289 results about "Fault handling" patented technology

The invention provides a communication network operation and maintenance fault positioning and tracking method and system, relates to the technical field, and belongs to the technical field of communication network fault diagnosis. According to the method, historical operation data, including network flow data, performance index data and alarm log data, of communication network equipment are collected, fault feature vectors are generated through training of a deep learning model, and a fault feature knowledge base is constructed; receiving operation data reported by equipment in real time to perform feature extraction, and performing similarity matching based on the fault feature knowledge base to determine a fault type; and analyzing a fault propagation path by adopting a graph traversal algorithm, determining fault root cause equipment by calculating a fault probability score of an equipment node, and generating a fault tracking report. According to the invention, accurate positioning and rapid diagnosis of communication network faults are realized, the fault processing efficiency is improved, and the network operation and maintenance cost is reduced.

The invention discloses a fault detection method and device for secondary equipment of a transformer substation. The method comprises the following steps: acquiring real-time operation parameters of the secondary equipment of the transformer substation, inputting the real-time operation parameters into a pre-trained graph neural network model to obtain equipment operation characteristics, and determining an equipment state vector according to a plurality of equipment operation characteristics in a continuous time window and a message passing mechanism; determining an equipment health degree score according to the equipment state vector and a knowledge graph, and triggering the intelligent inspection robot to execute a deep detection task under the condition that the health degree is lower than a preset health degree threshold value so as to collect target test data; determining a target fault type according to the target test data, the knowledge graph and the inference rule base, obtaining a fault processing scheme corresponding to a historical fault case, and generating corresponding maintenance guide information according to the fault processing scheme, thereby achieving the real-time detection, precise fault diagnosis and automatic maintenance of the secondary equipment of the transformer substation. And the operation safety and the maintenance efficiency of the power system are improved.

The invention discloses a dispatching automation fault intelligent processing system based on knowledge reasoning navigation. The dispatching automation fault intelligent processing system comprises a dispatching automation system environment sensing module which obtains machine room environment multi-source data in real time to serve as a data source; the intelligent analysis module performs preprocessing and labeling on the image type data and the text type data, then performs knowledge extraction to obtain entities and relationships among the entities, performs data fusion on the obtained entities, constructs an automatic duty knowledge graph, forms a scheduling automation system fault research and judgment mechanism reasoning model, and performs fault diagnosis on the scheduling automation system. A fault alarm event is generated, a knowledge reasoning environment is constructed, and a fault research and judgment conclusion is obtained through reasoning of a knowledge reasoning algorithm; an auxiliary decision-making module performs reasoning matching on the fault alarm event and the automatic duty knowledge graph through an RE2 model to obtain a fault handling auxiliary decision-making opinion; and constructing a fault exception handling flow navigation chart, and generating a fault handling coping strategy. The operation and maintenance management level of the dispatching automation machine room is improved.

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.

This application provides a communication fault handling method and system, and a device, and relates to the field of communication technologies. In this method, an out-of-band controller is connected to a network interface card, and a target network interface of the network interface card is configured to transmit a data packet between the out-of-band controller and an external network. The out-of-band controller actively obtains a target parameter that can indicate a status of communication between the out-of-band controller and the external network, to monitor whether the status of communication between the out-of-band controller and the external network is abnormal. If the target parameter indicates that the communication status is abnormal, the out-of-band controller actively sends a target command corresponding to the target parameter to the network interface card, and instructs the network interface card to execute the target command, to restore the communication status to normal. The out-of-band controller can actively monitor the communication status, and actively send, to the network interface card when the communication status is abnormal, the target command used to repair the communication status abnormality, so as to automatically restore the communication status to normal. In this way, there is no need to manually repair the communication status abnormality, which helps reduce manual costs and shorten a recovery period.

The invention provides a fault processing method and system for voice dial testing, and belongs to the technical field of communication network operation and maintenance, and the method comprises the steps: receiving a fault request from a signaling system; performing fault type identification on the fault requests in a preset cache period, and merging and compressing the fault requests of the same fault type; determining a first fault request in the merge set, and executing a routing tracking operation on a destination IP on a main / standby data communication equipment switch corresponding to a source IP of the first fault request to obtain current network state information; according to the current network state information and the historical network state information, whether routing abnormity and time delay abnormity exist or not is judged; determining a fault type according to a comparison result, and generating real-time alarm information; and in a preset time period, sending the real-time alarm information to a manager terminal. According to the invention, on the basis of real-time routing tracking, historical alarm comparison and time delay anomaly detection, large-scale fault requests can be quickly and accurately processed in a short time.

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 a system fault analysis and disposal method, device and equipment and a computer program product, and the method comprises the steps: obtaining current fault alarm information, and carrying out the retrieval in a vector knowledge base, and obtaining a historical fault retrieval result; determining a current fault solution and a corresponding fault handling agent by utilizing a large language model according to a historical fault retrieval result; according to the historical fault retrieval result and the large language model, calling a corresponding fault handling system by using a fault handling agent to handle the fault; and summarizing fault processing results by using a large language model. According to the invention, the three links of fault alarm, fault analysis and fault disposal are connected in series through the large model, intelligent management and automatic fault self-healing of the whole process are realized, and the large model is effectively connected with an external fault disposal system through an intelligent agent technology, so that the large model not only can accurately analyze the fault, but also has the fault disposal capability, and the fault disposal efficiency is improved. And the fault handling efficiency and the intelligent level are obviously 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 relates to a fault processing method and device for a distributed storage system, equipment and a storage medium, and belongs to the technical field of distributed storage, the method comprises the steps of detecting the state of a target placement group corresponding to a received read-write request, and according to the state of the target placement group corresponding to the read-write request, determining the fault of the target placement group; determining a running state of the distributed storage system; when it is detected that the distributed storage system is in a fault state, based on a message synchronization mechanism, performing message marking on the target placement group, synchronizing a generated first marking message to a first terminal and a second terminal, and meanwhile, processing the fault of the distributed storage system, the second terminal being used for sending a read-write request to the first terminal; and when it is detected that the fault of the distributed storage system is recovered, sending a second mark message to the second terminal by using the first terminal, and responding to a read-write request sent by the second terminal. The stability of the distributed storage system can be improved.

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 present invention belongs to the technical field of network communications. Disclosed are a network quality tuning method and system. The method comprises: a controller controls a forwarding unit to create an overlay service; after completing the creation of the overlay service, the forwarding unit receives routing information; the forwarding unit reports the routing information to the controller; after receiving the routing information, the controller forms routing data and records same into the database; an underlay test module tests the underlay network quality; the underlay test module reports an underlay test result to a network quality monitoring module; an overlay test module tests the overlay network quality; when the network quality monitoring module determines that the network quality has anomaly, a fault processing module forms a flow tuning policy and notifies the controller; and the controller generates a corresponding tuning configuration according to the tuning policy, sends the tuning configuration to the forwarding unit, and completes sending of the tuning configuration by means of the forwarding unit.

The invention discloses a power grid fault disposal panoramic intelligent navigation system, which comprises a fault disposal navigation affair mechanism model building module, which is used for carrying out text preprocessing on acquired power grid fault disposal data, then carrying out coding, identifying fault disposal entities, relationships and events, and carrying out data processing. The real-time alignment information is fused to establish a fault handling navigation affair mechanism model; the fault handling panoramic information reasoning module extracts fault handling entity information according to real-time information, transmits the fault handling entity information to a fault handling navigation affair mechanism model to generate a fault handling low-dimensional vector, and reasones an optimal fault handling measure by analyzing a power grid fault event and combining a power grid operation mode and power grid flow information; and the fault handling panoramic intelligent navigation module performs reasoning to obtain fault handling information, risk information, a risk control strategy and power restoration decision key factors, and generates a power restoration result in combination with on-site in-station and line patrol conditions. According to the invention, the accuracy and efficiency of power grid fault handling are improved.

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.