis splitting and path stiffness in the prior art are solved, and collaborative diagnosis and dynamic path generation of software and hardware faults are realized. And the fault positioning accuracy and the system recovery timeliness are improved.

This disclosure describes techniques for a system to share an IP address between computing resources (e.g., between a host server and its management controller), such that a server system may be recovered in the event of a system failure. For example, the host server may send a message to its management controller, such as a baseboard management controller, indicating that the IP address provided to the server system is in use, where the message may be sent at particular time intervals and / or within a threshold period of time. When a failure occurs with respect to the server system, the host server may be unable to send the message at the particular time interval and / or within the threshold period of time. Accordingly, the management controller may be configured to receive, or otherwise recover, the IP address such that the entire server system is accessible and recoverable.

The invention relates to the technical field of vehicle-mounted data processing, in particular to a safety method for instrument alarm icon detection, which comprises the following steps: after a black screen signal is received, an instrument application program receives a fault signal and performs logic judgment on the fault signal to obtain an alarm icon state of the fault signal; the instrument application program sends an alarm icon state of the fault signal to a UI thread and an SOC system adaptation layer; the SOC system adaptation layer forwards the alarm icon state of the fault signal to an SOC MCU, and the SOC MCU forwards the alarm icon state of the fault signal to a screen MCU; the screen MCU receives the alarm icon state of the fault signal and performs state detection so as to determine a mapping decision according to a detection result; and the screen MCU continuously monitors and updates the alarm state, and then resets the monitoring state after the system is recovered. According to the invention, the fault signal processing efficiency is effectively improved.

Techniques for file system recovery involve: running a recovery task for a file system on a first node, and synchronizing task data associated with the recovery task in a memory of the first node to a memory of a second node during the running of the recovery task. Data of the file system is stored in a storage device that is accessible via the first or second node. Such techniques further involve: in response to the recovery task panicking on the first node, resuming the running of the recovery task on the first node by using the task data that has been synchronized to the memory of the second node. Accordingly, the recovery task for the file system can continue even if some problems are encountered without re-running from the beginning.

The invention discloses a two-dimensional layering method for realizing intelligent operation and maintenance of a cloud computing environment, and the method comprises the steps: building an automatic operation and maintenance frame, and dividing the frame into two dimensions, namely a transverse dimension and a longitudinal dimension. According to the two-dimensional layering method for realizing intelligent operation and maintenance of the cloud computing environment, automatic scripts are compiled, repair operation is automatically executed according to specific warning conditions and events, such as service restarting, resource allocation adjustment and construction of a system with a self-healing capability, and automatic self-repair is performed according to a defined strategy when a fault is monitored, so that the two-dimensional layering method has remarkable advantages, and the practicability is high. The system can quickly respond, immediately start repair at the moment of a fault, shorten the system recovery time, reduce the influence of business interruption, quickly restart the fault service, improve the efficiency, save the manual troubleshooting and processing time and enable operation and maintenance personnel to concentrate on more important tasks.

The present disclosure belongs to the technical field of power system restoration, and particularly relates to an orderly black start method and system of a new energy power generation unit, comprising: acquiring system parameters of the new energy power generation unit; constructing a black start system model of the new energy power generation unit based on the acquired system parameters; evaluating the black start capability of the constructed black start system model to obtain a black start utility output of the new energy power generation unit; and optimizing the start order of the new energy power generation unit according to the acquired system parameters of the new energy power generation unit and the obtained black start utility output, combining an orderly participation algorithm to complete the orderly black start of the new energy power generation unit.

The invention discloses a power grid stability risk boundary generation method based on a large model. The power grid stability risk boundary generation method can dynamically simulate the recovery process of a power grid under load fluctuation or fault disturbance. By introducing transient stability analysis, the recovery time of the power grid after load fluctuation or disturbance can be accurately calculated, and the time boundary of system recovery is provided. When a fault or load fluctuation occurs, the power grid can rapidly recover stable operation, and a long-time unstable state is avoided. In addition, the maximum stable load, the minimum safe load and the overload threshold value are calculated. According to the method, the recovery capability and the stability risk boundary of the power grid can be rapidly calculated, and accurate real-time data support is provided for power grid dispatching and optimization. Compared with the traditional transient stability analysis, the calculation method provided by the invention has lower calculation cost, can update the stability risk boundary of the power grid in real time, and remarkably improves the dispatching and operation efficiency of the power grid.

The application discloses a kind of high availability methods of double-copy database based on arbitration, comprising: when activated arbitration module is determined that one virtual data node fails by listening to the heartbeat of two virtual data nodes in the double-copy Raft group, another surviving virtual data node is authorized as assigned leader Assigned_Leader, and the Assigned_Leader is independently provided with service in single-copy mode;The virtual data node that fails initiates election according to data volume as the elected standard after recovery online, so that the Assigned_Leader with more data is selected as the leader Leader, and the virtual data node Vnode2 that recovers online is selected as the follower Follower, then the Leader synchronizes the data during failure to the Follower, so that the data of both is completely consistent, so that the system recovers normal double-copy Raft mode.

The invention relates to the technical field of water conservancy project data analysis and intelligent decision making, in particular to a water conservancy project data analysis and processing system and method, and the method comprises the steps: obtaining multi-source heterogeneous data of a water conservancy system; constructing a multi-dimensional spatio-temporal data cube; based on the multi-dimensional spatio-temporal data cube, a toughness state feature vector is constructed, and the toughness state feature vector comprises a parameter used for representing supply-demand balance degree, a parameter used for representing engineering facility robustness and a parameter used for representing system recovery agility; calculating a system toughness entropy index; calculating an entropy change coefficient; based on the system toughness entropy index, identifying the vulnerability of the key path; and combining the entropy change coefficient with the critical path vulnerability to generate an optimal decision suggestion. According to the method, the problem that the influence of local decision on the global situation is difficult to quantify is solved, and the ability of coping with extreme events and complex challenges is systematically improved.

This invention relates to the field of power distribution system resilience enhancement technology, specifically a method for enhancing the resilience of a mobile hydrogen energy storage power distribution system. This method includes data acquisition and parameter initialization; constructing physical constraints for the power-transportation coupled system based on a multi-microgrid reconfiguration strategy; expanding the original typhoon scenario using an enhancement strategy to generate an expanded sample set including wind and solar power output prediction errors; constructing a fuzzy uncertainty set covering multi-source uncertainties; establishing a sub-Bruker optimal scheduling model with the objective of minimizing the overall system operating cost; and performing dual transformation and linearization on the sub-Bruker optimal scheduling model to obtain the trajectory of the mobile hydrogen energy storage vehicle, charging and discharging commands, and the action sequences of distribution network segment switches and tie switches. This invention effectively solves the problems of high difficulty in multi-grid resource coordination and difficulty in accurately obtaining data distribution characteristics under extreme disasters, significantly improving the economic efficiency of post-disaster system recovery and achieving an effective balance between robustness and economy.

Recovery of a target database system, comprising forming the target database system 500 and receiving multiple batches of database transactions 502. The following are performed repeatedly: generating

The invention relates to the technical field of power system stability control, and provides a new energy black-start partition optimization method considering unconventional risks, which comprises the following steps: simulating unconventional risks possibly encountered by a power system by adopting Monte Carlo sampling; extracting the output characteristics of wind power under the unconventional risk by adopting variational mode decomposition, and performing output prediction in combination with a long-short-term memory neural network; a power system recovery partition is divided based on an LPA algorithm, and the LPA algorithm is improved by considering a partition size balance principle, so that the partition area is more balanced, and the tag oscillation effect is reduced. According to the method, the black-start partition optimization model fusing new energy output uncertainty modeling and unconventional risk scene generation is designed, and the partition scheme is cooperatively solved by adopting the improved label propagation algorithm, so that the robustness and the recovery efficiency of the black-start partition are effectively improved; and rapid and stable power supply of a power system under complex disturbance can be realized.

A cluster storage system including servers containing storage processing units (SPUs) can create synchronized snapshot sets for the volumes that the SPUs maintain and can report the snapshot sets to a cloud-based service. Each snapshot in a set reflects the state a corresponding volume had at a rollback point corresponding to the set. A user of the storage system contacts the cloud-based service about recovery of the storage system, and the cloud-based service may present the user with a list of rollback points corresponding to the synchronized snapshot sets. The user may select to recover the storage system to any of the rollback points, and the SPUs promote the selected snapshots to replace the volumes for storage services.

The invention discloses an automatic fault elimination processing method, device and equipment based on terminal equipment, and relates to the technical field of the terminal equipment, and the method comprises the steps: detecting each started application through a preset fault detection program; when it is detected that the number of times of crash exception of the application exceeds a preset threshold value within preset time, it is judged that the system is abnormal, and the system is controlled to enter a safety mode, the control system automatically disconnects network connection and closes preset system services and processes, and only basic system functions are reserved; displaying prompt information of a security mode, and providing operation options of repairing a homepage, restoring factory settings and contacting customer service; and receiving a user operation instruction, selecting to uninstall the abnormal application and / or selecting to restore factory settings, and completing automatic fault elimination. According to the method, the problem that the system cannot be normally used due to continuous abnormality of the application of the large-screen television system is solved, and a user can recover the system to an available state through simple operation self-service troubleshooting when encountering such faults.

To provide an intervention device capable of estimating which factors governing the state of the system should be intervened in order to return the system to then original stable state just before the system transitions from the stable state to a critical state.SOLUTION: An intervention device 1 for suppressing fluctuations in networks where nodes with state quantities are connected includes: a state sample acquiring unit 11 that acquires multiple samples of state; an estimation unit 12; an intervention unit 13; and a control unit 14. The estimation unit 12 selects eigenvectors related to the eigenvalues of the covariance matrix of the acquired multiple samples as an estimate of the dominant right eigenvector. The control unit 14 is configured to control the intervention unit 13 so as to intervene to suppress the state quantity corresponding to the eigenvector component related to the selected eigenvalue on the network.SELECTED DRAWING: Figure 5

This application provides a method and apparatus for determining a system startup mode. The method for determining the system startup mode includes: storing first data required during system recovery into memory; storing guidance information for retrieving the first data into a first memory, which is not in memory; in response to system startup, obtaining second data based on the guidance information; if the second data meets a preset condition, selecting to restart the system instead of restoring the system; wherein, meeting the preset condition indicates that the second data does not include the first data.

The invention relates to an equipment fault analysis method and device, computer equipment and a readable storage medium. The method comprises the following steps: constructing a structural modal map and a semantic modal map according to equipment identifiers, equipment icons and a physical connection relationship among equipment, obtaining equipment identifiers and fault phenomena of fault equipment, generating a fault propagation chain containing fault equipment nodes based on the equipment identifiers, the structural modal map and the semantic modal map of the fault equipment, and transmitting the fault propagation chain to the fault equipment. Determining a device priority processing sequence of each device node in the fault propagation chain, determining a fault reason from a historical case library based on the device identifier of the fault device and the fault phenomenon, and generating a fault processing suggestion of each device node in the fault propagation chain according to the device priority processing sequence and the fault reason; the fault positioning efficiency can be obviously improved, the maintenance resource scheduling is optimized, and the power system recovery time is shortened.

The application relates to the computer technical field, in particular to a computer fault alarm system and method, which comprises a behavior mode analysis module, a performance fluctuation detection module, an event correlation analysis module, a fault early warning module and a resource adjustment response module. In the application, accurate behavior deviation indexes are provided by comparing high-frequency operation types and historical fault data, the indexes are used for optimizing a performance fluctuation monitoring process, especially when system performance anomalies are isolated and identified, the system fault detection capability is improved, the reaction speed and the early warning accuracy of early warning are enhanced by comparing a system load fluctuation with a conventional load change trend, the data are comprehensively utilized, the event correlation analysis is more accurate, the event propagation path and the correlation degree can be effectively mapped, the fault early warning timeliness and accuracy are improved, and the computer system recovery capability and the fault tolerance are enhanced through targeted resource adjustment.

The application discloses a kind of high-voltage substation intelligent monitoring and protection method and system based on cloud edge coordination architecture, and relates to power system control technical field, which comprises: S100: data acquisition;S200: preliminary detection of fault;S300: fault type identification;S400: protection decision;S500: cloud coordination;S600: system recovery.Adopt data hierarchical processing mechanism, guarantee the real-time of key protection function, simultaneously utilize cloud computing capacity to realize advanced analysis.Compared with traditional SCADA system, the cost of the application is reduced by more than 60%, deployment is more flexible, scalability is stronger, and supports fault prediction and preventive maintenance, significantly improves the safety and reliability of high-voltage substation.