336 results about "Repair time" patented technology

The invention relates to an intelligent maintenance decision method and system based on a knowledge graph, and relates to the technical field of intelligent operation and maintenance and decision support and information, and the method comprises the steps: obtaining the operation state data and historical maintenance data of industrial equipment; constructing an industrial knowledge graph and generating an incidence relation model; an optimal maintenance path is obtained based on the analysis of the relationship between the fault type and the maintenance path; optimizing a maintenance task allocation scheme through the optimal maintenance path, the incidence relation model and the maintenance resource constraint condition; carrying out maintenance time window dynamic adjustment analysis to obtain an optimal maintenance strategy; and finally, performing multi-objective optimization iterative analysis to obtain a final maintenance decision. According to the scheme, various factors can be comprehensively considered, and the scientificity and the accuracy of maintenance decision making of the industrial equipment are improved.

The invention discloses a semi-autogenous mill fault early warning and maintenance method based on digital twinning, which realizes optimization of a maintenance process through accurate maintenance fault early warning of related equipment of semi-autogenous mill processing. The method comprises the following steps: step 1, collecting historical total operation time data and historical maintenance record data of the semi-autogenous mill to determine equipment life cycle parameters; the historical total operation time data comprises total operation time, and the historical maintenance record data comprises fault frequency and total repair time; 2, obtaining a digital space according to the normal operation state data and the abnormal operation state data of the semi-autogenous mill, and constructing a digital twinborn model of the semi-autogenous mill based on a digital twinborn technology and the digital space; 3, inputting the equipment life cycle parameters obtained in real time into the digital twin model for training to obtain a real-time dynamic value, and generating a maintenance strategy and a maintenance early warning signal; and 4, evaluating the health state of the equipment according to the maintenance strategy to obtain a maintenance fault coefficient, and generating a fault early warning signal.

The invention relates to the technical field of traffic infrastructure maintenance, and particularly discloses a method for evaluating the anti-collision toughness of a rusted steel bar bridge structure after ship collision, and the method comprises the following steps: firstly, building a rusted bridge pier finite element model based on a rusted steel bar concrete theoretical degradation model; simulating ship collision by adopting an equivalent static method, and determining dynamic damage factors of the ship; structural nonlinear static analysis and nonlinear dynamic analysis are conducted by considering sudden external force to obtain a bridge function loss function, and then a bridge function is calculated; constructing a response surface agent model to perform dynamic response prediction; determining a bridge structure damage state judgment criterion; the vulnerability of the rusted bridge is calculated through Monte Carlo simulation; and according to the bridge function loss function, combining the repair time and the recovery function to calculate a structure anti-collision toughness index. The method provided by the invention fills up the blank of ship collision resistance toughness evaluation of the coastal rusted bridge pier, provides a scientific basis for bridge safety evaluation and maintenance decision, and is of great significance for guaranteeing safe operation of the bridge.

The invention relates to the technical field of integrated circuit repair, in particular to a storage repair system based on a polymorphic BISR chain, the system divides storage units in a chip into a plurality of repair modules, and a plurality of off-chip registers contained in each repair module form a plurality of first off-chip register chains; when the memory unit in the chip is repaired, the memory unit can be repaired at the same time through the plurality of first off-chip register chains, so that the repair duration of the memory unit of the chip is determined according to the maximum chain length of each first off-chip register chain; compared with the prior art that the repair duration of the chip storage unit is determined according to the sum of the chain lengths of all the off-chip registers, the storage repair time is greatly shortened, the storage repair efficiency is further improved, in the storage repair process, the storage unit can adopt a parallel repair mode or a serial repair mode, and the repair efficiency is improved. Storage repair can be compatible with memory cells of different repair types.

The invention discloses a digital automobile maintenance and repair market intelligent operation system, particularly relates to the field of automobile maintenance and repair, and comprises a database, a vehicle information acquisition module, a data preprocessing module, a repair auxiliary diagnosis module, a work order intelligent scheduling module and a user information terminal. The maintenance auxiliary diagnosis module constructs a fault diagnosis model based on a vehicle data processing text and a historical maintenance case library, the accuracy and efficiency of fault diagnosis are improved, a maintenance work order is generated according to a diagnosis result and an association rule table, accurate selection of accessories needed by maintenance is ensured, and the maintenance time and cost are reduced; according to the intelligent work order scheduling module, the objective function and the genetic algorithm are constructed, related variables are comprehensively considered, reasonable distribution of maintenance work orders is achieved, resource utilization of maintenance enterprises is effectively balanced, work order waiting time and total maintenance time are shortened, and overall operation efficiency is improved.

The invention relates to the technical field of intelligent operation and maintenance, in particular to a fault insight and self-healing method and system based on chain control. According to the chain control-based fault insight and self-healing method, indexes, logs and tracking data of a micro-service environment are dynamically collected and fused; the method comprises the following steps: dynamically constructing and visualizing a service dependent topology, realizing dynamic topology construction and intelligent visual rendering, performing intelligent root cause analysis and predictive diagnosis based on multi-dimensional data, realizing self-adaptive early warning, generating an intelligent decision, performing closed-loop learning optimization based on an execution result, and realizing automatic fault repair and continuous optimization. According to the fault insight and self-healing method and system based on chain control, a predictive early warning mechanism is established, automatic fault self-healing is realized, and through intelligent and automatic means, manual intervention is reduced, the operation and maintenance cost is reduced, the average repair time is shortened, the service continuity is guaranteed, and the system availability is improved.

The invention discloses an intelligent property management system based on artificial intelligence, and relates to the technical field of intelligent property, and the system comprises a data management center which is in communication connection with a data collection and transmission module, a fault recognition and diagnosis module, a knowledge graph auxiliary decision module, an intelligent repair customer service module and an equipment maintenance management module. And the data acquisition and transmission module is used for acquiring and preprocessing operation data of the facility equipment based on various sensors deployed on the property facility equipment. According to the invention, real-time analysis is carried out on facility equipment operation data through an artificial intelligence algorithm, potential faults can be identified in advance and early warning can be given out, fault expansion is avoided, fault causes are rapidly positioned, clear guidance is provided for maintenance personnel, maintenance time is shortened, a knowledge graph is combined with a fault identification result, a solution strategy and decision support are provided, and maintenance efficiency is improved. Maintenance personnel are helped to quickly make a reasonable maintenance plan, resource allocation is optimized, and the fault processing efficiency is remarkably improved.

The invention discloses a composite insulating arm surface repairing material and a repairing method, and the repairing material comprises the following raw material components in parts by weight: 100 parts of matrix resin, 0.8-4 parts of a curing agent, 0.2-1.2 parts of an accelerant, 5-20 parts of color paste, 10-25 parts of inorganic particles, and 10-25 parts of inorganic fibers. The repairing material is simple in preparation method and convenient to use, according to the repairing method, the repairing material is used for replacing gel coat spraying repairing, the operation difficulty is low, the repairing duration is shortened, the repairing efficiency is improved, and all technical indexes of the repaired insulating arm component can meet the use requirements.

The invention discloses a product production process scheduling method and system based on intelligent manufacturing, and belongs to the technical field of intelligent manufacturing. According to the method, rapid local rescheduling is realized through fault influence domain identification, a three-level response strategy and real-time equipment health assessment. When an equipment fault signal is detected, a to-be-executed task on the fault equipment is identified, a subsequent task chain is traced through the technological process dependency relationship, the boundary of a fault influence domain is determined, and the influence domain relates to 10%-20% of tasks in the whole production plan. And selecting a corresponding response strategy according to the predicted repair time, adopting a task delay strategy when the predicted repair time is less than 30 minutes, performing local redistribution on tasks in the influence domain when the predicted repair time is less than 30 minutes to 2 hours, and expanding the influence domain to the whole process for comprehensive optimization when the predicted repair time is more than 2 hours. Meanwhile, monitoring data such as equipment vibration, temperature, current and rotating speed are collected to calculate a health degree score, and 5%-10% of productivity redundancy is reserved for high-risk equipment.

The present invention relates to the technical field of avionics equipment, and disclosed is a cross-domain maintenance decision-making method for coordinated optimization of maintenance service outlets, activities, and resources. The method comprises the steps of: on the basis of a fault phenomenon, acquiring a set of a variety of maintenance activities; determining whether resources required for a faulty product are missing at a current service outlet, and if the resources are missing, separately computing a resource scheduling time and cost required for each maintenance activity for which resources are missing; computing a fault repair time, repair costs, and repair probability of a certain maintenance activity; and determining a goal of a maintenance decision, and outputting an optimal maintenance scheme. The present invention can assist technicians in making maintenance decisions during maintenance of electronic products, reduce the waste of time and resources caused by the inconsistencies and uncertainties of maintenance activities, guide maintenance activities of remote operation and maintenance, reduce maintenance time, and reduce operation and maintenance costs.

The embodiment of the invention provides a safety injection system and method, and relates to the field of reactor safety systems. The problem that the water injection flow of a safety injection system is not matched with the flow needed in the reactor water loss accident stage is solved. The safety injection device comprises a pressure-bearing container and a damping device, wherein a safety injection outlet pipe is arranged at the bottom of the pressure-bearing container; the damping device is arranged in the pressure-bearing container, the damping device is provided with a water inlet and a water outlet, and safety injection water in the pressure-bearing container flows through the damping device from the water inlet and then flows to the safety injection outlet pipe from the water outlet. The drainage flow of the safety injection water in the pressure-bearing container is gradually reduced along with the process of the water loss accident, and compared with a pressure-bearing container without the damping, the flow in the initial stage is lower, so that the water quantity of the safety injection bypass can be reduced; the flow in the middle stage can quickly realize refilling of water in the lower cavity of the reactor core and resubmerging of the reactor core; the flow submerged in the reactor core is maintained to be lower in the later period of the accident, the safety injection time is fully prolonged, and safety injection water is effectively utilized.

The invention relates to the technical field of composite material repair, in particular to a short carbon fiber technology-based composite material rapid repair method, which comprises the following steps of short carbon fiber pretreatment; preparing a resin matrix; preparing spraying slurry; cleaning the damaged area by laser; scanning the unmanned aerial vehicle; layering and synchronous curing; evaluating the quality of the coating; a chopped fiber spraying technology is applied to the aspect of composite material damage repair, repair time is shortened, cost is reduced, interface bonding strength and fiber orientation are optimized, and the problem that the mechanical property recovery rate of the repaired material is low due to the fact that interlayer stripping or fiber orientation mismatching is prone to occurring in a repair area is solved. And the method can be used for rapidly detecting the thickness of the bubble defect, is suitable for efficient, accurate and light-weight repair of the damage of the CFRP, and is particularly suitable for on-site rapid maintenance scenes.

The invention discloses a vulnerability processing method and device, equipment and a medium in the technical field of computers. Feature coding is carried out based on server operation information and sensor data; the target features obtained through coding and the matched vulnerability features are constructed into a vulnerability chain, and the emergency degree and the repair time period of the vulnerability chain are determined; and finally, generating a vulnerability repair strategy based on the target feature, the emergency degree and the repair time period by using the repair decision model, and automatically executing the vulnerability repair strategy. Therefore, the full-automatic process of data acquisition, vulnerability detection and vulnerability repair is realized, the vulnerability repair efficiency can be improved, and the influence on services is reduced.

The invention provides a tough road network repair time sequence multi-objective optimization method giving consideration to efficiency and safety. The method comprises the steps that S1, road network system travel data and road network system accident data in the road network repair period are acquired, and a road network system efficiency evaluation index and a road network system safety evaluation index are established according to the road network system travel data and the road network system accident data; s2, respectively obtaining a first road network toughness index and a second road network toughness index according to dynamic changes of the road network system efficiency evaluation index and the road network system safety evaluation index, and constructing a toughness-oriented road network repair time sequence multi-objective optimization model based on the first road network toughness index and the second road network toughness index; s3, solving the toughness-oriented road network repair time sequence multi-objective optimization model by adopting a hybrid variable neighborhood non-dominated solution sorting genetic algorithm; and S4, compiling a hybrid variable neighborhood non-dominated solution sorting genetic algorithm through MATLAB, and obtaining the solution of the toughness-oriented road network repair time sequence multi-objective optimization model to obtain a Pareto optimal solution as an optimal road network repair time sequence multi-objective optimization scheme. The method has the beneficial effects that the influence of post-disaster road network restoration efficiency and restoration activities on road network traffic safety can be considered, and rapid restoration of the road network after a rainstorm event is ensured.

The invention discloses a war damaged equipment maintenance scheduling method based on digital twinning and robustness optimization, and aims to solve the problems that a traditional optimization model is insufficient in adaptability to a battlefield dynamic scene and is incomplete in consideration of risk factors. The method is realized through the following steps: firstly, acquiring a battle damage equipment state, a maintenance unit state and environmental factor data in real time by using a digital twin technology, and constructing a task importance degree, battle damage equipment maintenance time and maintenance unit maneuvering time evaluation model; secondly, a multi-objective optimization function with the maximum comprehensive importance degree and the minimum maximum maintenance time as objectives is established, an uncertainty set of team confrontation intensity, capacity matching coefficients, threat coefficients and fatigue coefficients is constructed, and robustness buffer capacity is introduced for robustness optimization modeling; example verification shows that the method can effectively fuse dynamic data, quantitatively process multiple risks, improve the anti-interference capability and battlefield adaptability of a scheduling scheme, and provide scientific decision support for wartime equipment maintenance support.

The invention discloses an automatic operation and maintenance system based on fusion of an AI agent and a configuration management database, and the system comprises a data collection module which is used for automatically collecting configuration information of IT infrastructures through a multi-mode collection technology; the configuration management database is used for converting the configuration information into configuration items and dependencies to construct a knowledge graph; the AI agent comprises a log analysis unit used for carrying out structured processing on the unstructured log data; the anomaly detection unit is used for carrying out anomaly detection on the structured log data and time sequence index data by adopting an unsupervised machine learning algorithm; the root cause positioning unit is used for performing topological relation reasoning on the detected abnormal events based on a knowledge graph, and determining a fault type and a root cause configuration item causing the fault; and the automatic executor is used for calling an automatic operation and maintenance tool to execute repair operation according to the fault type and the root cause configuration item. The operation and maintenance efficiency can be improved, and the fault repair time can be shortened.

According to the mask defect in-situ repairing method, the femtosecond laser is adopted for defect repairing, and all the advantages of the femtosecond laser are absorbed. Femtosecond laser is ultrashort pulse laser with'femtosecond 'as a time unit, the pulse duration time of the femtosecond laser is extremely short (femtosecond magnitude), and the peak power of the femtosecond laser is extremely high (the maximum can reach pat watt). Therefore, according to the repairing method, the repairing precision can be reduced to 15 nm, the heat affected zone is smaller than 1 micron, the repairing time can be shortened to 100 ms for the defect of 100 nm, the roughness of the repaired surface is smaller than or equal to 0.5 nm, meanwhile, the good effects of high repairing precision, low heat affected zone, high repairing speed, low equipment cost and simple operation are achieved, and the rejection rate of the mask is reduced. The method is especially suitable for repairing advanced process masks, such as EUV and ArF, and display panel masks, such as OLED and FMM, and MEMS device masks.

The utility model discloses a repair product clamp which comprises a supporting table and first positioning blocks, an iron plate is fixed to the top of the supporting table, the number of the first positioning blocks is four, and the four first positioning blocks are arranged at the positions, close to the four corners, of the top of the iron plate respectively. A plurality of supporting columns are further fixed to the position, close to the middle, of the top of the iron plate and located among the four first positioning blocks. An inductive head is further arranged at the top of the iron plate; through the designed structures of the supporting table, the iron plate, the first positioning blocks, the first magnets and the like, the distance between the four first positioning blocks can be adjusted according to different sizes of products, the device can be suitable for the products of different sizes, the good positioning and stabilizing effects on the repaired products are achieved, and the repairing efficiency is improved. And meanwhile, a movable inductive head is designed in the repair area to carry out time control, reminding is carried out after the time is up, a worker is reminded of the repair time, and the repair efficiency and the yield are ensured.

In a computer-implemented method and associated tangible non-transitory computer-readable medium, an image of a damaged vehicle may be analyzed to generate a repair estimate. A dataset populated with digital images of damaged vehicles and associated claim data may be used to train a deep learning neural network to learn damaged vehicle image characteristics that are predictive of claim data characteristics, and a predictive similarity model may be generated. Using the predictive similarity model, one or more similarity scores may be generated for a digital image of a newly damaged vehicle, indicating its similarity to one or more digital images of damaged vehicles with known damage level, repair time, and / or repair cost. A repair estimate may be generated for the newly damaged vehicle based on the claim data associated with images that are most similar to the image of the newly damaged vehicle.

The present invention discloses a method and system for intelligent diagnosis and maintenance guidance of household appliance faults, which belongs to the technical field of electrical appliance fault diagnosis and maintenance, and can improve the maintenance efficiency of household appliances; the method comprises the following steps: receiving a fault code sent by a household appliance; sending the fault code to a maintenance end, so that the maintenance end determines the fault type according to the fault code, and when it is determined that the first user has the ability to solve the fault type by himself, sending a maintenance plan to a preset first user's terminal device; when it is determined that the first user does not have the ability to solve the fault type by himself, automatically assigning a maintenance personnel for on-site maintenance, and sending corresponding prompt information to the preset first user's terminal device, and sending the fault type and fault code to the terminal device of the assigned maintenance personnel; wherein the prompt information at least includes the maintenance personnel's estimated on-site maintenance time and contact information.

The invention provides an intelligent fault self-healing method based on a multi-dimensional index, and relates to the technical field of fault detection and repair, and the method comprises the steps: collecting multi-source data, carrying out the feature engineering processing, carrying out the fault classification through employing an XGBoost classifier, and selecting a combined repair strategy according to the fault type in combination with the controller type and service level features. And the repair operation is executed after the service dependency graph is optimized. The fault diagnosis accuracy can be improved, the fault repair time is shortened, the manual intervention requirement is reduced, and the cloud platform service reliability is improved.

The invention provides a wind power blade repairing robot system which comprises a bottom plate, a mechanical arm module, a putty smearing module, a spraying module, a polishing and cleaning module and a consumable library, the mechanical arm module comprises an RGB-D camera, an adapter ring, a robot tail end quick change disc and a mechanical arm, and the mechanical arm is arranged on the bottom plate. The adapter ring is arranged at the tail end of the mechanical arm, the RGB-D camera and the robot tail end quick-change disc are both installed on the adapter ring, and the putty smearing module, the spraying module and the polishing and cleaning module can be connected with the robot tail end quick-change disc through the tail end quick-change disc. A'coating and scraping 'putty integrated polishing and cleaning module and a spraying module are designed, repairing work of putty coating and putty scraping is carried out at the same time, the size and the weight are saved, meanwhile, the repairing efficiency is improved, according to the repairing method, no manual operation in the whole process can be achieved, real full-automatic blade repairing is achieved, unmanned replacement is achieved, and the repairing efficiency is improved. And the repairing time is obviously reduced.

The invention discloses a fault safety self-checking system based on computer hardware, and relates to the technical field of hardware fault detection, and the system comprises a hardware monitoring module which collects the working state data of target computer hardware in real time; the fault diagnosis module is used for performing real-time analysis according to the data acquired by the hardware monitoring module and detecting potential faults of the hardware component; the fault prediction module is used for predicting potential faults of the target computer hardware based on the historical fault data, the working state data and a machine learning algorithm and carrying out early warning in advance; the automatic repairing module is used for automatically executing preset repairing operation when hardware faults and potential faults are detected; and the user notification module is used for sending fault alarm information, repair progress and result to a user. According to the method, highly-integrated hardware monitoring, fault diagnosis, prediction, automatic repair and notification functions are provided, the reliability, stability and safety of computer hardware are remarkably improved, and loss and repair time when a system fault occurs are reduced.

The invention relates to an intelligent control method and system for mold maintenance precision in the technical field of information, and the method comprises the steps: carrying out the classification of deviation data through employing a clustering algorithm according to a deviation calculation result, recognizing a region with large deviation, and determining the specific position of an error source; the mold state judgment result is combined with material attributes and machining process data, and the remaining service life of the mold is calculated through a remaining service life prediction model; generating a maintenance strategy and a time plan by adopting an optimization algorithm according to a residual life prediction result, and determining optimal maintenance time and a resource allocation scheme; a maintenance strategy and a time plan are input into a mold full-life-cycle management platform, and seamless data integration with a production control system and a quality tracing system is achieved; and the mold precision state is monitored in real time through the full-life-cycle management platform, and if it is monitored that the precision deviation exceeds a preset threshold value, the maintenance process is automatically triggered.

A method and system may use photo deformation techniques for vehicle repair analysis to determine a repair time for repairing a damaged vehicle part. A user's client device may generate a three-dimensional (3D) image or model of a damaged vehicle part by capturing several two-dimensional images of the damaged vehicle part. One or several characteristics of the damaged vehicle part may be extracted from the 3D model and the characteristics may be compared to characteristics for previously damaged vehicle part, where the actual repair times were measured. A repair time for the damaged vehicle part may be determined based on the comparison and displayed on the client device.

The invention relates to a quick repair method for an assembled composite material. The quick repair method comprises the following steps: S1, manufacturing a composite material laminated plate; s2, cutting the composite material laminated plate; s3, holes are formed in the hexagonal composite material patch units; s4, obtaining a large number of hexagonal composite material patch units; s5, adhering the alkali-free glass fiber cloth; s6, holes are formed in the aluminum alloy plate; s7, the aluminum alloy plate is cut; s8, a large number of aluminum alloy connecting units are obtained; s9, repairing and patch assembling; s10, adjusting the appearance of the curved surface of the assembly structure; s11, the assembly structure is installed; through prefabrication and splicing of a large number of hexagonal composite material patch units and aluminum alloy connecting units, the repairing and manufacturing time of large composite materials is shortened, and the repairing speed is increased; by changing the using number of the hexagonal composite material patch units and the aluminum alloy connecting units, rapid repair of different damage areas can be effectively achieved; by changing the bending shape of the aluminum alloy connecting unit, the damage of the composite materials with different curvatures can be effectively and rapidly repaired.

The invention discloses a repair-oriented product information identifying and tracing system and method. The method comprises the following steps of: warehousing a product, and inputting repair information; reading the top cover information of the product, and judging the top cover information of the product; judging whether the image information is defective; identifying image information; performing secondary verification on the information; spraying a new bar code on the product; and a repairing process. The system comprises a reading and spraying module, a process operation end and a tracing and analyzing module. Compared with the prior art, the method has the advantages that mixed line repair conditions of product manufacturers, versions and batches can be considered, and identification, identification, tracking and tracing in the product repair process are realized. Maintenance personnel can quickly understand the fault condition of the product, the repair condition of the previous process and the like, so that a more reasonable repair scheme is formulated, the repair time is shortened, and the repair efficiency is improved. When batch quality problems occur to products, enterprises can quickly position the problem range, take effective measures for improvement and recall, and reduce the quality risk and loss.

The invention discloses a prediction type maintenance method and system for a nuclear power plant. The method comprises the following steps: configuring a parameter threshold for a first object, and setting an exception handling rule; the method comprises the following steps: collecting first object operation data, and performing first preprocessing; and predicting and classifying the health state of the first object according to a processing result, and generating a work order. The nuclear power plant prediction type maintenance method and system provided by the invention are helpful for predicting equipment faults, optimizing time and resources to reduce maintenance and operation costs, and improving the performance and reliability of equipment; equipment asset performance and normal operation time are optimized, and cost can be reduced; the early warning of potential faults is helpful for reducing faults, in-plan maintenance or out-of-plan shutdown. The visibility of the continuous state is improved, so that the reliability and durability of the equipment in the whole life cycle are improved; indexes such as average fault interval time and average repair time can be effectively improved, and the income and profitability of enterprises are improved.

The invention discloses a big data-based switch fault elimination method and system, and relates to the technical field of network operation and maintenance, and the method comprises the steps: distributing each network link state node through employing a self-adaptive controller, and collecting network state data; constructing a streaming processing engine, and setting a dynamic baseline alarm device to preliminarily classify the network state data; querying switch information corresponding to the network state data by adopting a controller code, and carrying out abnormal index analysis to obtain a fault data label; aI pipeline detection is deployed, and intelligent root cause analysis is performed on the fault data label, so that gradual optimization from alarm to root cause positioning is realized, and the average repair time is greatly shortened.

The invention discloses a digital intelligent operation and maintenance system and method for relay protection, and relates to the technical field of operation and maintenance management. If yes, a robot set capable of being operated and maintained is determined according to the fault type set; according to a preset important value of the relay protection device, the number of robots which are sent to the relay protection device for operation and maintenance in a robot set capable of performing operation and maintenance is determined; calculating the priority value that each robot in the robot set capable of operation and maintenance is dispatched to the relay protection device for operation and maintenance, and screening a corresponding number of robots from the robot set capable of operation and maintenance according to the sequence of the priority values from large to small for operation and maintenance; maintenance tasks can be effectively completed, delay of fault repair time is slowed down, influences on the stability of a power grid are reduced, it is ensured that large-scale power failure or equipment damage cannot be caused, and the reliability of the equipment and the overall operation efficiency are ensured.