243 results about "Fault handling" patented technology

The invention relates to the technical field of circuit detection, discloses a power transmission line thermochromic wire clamp heating early warning method and system, effectively solves the problem of data acquisition distortion in a strong electromagnetic environment, and improves the accuracy of state evaluation through multi-source data fusion. The dynamically adjusted early warning model reduces the risk of false alarm and missing alarm caused by equipment aging, the intelligent decision support module shortens the fault handling response time, the data closed-loop mechanism ensures the reliability of the system in the whole life cycle, and the reliability of the system in the whole life cycle is improved through multi-sensor cooperative monitoring and edge calculation processing. And the influence of environmental factors on data acquisition is reduced. The two-channel transmission architecture guarantees the data transmission integrity under different network conditions, the CRC verification mechanism effectively recognizes and corrects transmission errors, a high-quality data basis is provided for a subsequent early warning model, the abnormal data recollection mechanism avoids data missing caused by single collection failure, and continuous and stable operation of the monitoring system is ensured.

The invention relates to the technical field of power grids, in particular to a metering box remote monitoring method, system and device based on artificial intelligence and a medium. Acquiring electrical parameter data and environmental data of the metering box; performing time domain and frequency domain feature extraction on the data to obtain key features; inputting the processed data into a preset abnormal state detection model; identifying an abnormal state of the metering box based on a model output result; and when the abnormity is identified, alarm information is generated and sent to a monitoring terminal through a remote communication network. Multi-dimensional monitoring data are collected in real time through multiple sensors, feature extraction and anomaly detection are performed by applying an artificial intelligence technology, a model is continuously optimized in combination with an online learning mechanism, and comprehensive sensing of the running state of the metering box and accurate recognition of the abnormal state are achieved. Compared with a traditional monitoring system, the method improves the detection accuracy, reduces the false alarm rate and the missing report rate, improves the fault processing efficiency through the automatic generation of the maintenance suggestions, and provides a powerful guarantee for the operation of a power system.

The invention relates to the field of industrial equipment monitoring, and discloses a power plant steam-water system edge calculation monitoring terminal system, which comprises a data acquisition module used for performing real-time acquisition on temperature, pressure, flow and liquid level parameters of key parts such as a boiler, a steam turbine and a pipeline in a power plant steam-water system, an acquisition result is converted into a standard data format to be output; the edge calculation module is used for performing local processing on the data, including feature extraction, data modeling, anomaly recognition and operation state analysis, and the module establishes a state model based on historical data and outputs parameter optimization suggestions according to a set strategy; and the communication module is used for transmitting the processing result to a monitoring center and receiving an instruction issued by the monitoring center. Local modeling and recognition are carried out on collected data through the edge calculation module, delay caused by data return is avoided, an abnormal early warning mechanism of second-level response is achieved, and the fault handling capacity of the system is enhanced.

The invention discloses a data backup management system for communication, which belongs to the technical field of data management, and comprises an intelligent hierarchical backup module, a block chain security module, an AI resource scheduling module, a hybrid cloud backup module and an automatic fault processing module, the intelligent hierarchical backup module is used for dividing communication data into hot data, warm data and cold data according to the importance, use frequency and modification frequency of the data, and the block chain security module is used for generating a unique hash value for each backup data and recording the unique hash value on a block chain. The AI resource scheduling module is used for analyzing and learning historical backup data and operation records by using a deep learning algorithm, and the hybrid cloud backup module is used for combining a local data center and public cloud storage. And the automatic fault processing module is used for deploying the automatic fault detection module to monitor the running states of the backup server, the storage device and the network link in real time.

The invention discloses a power distribution network fault processing method, system and device based on a digital twinborn technology, and a medium. The method comprises the following steps: collecting real-time operation data of a power distribution network, constructing a digital twinborn model of the power distribution network, identifying a potential fault source through the digital twinborn model, and generating a candidate fault propagation path according to the potential fault source; calculating a propagation damping score for each candidate fault propagation path; comparing each propagation damping score with a propagation score threshold value corresponding to the current operation stage; and according to the deviation condition of the propagation damping score and the suppression result of the candidate fault propagation path in the actual fault response, a scoring factor is adjusted, and the suppression strategy of the candidate fault propagation path is adjusted. According to the power distribution network fault processing method based on the digital twinning technology, the digital twinning model comprising the equipment layer, the connection layer and the state layer is constructed, real-time mapping of the structure and the operation state of the power distribution network is achieved, and the accuracy of fault source positioning is improved.

The invention discloses an AI-based network log analysis processing method, which comprises the following steps of: firstly, collecting network equipment log information through a collection script supporting multiple protocol modes, and writing the collection script and deploying and starting after determining equipment and protocol types; thirdly, carrying out preliminary classification, data supplementation and formatting processing on the original logs; and then, sending the processed log data to an AI large model for semantic analysis, including deep understanding, basic classification, secondary analysis and providing of processing suggestions. An analysis result is stored in a data think tank for historical comparison, and an inconsistent result is manually confirmed and corrected; when the network equipment triggers a fault alarm, calling the data think tank to supplement alarm content; and meanwhile, equipment related data handbooks provided by manufacturers are uploaded regularly, the analysis accuracy of the AI model is corrected, verification and testing are carried out, it is ensured that the scheme can comprehensively and efficiently collect and process logs, accurately analyze faults and continuously optimize the model, and effective support is provided for network fault processing.

The invention relates to the field of data communication, and relates to a fault processing method and an MLAG system, and the method comprises the steps: when a master device detects a Peer-link fault, obtaining the state of an uplink port of the master device, and transmitting the state to an access device; when the slave equipment detects a Peer-link fault, the slave equipment obtains the state of an uplink port of the slave equipment and sends the state to the access equipment; and when the access equipment judges that the state of the uplink port of the master equipment is faulty and the state of the uplink port of the slave equipment is normal, the access equipment sends a configuration cancelling message to the slave equipment so as to indicate the slave equipment to cancel the operation of configuring the own aggregation group port to be in a faulty closed state according to the configuration cancelling message. And the slave device receives the flow of the access device through the own aggregation group port and sends the flow out through the uplink port of the slave device. According to the invention, the robustness of the MLAG system can be improved when the Peer-link fault occurs.

The invention belongs to the technical field of display terminal fault diagnosis, and particularly relates to a display terminal full life cycle fault intelligent diagnosis system, which receives fault phenomenon description of a display terminal, retrieves a signal input end control object set associated with a fault phenomenon, and performs targeted detection on each control object in the set. Generating an original detection data set, carrying out instantaneous abnormal point elimination, obtaining an effective fault feature set carrying a potential fault identifier, fusing the effective fault feature set with a historical fault contribution degree weight, obtaining the fault reason confidence of each control object, judging the association strength of a fault mode of each control object and an environment factor through a preset environment association rule, and determining the fault mode of each control object according to the association strength. And generating an environment sensitivity evaluation label, binding the environment sensitivity evaluation label with the fault cause confidence coefficient, and revealing a coupling mechanism of fault root causes and environment inducements to output a fault positioning diagnosis report, thereby avoiding insufficient fault positioning granularity caused by complete machine generalization detection, and providing a more comprehensive basis for fault disposal.

The embodiment of the invention discloses a CXL memory fault processing method, computing equipment and a computing system, relates to the field of computing, and at least can realize memory fault synchronization between the computing equipment so as to ensure stable operation of the computing equipment. The CXL memory fault processing method comprises the steps of determining second computing equipment from a computing equipment cluster under the condition that access of first computing equipment to a first memory space is abnormal; wherein the first computing device is any computing device in a computing device cluster; the second computing device is a computing device sharing a first memory space with the first computing device in the computing device cluster; the first memory space is a memory space in the CXL memory device; sending the first message to the second computing device; the first message is used for indicating that the first memory space access is abnormal.

The invention relates to the technical field of intelligent traffic equipment management, in particular to a signal equipment health state monitoring method and system, and the method comprises the steps: receiving operation, external field sensing and communication link data of signal equipment through a protocol conversion interface, converting the data into a unified format, and storing the data in a data medium; after abnormal value filtering and missing value completion, operation characteristic parameters are extracted, a layered health degree evaluation model is constructed, equipment-level, intersection-level and trunk-level health degrees are calculated in sequence, and early warning is triggered if the health degrees are lower than a preset threshold value; constructing a device-link-scene association map, positioning a fault type and a fault source in combination with a fault feature matching algorithm, and analyzing a fault influence range; and according to the fault influence range, the device priority and the operation and maintenance resource real-time state, generating an operation and maintenance work order and a resource scheduling suggestion, and pushing early warning information, a fault positioning result and a health degree report to an operation and maintenance terminal. Full-level health perception and operation and maintenance resource optimization can be realized, the fault handling period is shortened, and the traffic passing efficiency is guaranteed.

The invention relates to a navigation equipment fault anomaly detection method based on a multi-layer dynamic causal relationship network, and the method comprises the steps: collecting multi-source data from a navigation system, and constructing the multi-layer dynamic causal relationship network comprising a system macroscopic layer and an equipment layer; processing a real-time data stream of the navigation system by adopting a message queue, and extracting feature data used for real-time fault detection in the real-time data stream; analyzing the feature data by using a multi-layer dynamic causal relationship network, judging whether equipment abnormity exists or not, and if the judgment result is yes, further positioning the reason of the equipment abnormity by using the multi-layer dynamic causal relationship network; and if the equipment is abnormal, a fault alarm is given out. According to the invention, real-time automatic detection and positioning of equipment faults are realized, engineers can process the equipment faults conveniently, fault processing efficiency is improved, and navigation safety and stability are effectively guaranteed.

The invention provides a comprehensive service intelligent management method, which comprises the following steps: S1, acquiring a service demand submitted by a user, and analyzing and generating a resource configuration scheme through an AI algorithm; s2, the resource configuration scheme is automatically checked through an AI auditing engine, and manual auxiliary auditing is triggered; s3, automatically executing cross-system equipment configuration and verifying link performance according to the resource configuration scheme passing the audit; and S4, on the basis of the real-time monitoring data, utilizing an AI algorithm to predict equipment faults and schedule maintenance tasks. According to the method, through full-process AI enabling and cross-system collaborative management, the core pain points of low efficiency, fault processing lagging, non-standard auditing and high cost in traditional communication network management are effectively solved, and powerful support is provided for intelligent, efficient and low-cost operation of the communication network.

The invention discloses a server management system, a server management method and electronic equipment, and relates to the technical field of computers.In the method, on one hand, edge nodes are arranged in a plurality of different areas respectively, and each edge node is connected with a server in the area where the edge node is located through a first communication line; and connecting a cloud management platform through a second communication line. The edge node can perform autonomous management on the server in the area based on the management information issued by the cloud management platform. The server and the edge node are located in the same area, and the communication delay is short, so that when the server fails, the edge node can timely issue an instruction to perform fault processing, and the fault recovery duration of the server can be shortened. And on the other hand, the theoretical communication rate of the first communication line is higher than the theoretical communication rate of the second communication line, so that the data transmission rate between the server and the edge node can be improved, and the fault recovery duration of the server is further shortened.

The invention discloses an alarm system and method based on intelligent process monitoring and message queue detection, and relates to the technical field of intelligent monitoring alarm, and the system comprises a process state monitoring module which is used for regularly detecting the operation state of a key process; the message queue monitoring module is used for acquiring a message queue stacking condition in real time; the multi-stage alarm module is used for triggering alarm according to abnormal conditions and selecting different notification modes; the automatic recovery module is used for executing recovery operation after the exception occurs; the timed scheduling module is used for monitoring the real-time performance and regular execution of tasks; and the log and report module is used for recording results, abnormal conditions and processing processes of the monitoring tasks. According to the method, the monitoring task of the key process and the message queue can be completed in a second level, and the fault processing time is effectively shortened through timing scheduling and real-time alarming; after the abnormality is detected, various recovery means are tried, and the result of each recovery trial is automatically recorded, so that subsequent analysis is facilitated; a hierarchical design is adopted, and the problems are classified and processed according to priorities.

The invention discloses a high-reliability charging pile redundancy control system, and relates to the technical field of charging pile redundancy control. According to the high-reliability charging pile redundancy control system, running state data of a charging gun, a contactor, a communication module and the like are collected and preprocessed in real time through the multi-source data acquisition subsystem, and the running state data are compared and analyzed with reference data through the fault trend preliminary diagnosis subsystem, so that the fault trend is recognized in advance; a support vector machine model of the fault diagnosis subsystem is used to accurately identify a fault mode, and finally the redundancy control strategy generation subsystem matches an optimal strategy according to a historical state vector and a reward value to realize early warning, accurate diagnosis and dynamic redundancy control of a fault. The reliability, the fault handling capacity and the operation efficiency of a charging pile system are improved, the charging interruption risk and the operation and maintenance cost caused by faults are reduced, and the problems that a traditional charging pile cannot be charged due to the faults of a single control board, fault diagnosis is lagged, and a redundancy strategy is rigid are solved.

The embodiment of the invention provides a fault prediction method, a fault processing method and a fault processing system.The fault prediction method comprises the steps that a memory error event of a cloud server is obtained, and the memory error event has corresponding event information; based on the event information, extracting a first distribution feature of the memory error event in a basic storage unit of the cloud server memory; determining a second distribution feature of the memory error event in the instance according to the first distribution feature and an affiliation relationship between the basic storage unit and the instance; and on the basis of the second distribution feature, a fault prediction model is utilized to determine a predicted fault instance, and the fault prediction model is obtained based on sample distribution feature training of the sample memory fault event on the instance. By determining the distribution characteristics of the instance granularity, fault prediction of the instance granularity is realized based on the distribution characteristics of the instance granularity, and the refinement degree of fault prediction is improved.

The invention discloses a passive fault positioning system and method based on SRv6 data plane detection, and the method comprises the steps: deploying a data collection module at an SRv6 network node, passively collecting a passing data message, and adding detection information into the data message; analyzing an SRH extension head in the message to extract detection information, and filtering and processing the detection information to provide formatted data; summarizing detection information in the monitoring data of different nodes in different time periods, and performing association and fusion to form a to-be-analyzed data packet; according to the detection information in the to-be-analyzed data packet, performing fault positioning analysis by using a fault analysis method to lock a fault position; and performing root cause tracing based on the fault positioning position to obtain a fault cause, outputting a fault positioning result and linking a fault processing flow. According to the method, the existing information of the SRv6 data plane is multiplexed to realize non-overhead passive detection, and high-precision and real-time fault positioning of the SRv6 network is realized.

The invention belongs to the field of network communication, and provides a network fault automatic processing method and system, and the method comprises the steps: collecting a multi-source monitoring signal, and constructing a space-time matrix used for representing a network state; training the decision tree model by using a reinforcement learning algorithm, and constructing a reward function according to the root cause positioning accuracy and the repair effect; when the decision tree model determines a fault root cause, calling a software defined network (SDN) controller interface, generating a corresponding rerouting strategy according to the fault root cause, and issuing the rerouting strategy to network equipment for path adjustment; applying the rerouting strategy in a simulation environment, collecting QoS (Quality of Service) indexes before and after adjustment, and verifying the validity of a repair strategy; and feeding back a repair verification result to a training process of the decision tree model, and updating parameters of the reinforcement learning algorithm. According to the invention, the accuracy of network fault automatic processing can be improved.

The invention discloses a high-voltage interlocking detection method and device and a storage medium, and belongs to the technical field of new energy automobiles. A VIU and a high-voltage component without a high-voltage interlocking self-checking function are connected in series to form a high-voltage interlocking loop, and the method comprises the following steps: the VIU inputs a high-voltage interlocking detection signal to the high-voltage interlocking loop and obtains a detection result; determining whether the high-voltage interlocking loop has a high-voltage interlocking fault according to the detection result, and if the high-voltage interlocking loop has the high-voltage interlocking fault, sending a first high-voltage interlocking fault message to a VCU; and the VCU carries out fault processing on the first high-voltage interlocking fault message according to the vehicle state of the vehicle. According to the invention, high-voltage interlocking detection can be carried out on a high-voltage component without a high-voltage interlocking self-detection function.

The invention belongs to the technical field of network equipment management, and particularly relates to a router unified configuration and debugging method and device, electronic equipment and a storage medium. Comprising the following steps: constructing a protocol analysis model to analyze and process data packets of different protocols and standards; establishing a database with complete equipment models, constructing a command library, and analyzing and classifying different types of commands; user input is analyzed by using a natural language processing technology, user input habits and common commands are recorded through a machine learning algorithm, and personalized command recommendation is provided; a standardized operation process is designed, and the links of configuration, debugging, monitoring and fault processing of the router are covered; implementing identity verification, access control and data encryption measures, and monitoring and reporting security risks in the network in real time; according to the invention, multi-protocol support, standardized operation flow, automatic configuration and monitoring, intelligent fault processing and safe data management can be realized, and the efficiency and accuracy of network management are improved, so that the manual intervention cost is reduced.

The invention discloses an emergency broadcast decision-making method for dynamically reconstructing a broadcast list, which is characterized by comprising the following steps of: 1, monitoring running state parameters of a broadcast link in real time, the running state parameters comprising a signal quality parameter, a network link parameter, a server resource parameter and an audio stream content parameter; 2, when it is monitored that the operation state parameters are abnormal, fault diagnosis is carried out based on a preset knowledge base, and the knowledge base stores the mapping relation between fault features and disposal plans; step 3, generating a broadcast list reconstruction strategy according to the diagnosis result and a multi-dimensional characteristic factor of the current broadcast program, wherein the multi-dimensional characteristic factor at least comprises a program type, an importance level and a switching smoothness requirement; and step 4, executing automatic switching of the emergency audio streams according to the playlist reconstruction strategy. According to the invention, the problems of untimely emergency response, inaccurate decision, discontinuous fault handling and the like in a complex broadcast environment can be solved, the broadcast content can be quickly and dynamically reconstructed, and the broadcast continuity and the service quality are ensured.

The invention relates to the technical field of intelligent space operation and maintenance, and discloses an intelligent space operation and maintenance optimization method and device based on data elements, and the method comprises the steps: collecting the operation data of an Internet of Things terminal, an edge node and a cloud platform in an intelligent space, and carrying out the fusion of the operation data, and obtaining the fusion data; performing sensitive information identification and encryption on the fused data to obtain encrypted data; inputting the encrypted data into a local model of each edge node to extract equipment operation characteristics, and integrating an equipment operation characteristic set in a cloud aggregation server; performing exception identification based on the equipment operation feature set to obtain equipment exception state information; according to the method, an interpretable anomaly analysis path and a comprehensive situation awareness report are provided for operation and maintenance personnel, the fault processing efficiency is remarkably improved, and intelligent operation and maintenance management of the intelligent space is realized.

The invention relates to the technical field of vehicle safety, and provides a vehicle fault determination method, electronic equipment and a vehicle, and the method comprises the steps: determining that the vehicle has a fault, obtaining vehicle log data and fault text data, and carrying out the coding processing of the vehicle log data, and obtaining a fault signal vector; analyzing the fault text data to obtain a fault semantic vector; determining a target fusion weight, and performing fusion processing on the fault signal vector and the fault semantic vector based on the target fusion weight to obtain a multi-modal fusion vector; and inputting the multi-modal fusion vector into a pre-trained vehicle fault analysis model, processing the multi-modal fusion vector by the vehicle fault analysis model, and outputting a target fault type and a target fault processing mode. According to the method and the device, the target fault type and the target fault processing mode are determined, so that a user can clearly know the fault type of the vehicle fault, and the user can conveniently and correspondingly process the fault of the current vehicle according to the determined target fault processing mode.

The invention belongs to the technical field of power systems, and particularly relates to a power distribution line fault accurate positioning method and system, and the method comprises the steps: constructing a dynamic updating topological impedance library containing a topological structure, line parameters and terminal information; after a fault signal is triggered, the multiple terminals cooperatively collect a traveling wave signal and a timestamp and complete integrity verification; preprocessing the signal, and extracting a traveling wave leading edge feature point timestamp and a voltage-current amplitude ratio; determining a fault associated branch through time difference, impedance deviation and signal polarity screening in combination with topological impedance library information; tracing and simplifying a traveling wave path, and calculating an actual propagation speed initial fault distance; and correcting the distance according to the impedance distribution characteristics and converting into geographic coordinates for output. According to the method, the problems of large deviation and high misjudgment rate of a traditional positioning method are solved, the accuracy and response speed of fault positioning are improved, the fault handling time is shortened, the operation and maintenance cost is reduced, and safe and reliable operation of a distribution line is guaranteed.

This application provides a method for diagnosing and isolating RapidIO system link faults, belonging to the technical field of RapidIO system link fault handling. Specifically, the method includes active diagnosis, which includes: route retrieval, which searches for routes on all switch devices in the RapidIO system, using a depth-first algorithm to retrieve the system's routing tables, including the device routing table and port routing table, and obtains the device IDs of all terminal devices in the system, while proactively discovering link faults during the retrieval process; route matching, which matches the device IDs of all terminal devices in the system with the system's routing table. Based on the matching results, the method locates switch nodes with routing errors and further localizes the routing errors to the corresponding switch ports. This solution improves system reliability.

The invention discloses a fault processing method and computing equipment, and relates to the technical field of computers. The method is applied to the distributed storage system, the distributed storage system comprises at least one storage node, the storage node comprises at least one disk, and the disk comprises one or more magnetic arms; the method comprises the following steps: acquiring fault information; based on the fault information, fault types are determined, and the fault types comprise a disk fault and a magnetic arm fault; and based on the fault type, reconstructing at least one fault logic unit in the fault disk. According to the method, the fault type of the fault disk can be effectively distinguished, that is, whether the whole disk fault or the partial magnetic arm fault of the multi-magnetic-arm disk can be distinguished, so that the range of data reconstruction can be determined, the conditions of data loss and even EC degradation are avoided, and the reliability of a distributed storage system is guaranteed.

The present invention provides a fault handling method and system for voice call testing, belonging to the technical field of communication network operation and maintenance, including: receiving a fault request from a signaling system; identifying the fault type of the fault request within a preset cache period, and merging and compressing the fault requests of the same fault type; determining the first fault request in the merged set, and performing a route tracing operation on the destination IP on the primary and standby data communication device switches corresponding to the source IP of the first fault request to obtain the current network status information; judging whether there are routing anomalies and latency anomalies according to the current network status information and historical network status information; determining the fault type according to the comparison result, and generating real-time alarm information; within a preset time period, sending the real-time alarm information to the management personnel terminal. The present invention realizes the rapid and accurate processing of a large number of fault requests in a short time through real-time route tracing, historical alarm comparison, and latency anomaly detection.

The invention discloses a fault early warning and quick response processing method based on network equipment operation and maintenance data, and relates to the technical field of network equipment operation and maintenance. According to the method, network equipment hardware, software and link state data and key component energy consumption data are collected in a multi-dimensional mode, a correlation model and a rule base are constructed, quantitative grading and correlation analysis are combined, fault hidden dangers and correlation components are accurately recognized, fault early warning is achieved, an adaptive response disposal scheme is generated based on the hidden danger level, and the fault handling efficiency is improved. The execution safety is ensured through instruction verification, the fault handling efficiency is greatly improved, and the operation and maintenance cost and the fault influence are reduced; meanwhile, on the premise of guaranteeing safety, the equipment operation state is optimized, the energy consumption of key components is regulated and controlled to the optimal interval, and the energy utilization rate and the equipment operation stability are improved; according to the invention, fault early warning precision, response processing high efficiency and operation state optimization are realized, and the intelligent level and comprehensive benefits of network equipment operation and maintenance are significantly improved.

The embodiment of the invention discloses a communication network fault processing method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a working state of each communication network element in a communication network in a target time period, and determining a fault network element in each communication network element based on the working state of each communication network element; under the condition that the number of the fault network elements is multiple, for each current fault network element, determining a fault coupling degree between the current fault network element and a reference fault network element, and based on the fault coupling degree, determining a scoring result that the current fault network element is a fault root cause; and determining the processing priority of the current fault network element based on the scoring result, sorting the processing sequence of the current fault network element based on the fault priority, and obtaining the target fault processing sequence of the communication network, thereby ensuring that key faults are firstly processed, improving the fault processing efficiency, reducing the influence of the faults on the stable operation of the communication network, and improving the reliability of the communication network. And the communication experience is improved.

The application provides a power distribution network fault disposal simulation training evaluation method based on a seven-layer track node tracking array. First, the simulation training operation result information of seven links, such as a sensing node, in the fault disposal process of a dispatcher is described by establishing a seven-layer track node tracking array model. Then, the fault disposal process of the dispatcher is quantitatively evaluated by establishing a sensing node evaluation index. Secondly, the whole process from the sensing node to the archiving node of the dispatcher in disposing a certain fault is evaluated by establishing a single fault disposal evaluation index. Finally, the comprehensive evaluation of all fault disposal conditions in the simulation training of the dispatcher is performed by establishing a power distribution network fault disposal simulation training comprehensive evaluation index. The scheme can comprehensively reflect the fault disposal process of the dispatcher, better reflect the fault disposal level of the dispatcher, the method is simple and reliable, can meet the field application requirements, and has good popularization value.